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Schmitzer L, Kaczmarz S, Göttler J, Hoffmann G, Kallmayer M, Eckstein HH, Hedderich DM, Kufer J, Zimmer C, Preibisch C, Hyder F, Sollmann N. Macro- and microvascular contributions to cerebral structural alterations in patients with asymptomatic carotid artery stenosis. J Cereb Blood Flow Metab 2024:271678X241238935. [PMID: 38506325 DOI: 10.1177/0271678x241238935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
Atherosclerosis can underly internal carotid artery stenosis (ICAS), a major risk factor for ischemic stroke, as well as small vessel disease (SVD). This study aimed to investigate hemodynamics and structural alterations associated with SVD in ICAS patients. 28 patients with unilateral asymptomatic ICAS and 30 age-matched controls underwent structural (T1-/T2-weighted and diffusion tensor imaging [DTI]) and hemodynamic (pseudo-continuous arterial spin labeling and dynamic susceptibility contrast) magnetic resonance imaging. SVD-related alterations were assessed using free water (FW), FW-corrected DTI, and peak-width of skeletonized mean diffusivity (PSMD). Furthermore, cortical thickness, cerebral blood flow (CBF), and capillary transit time heterogeneity (CTH) were analyzed. Ipsilateral to the stenosis, cortical thickness was significantly decreased in the posterior dorsal cingulate cortex (p = 0.024) and temporal pole (p = 0.028). ICAS patients exhibited elevated PSMD (p = 0.005), FW (p < 0.001), and contralateral alterations in FW-corrected DTI metrics. We found significantly lateralized CBF (p = 0.011) and a tendency for lateralized CTH (p = 0.067) in the white matter (WM) related to ICAS. Elevated PSMD and FW may indicate a link between SVD and WM changes. Contralateral alterations were seen in FW-corrected DTI, whereas hemodynamic and cortical changes were mainly ipsilateral, suggesting SVD might influence global brain changes concurrent with ICAS-related hemodynamic alterations.
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Affiliation(s)
- Lena Schmitzer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology & Biomedical Imaging, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stephan Kaczmarz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology & Biomedical Imaging, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Philips GmbH Market DACH, Hamburg, Germany
| | - Jens Göttler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology & Biomedical Imaging, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Gabriel Hoffmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michael Kallmayer
- Department for Vascular and Endovascular Surgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Hans-Henning Eckstein
- Department for Vascular and Endovascular Surgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Dennis Martin Hedderich
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan Kufer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology & Biomedical Imaging, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christine Preibisch
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Fahmeed Hyder
- Department of Radiology & Biomedical Imaging, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
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Bayas A, Mansmann U, Ön BI, Hoffmann VS, Berthele A, Mühlau M, Kowarik MC, Krumbholz M, Senel M, Steuerwald V, Naumann M, Hartberger J, Kerschensteiner M, Oswald E, Ruschil C, Ziemann U, Tumani H, Vardakas I, Albashiti F, Kramer F, Soto-Rey I, Spengler H, Mayer G, Kestler HA, Kohlbacher O, Hagedorn M, Boeker M, Kuhn K, Buchka S, Kohlmayer F, Kirschke JS, Behrens L, Zimmermann H, Bender B, Sollmann N, Havla J, Hemmer B. Prospective study validating a multidimensional treatment decision score predicting the 24-month outcome in untreated patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis, the ProVal-MS study. Neurol Res Pract 2024; 6:15. [PMID: 38449051 PMCID: PMC10918966 DOI: 10.1186/s42466-024-00310-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/16/2024] [Indexed: 03/08/2024] Open
Abstract
INTRODUCTION In Multiple Sclerosis (MS), patients´ characteristics and (bio)markers that reliably predict the individual disease prognosis at disease onset are lacking. Cohort studies allow a close follow-up of MS histories and a thorough phenotyping of patients. Therefore, a multicenter cohort study was initiated to implement a wide spectrum of data and (bio)markers in newly diagnosed patients. METHODS ProVal-MS (Prospective study to validate a multidimensional decision score that predicts treatment outcome at 24 months in untreated patients with clinically isolated syndrome or early Relapsing-Remitting-MS) is a prospective cohort study in patients with clinically isolated syndrome (CIS) or Relapsing-Remitting (RR)-MS (McDonald 2017 criteria), diagnosed within the last two years, conducted at five academic centers in Southern Germany. The collection of clinical, laboratory, imaging, and paraclinical data as well as biosamples is harmonized across centers. The primary goal is to validate (discrimination and calibration) the previously published DIFUTURE MS-Treatment Decision score (MS-TDS). The score supports clinical decision-making regarding the options of early (within 6 months after study baseline) platform medication (Interferon beta, glatiramer acetate, dimethyl/diroximel fumarate, teriflunomide), or no immediate treatment (> 6 months after baseline) of patients with early RR-MS and CIS by predicting the probability of new or enlarging lesions in cerebral magnetic resonance images (MRIs) between 6 and 24 months. Further objectives are refining the MS-TDS score and providing data to identify new markers reflecting disease course and severity. The project also provides a technical evaluation of the ProVal-MS cohort within the IT-infrastructure of the DIFUTURE consortium (Data Integration for Future Medicine) and assesses the efficacy of the data sharing techniques developed. PERSPECTIVE Clinical cohorts provide the infrastructure to discover and to validate relevant disease-specific findings. A successful validation of the MS-TDS will add a new clinical decision tool to the armamentarium of practicing MS neurologists from which newly diagnosed MS patients may take advantage. Trial registration ProVal-MS has been registered in the German Clinical Trials Register, `Deutsches Register Klinischer Studien` (DRKS)-ID: DRKS00014034, date of registration: 21 December 2018; https://drks.de/search/en/trial/DRKS00014034.
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Affiliation(s)
- Antonios Bayas
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany.
| | - Ulrich Mansmann
- Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Begum Irmak Ön
- Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Verena S Hoffmann
- Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Markus C Kowarik
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Markus Krumbholz
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Makbule Senel
- Department of Neurology, University Hospital Ulm, Ulm, Germany
| | - Verena Steuerwald
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany
| | - Markus Naumann
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Stenglinstrasse 2, 86156, Augsburg, Germany
| | - Julia Hartberger
- Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
| | - Martin Kerschensteiner
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Eva Oswald
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christoph Ruschil
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | | | | | - Fady Albashiti
- Medical Data Integration Center, University Hospital, LMU Munich, Munich, Germany
| | - Frank Kramer
- IT-Infrastructure for Translational Medical Research, University of Augsburg, Augsburg, Germany
| | - Iñaki Soto-Rey
- Medical Data Integration Center, Institute of Digital Medicine, University Hospital Augsburg, Augsburg, Germany
| | - Helmut Spengler
- Medical Data Integration Center, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Gerhard Mayer
- Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | | | - Oliver Kohlbacher
- Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany
- Department of Computer Science, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Marlien Hagedorn
- Medical Data Integration Center, University Hospital, LMU Munich, Munich, Germany
| | - Martin Boeker
- Institute for Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus Kuhn
- Institute for Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Stefan Buchka
- Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | | | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Lars Behrens
- Diagnostic and Interventional Neuroradiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany
| | - Hanna Zimmermann
- Institute of Neuroradiology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Joachim Havla
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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Börner-Schröder C, Huß K, Lense S, Pompignoli J, Lechner MF, Marx M, Sollmann N, Heinen F, Bonfert M. [New headache therapy for children and adolescents - repetitive magnetic stimulation of the neck muscles]. MMW Fortschr Med 2024; 166:76-79. [PMID: 38514568 DOI: 10.1007/s15006-024-3732-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Affiliation(s)
- Corinna Börner-Schröder
- Dr. von Haunersches Kinderspital, LMU Klinikum München, Abtlg. f. Päd. Neurologie u. Entwicklungsneurologie, Lindwurmstr. 4, 80337, München, Germany
| | - Kristina Huß
- Integriertes Sozialpädiatrisches Zentrum, Dr. von Haunersches Kinderspital des LMU Klinikums München, Lindwurmstraße 4, München, Germany
| | - Sahra Lense
- Integriertes Sozialpädiatrisches Zentrum, Dr. von Haunersches Kinderspital des LMU Klinikums München, Lindwurmstraße 4, München, Germany
| | - Julie Pompignoli
- Abteilung für Diagnostische und Interventionelle Neuroradiologie, Klinikum rechts der Isar, Technische Universität München, München, Germany
| | - Matthias F Lechner
- Integriertes Sozialpädiatrisches Zentrum, Dr. von Haunersches Kinderspital des LMU Klinikums München, Lindwurmstraße 4, München, Germany
| | - Maike Marx
- Integriertes Sozialpädiatrisches Zentrum, Dr. von Haunersches Kinderspital des LMU Klinikums München, Lindwurmstraße 4, München, Germany
| | - Nico Sollmann
- Abteilung für Diagnostische und Interventionelle Neuroradiologie, Klinikum rechts der Isar, Technische Universität München, München, Germany
| | - Florian Heinen
- Integriertes Sozialpädiatrisches Zentrum, Dr. von Haunersches Kinderspital des LMU Klinikums München, Lindwurmstraße 4, München, Germany
| | - Michaela Bonfert
- Dr. von Haunersches Kinderspital, LMU Klinikum München, Abtlg. f. Päd. Neurologie u. Entwicklungsneurologie, Lindwurmstr. 4, 80337, München, Germany.
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Rühling S, Dittmann J, Müller T, Husseini ME, Bodden J, Hernandez Petzsche MR, Löffler MT, Sollmann N, Baum T, Seifert-Klauss V, Wostrack M, Zimmer C, Kirschke JS. Sex differences and age-related changes in vertebral body volume and volumetric bone mineral density at the thoracolumbar spine using opportunistic QCT. Front Endocrinol (Lausanne) 2024; 15:1352048. [PMID: 38440788 PMCID: PMC10911120 DOI: 10.3389/fendo.2024.1352048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 01/22/2024] [Indexed: 03/06/2024] Open
Abstract
Objectives To quantitatively investigate the age- and sex-related longitudinal changes in trabecular volumetric bone mineral density (vBMD) and vertebral body volume at the thoracolumbar spine in adults. Methods We retrospectively included 168 adults (mean age 58.7 ± 9.8 years, 51 women) who received ≥7 MDCT scans over a period of ≥6.5 years (mean follow-up 9.0 ± 2.1 years) for clinical reasons. Level-wise vBMD and vertebral body volume were extracted from 22720 thoracolumbar vertebrae using a convolutional neural network (CNN)-based framework with asynchronous calibration and correction of the contrast media phase. Human readers conducted semiquantitative assessment of fracture status and bony degenerations. Results In the 40-60 years age group, women had a significantly higher trabecular vBMD than men at all thoracolumbar levels (p<0.05 to p<0.001). Conversely, men, on average, had larger vertebrae with lower vBMD. This sex difference in vBMD did not persist in the 60-80 years age group. While the lumbar (T12-L5) vBMD slopes in women only showed a non-significant trend of accelerated decline with age, vertebrae T1-11 displayed a distinct pattern, with women demonstrating a significantly accelerated decline compared to men (p<0.01 to p<0.0001). Between baseline and last follow-up examinations, the vertebral body volume slightly increased in women (T1-12: 1.1 ± 1.0 cm3; L1-5: 1.0 ± 1.4 cm3) and men (T1-12: 1.2 ± 1.3 cm3; L1-5: 1.5 ± 1.6 cm3). After excluding vertebrae with bony degenerations, the residual increase was only small in women (T1-12: 0.6 ± 0.6 cm3; L1-5: 0.7 ± 0.7 cm3) and men (T1-12: 0.7 ± 0.6 cm3; L1-5: 1.2 ± 0.8 cm3). In non-degenerated vertebrae, the mean change in volume was <5% of the respective vertebral body volumes. Conclusion Sex differences in thoracolumbar vBMD were apparent before menopause, and disappeared after menopause, likely attributable to an accelerated and more profound vBMD decline in women at the thoracic spine. In patients without advanced spine degeneration, the overall volumetric changes in the vertebral body appeared subtle.
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Affiliation(s)
- Sebastian Rühling
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jonas Dittmann
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Tobias Müller
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Malek El Husseini
- Department of Informatics, TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Moritz R Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian T Löffler
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Vanadin Seifert-Klauss
- Department of Gynaecology, Interdisciplinary Osteoporosis Center, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Maria Wostrack
- Department of Neurosurgery, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, TUM School of Medicine and Health, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Sollmann N, Hoffmann G, Schramm S, Reichert M, Hernandez Petzsche M, Strobel J, Nigris L, Kloth C, Rosskopf J, Börner C, Bonfert M, Berndt M, Grön G, Müller HP, Kassubek J, Kreiser K, Koerte IK, Liebl H, Beer A, Zimmer C, Beer M, Kaczmarz S. Arterial Spin Labeling (ASL) in Neuroradiological Diagnostics - Methodological Overview and Use Cases. ROFO-FORTSCHR RONTG 2024; 196:36-51. [PMID: 37467779 DOI: 10.1055/a-2119-5574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
BACKGROUND Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI)-based technique using labeled blood-water of the brain-feeding arteries as an endogenous tracer to derive information about brain perfusion. It enables the assessment of cerebral blood flow (CBF). METHOD This review aims to provide a methodological and technical overview of ASL techniques, and to give examples of clinical use cases for various diseases affecting the central nervous system (CNS). There is a special focus on recent developments including super-selective ASL (ssASL) and time-resolved ASL-based magnetic resonance angiography (MRA) and on diseases commonly not leading to characteristic alterations on conventional structural MRI (e. g., concussion or migraine). RESULTS ASL-derived CBF may represent a clinically relevant parameter in various pathologies such as cerebrovascular diseases, neoplasms, or neurodegenerative diseases. Furthermore, ASL has also been used to investigate CBF in mild traumatic brain injury or migraine, potentially leading to the establishment of imaging-based biomarkers. Recent advances made possible the acquisition of ssASL by selective labeling of single brain-feeding arteries, enabling spatial perfusion territory mapping dependent on blood flow of a specific preselected artery. Furthermore, ASL-based MRA has been introduced, providing time-resolved delineation of single intracranial vessels. CONCLUSION Perfusion imaging by ASL has shown promise in various diseases of the CNS. Given that ASL does not require intravenous administration of a gadolinium-based contrast agent, it may be of particular interest for investigations in pediatric cohorts, patients with impaired kidney function, patients with relevant allergies, or patients that undergo serial MRI for clinical indications such as disease monitoring. KEY POINTS · ASL is an MRI technique that uses labeled blood-water as an endogenous tracer for brain perfusion imaging.. · It allows the assessment of CBF without the need for administration of a gadolinium-based contrast agent.. · CBF quantification by ASL has been used in several pathologies including brain tumors or neurodegenerative diseases.. · Vessel-selective ASL methods can provide brain perfusion territory mapping in cerebrovascular diseases.. · ASL may be of particular interest in patient cohorts with caveats concerning gadolinium administration..
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Gabriel Hoffmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Miriam Reichert
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Moritz Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Lorenzo Nigris
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Corinna Börner
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michaela Bonfert
- LMU Hospital, Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maria Berndt
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy III, University Hospital Ulm, Ulm, Germany
| | | | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, Ulm, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Inga K Koerte
- cBrain, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, United States
- Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Hans Liebl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, Berufsgenossenschaftliche Unfallklinik Murnau, Murnau, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- MoMan - Center for Translational Imaging, University Hospital Ulm, Ulm, Germany
- i2SouI - Innovative Imaging in Surgical Oncology, University Hospital Ulm, Ulm, Germany
| | - Stephan Kaczmarz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Market DACH, Philips GmbH, Hamburg, Germany
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6
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Kerscher SR, Zipfel J, Bevot A, Sollmann N, Haas-Lude K, Tellermann J, Schuhmann MU. Non-Invasive Quantitative Approximation of Intracranial Pressure in Pediatric Idiopathic Intracranial Hypertension Based on Point-of-Care Ultrasound of the Optic Nerve Sheath Diameter. Brain Sci 2023; 14:32. [PMID: 38248247 PMCID: PMC10812972 DOI: 10.3390/brainsci14010032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/22/2023] [Accepted: 12/25/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND To investigate whether ultrasound-based optic nerve sheath diameter (US-ONSD) is a reliable measure to follow up children with idiopathic intracranial hypertension (IIH). In addition, to analyze the inter- and intra-individual relationships between US-ONSD and intracranial pressure (ICP), and to investigate whether an individualized mathematical regression equation obtained from two paired US-ONSD/ICP values can be used to approximate ICP from US-ONSD values. METHODS 159 US examinations and 53 invasive ICP measures via lumbar puncture (LP) were performed in 28 children with IIH. US-ONSD was measured using a 12 Mhz linear transducer and compared to ICP values. In 15 children, a minimum of 2 paired US-ONSD/ICP determinations were performed, and repeated-measures correlation (rmcorr) and intra-individual correlations were analyzed. RESULTS The cohort correlation between US-ONSD and ICP was moderate (r = 0.504, p < 0.01). Rmcorr (r = 0.91, p < 0.01) and intra-individual correlations (r = 0.956-1) of US-ONSD and ICP were excellent. A mathematical regression equation can be calculated from two paired US-ONSD/ICP values and applied to the individual patient to approximate ICP from US-ONSD. CONCLUSIONS Related to excellent intra-individual correlations between US-ONSD and ICP, an individualized regression formula, created from two pairs of US-ONSD/ICP values, may be used to directly approximate ICP based on US-ONSD values. Hence, US-ONSD may become a non-invasive and reliable measure to control treatment efficacy in pediatric IIH.
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Affiliation(s)
- Susanne Regina Kerscher
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
- Department of Neurosurgery and Neurotechnology, Division of Pediatric Neurosurgery, University Hospital of Tuebingen, 72076 Tuebingen, Germany; (J.Z.); (J.T.); (M.U.S.)
| | - Julian Zipfel
- Department of Neurosurgery and Neurotechnology, Division of Pediatric Neurosurgery, University Hospital of Tuebingen, 72076 Tuebingen, Germany; (J.Z.); (J.T.); (M.U.S.)
| | - Andrea Bevot
- Department of Pediatric Neurology and Developmental Medicine, University Children’ s Hospital of Tuebingen, 72076 Tuebingen, Germany; (A.B.); (K.H.-L.)
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Karin Haas-Lude
- Department of Pediatric Neurology and Developmental Medicine, University Children’ s Hospital of Tuebingen, 72076 Tuebingen, Germany; (A.B.); (K.H.-L.)
| | - Jonas Tellermann
- Department of Neurosurgery and Neurotechnology, Division of Pediatric Neurosurgery, University Hospital of Tuebingen, 72076 Tuebingen, Germany; (J.Z.); (J.T.); (M.U.S.)
| | - Martin Ulrich Schuhmann
- Department of Neurosurgery and Neurotechnology, Division of Pediatric Neurosurgery, University Hospital of Tuebingen, 72076 Tuebingen, Germany; (J.Z.); (J.T.); (M.U.S.)
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7
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Kloth C, Beck A, Sollmann N, Beer M, Horger M, Thaiss WM. Imaging of Pathologies of the Temporal Bone and Middle Ear: Inflammatory Diseases, Their Mimics and Potential Complications-Pictorial Review. Tomography 2023; 9:2190-2210. [PMID: 38133074 PMCID: PMC10747582 DOI: 10.3390/tomography9060170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
Imaging of the temporal bone and middle ear is challenging for radiologists due to the abundance of distinct anatomical structures and the plethora of possible pathologies. The basis for a precise diagnosis is knowledge of the underlying anatomy as well as the clinical presentation and the individual patient's otological status. In this article, we aimed to summarize the most common inflammatory lesions of the temporal bone and middle ear, describe their specific imaging characteristics, and highlight their differential diagnoses. First, we introduce anatomical and imaging fundamentals. Additionally, a point-to-point comparison of the radiological and histological features of the wide spectrum of inflammatory diseases of the temporal bone and middle ear in context with a review of the current literature and current trends is given.
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Affiliation(s)
- Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (N.S.); (M.B.); (W.M.T.)
- Radiology and Radiation Therapy Lindau, Friedrichshafener Str. 83, 88131 Lindau (Lake Constance), Germany
| | - Annika Beck
- Institute of Pathology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany;
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (N.S.); (M.B.); (W.M.T.)
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (N.S.); (M.B.); (W.M.T.)
| | - Marius Horger
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany;
| | - Wolfgang Maximilian Thaiss
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (N.S.); (M.B.); (W.M.T.)
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany;
- Department of Nuclear Medicine, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany
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8
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Strobel J, Müller HP, Ludolph AC, Beer AJ, Sollmann N, Kassubek J. New Perspectives in Radiological and Radiopharmaceutical Hybrid Imaging in Progressive Supranuclear Palsy: A Systematic Review. Cells 2023; 12:2776. [PMID: 38132096 PMCID: PMC10742083 DOI: 10.3390/cells12242776] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 11/28/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by four-repeat tau deposition in various cell types and anatomical regions, and can manifest as several clinical phenotypes, including the most common phenotype, Richardson's syndrome. The limited availability of biomarkers for PSP relates to the overlap of clinical features with other neurodegenerative disorders, but identification of a growing number of biomarkers from imaging is underway. One way to increase the reliability of imaging biomarkers is to combine different modalities for multimodal imaging. This review aimed to provide an overview of the current state of PSP hybrid imaging by combinations of positron emission tomography (PET) and magnetic resonance imaging (MRI). Specifically, combined PET and MRI studies in PSP highlight the potential of [18F]AV-1451 to detect tau, but also the challenge in differentiating PSP from other neurodegenerative diseases. Studies over the last years showed a reduced synaptic density in [11C]UCB-J PET, linked [11C]PK11195 and [18F]AV-1451 markers to disease progression, and suggested the potential role of [18F]RO948 PET for identifying tau pathology in subcortical regions. The integration of quantitative global and regional gray matter analysis by MRI may further guide the assessment of reduced cortical thickness or volume alterations, and diffusion MRI could provide insight into microstructural changes and structural connectivity in PSP. Challenges in radiopharmaceutical biomarkers and hybrid imaging require further research targeting markers for comprehensive PSP diagnosis.
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Affiliation(s)
- Joachim Strobel
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Hans-Peter Müller
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
| | - Albert C. Ludolph
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
| | - Ambros J. Beer
- Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany;
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Jan Kassubek
- Department of Neurology, University Hospital Ulm, 89081 Ulm, Germany; (H.-P.M.); (A.C.L.); (J.K.)
- German Center for Neurodegenerative Diseases (DZNE), Ulm University, 89081 Ulm, Germany
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9
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Sollmann N. Editorial for "Mismatch of MRI White Matter Hyperintensities and Gait Function in Patients With Cerebral Small Vessel Disease". J Magn Reson Imaging 2023. [PMID: 37929925 DOI: 10.1002/jmri.29122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 11/07/2023] Open
Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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10
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Sollmann N, Zhang H, Kloth C, Zimmer C, Wiestler B, Rosskopf J, Kreiser K, Schmitz B, Beer M, Krieg SM. Modern preoperative imaging and functional mapping in patients with intracranial glioma. ROFO-FORTSCHR RONTG 2023; 195:989-1000. [PMID: 37224867 DOI: 10.1055/a-2083-8717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Magnetic resonance imaging (MRI) in therapy-naïve intracranial glioma is paramount for neuro-oncological diagnostics, and it provides images that are helpful for surgery planning and intraoperative guidance during tumor resection, including assessment of the involvement of functionally eloquent brain structures. This study reviews emerging MRI techniques to depict structural information, diffusion characteristics, perfusion alterations, and metabolism changes for advanced neuro-oncological imaging. In addition, it reflects current methods to map brain function close to a tumor, including functional MRI and navigated transcranial magnetic stimulation with derived function-based tractography of subcortical white matter pathways. We conclude that modern preoperative MRI in neuro-oncology offers a multitude of possibilities tailored to clinical needs, and advancements in scanner technology (e. g., parallel imaging for acceleration of acquisitions) make multi-sequence protocols increasingly feasible. Specifically, advanced MRI using a multi-sequence protocol enables noninvasive, image-based tumor grading and phenotyping in patients with glioma. Furthermore, the add-on use of preoperatively acquired MRI data in combination with functional mapping and tractography facilitates risk stratification and helps to avoid perioperative functional decline by providing individual information about the spatial location of functionally eloquent tissue in relation to the tumor mass. KEY POINTS:: · Advanced preoperative MRI allows for image-based tumor grading and phenotyping in glioma.. · Multi-sequence MRI protocols nowadays make it possible to assess various tumor characteristics (incl. perfusion, diffusion, and metabolism).. · Presurgical MRI in glioma is increasingly combined with functional mapping to identify and enclose individual functional areas.. · Advancements in scanner technology (e. g., parallel imaging) facilitate increasing application of dedicated multi-sequence imaging protocols.. CITATION FORMAT: · Sollmann N, Zhang H, Kloth C et al. Modern preoperative imaging and functional mapping in patients with intracranial glioma. Fortschr Röntgenstr 2023; 195: 989 - 1000.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, United States
| | - Haosu Zhang
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TranslaTUM - Central Institute for Translational Cancer Research, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Bernd Schmitz
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Sandro M Krieg
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
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11
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Yu D, Chuang KH, Sollmann N. Editorial: New challenges and future perspectives in brain imaging methods. Front Neurosci 2023; 17:1265054. [PMID: 38027500 PMCID: PMC10646571 DOI: 10.3389/fnins.2023.1265054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023] Open
Affiliation(s)
- Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Kai-Hsiang Chuang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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12
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Grosse L, Schnabel JF, Börner-Schröder C, Späh MA, Meuche AC, Sollmann N, Breuer U, Warken B, Hösl M, Heinen F, Berweck S, Schröder SA, Bonfert MV. Safety and Feasibility of Functional Repetitive Neuromuscular Magnetic Stimulation of the Gluteal Muscles in Children and Adolescents with Bilateral Spastic Cerebral Palsy. Children (Basel) 2023; 10:1768. [PMID: 38002859 PMCID: PMC10670153 DOI: 10.3390/children10111768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 10/23/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023]
Abstract
Background: For children and adolescents affected by bilateral spastic cerebral palsy (BSCP), non-invasive neurostimulation with repetitive neuromuscular magnetic stimulation (rNMS) combined with physical exercises, conceptualized as functional rNMS (frNMS), represents a novel treatment approach. Methods: In this open-label study, six children and two adolescents (10.4 ± 2.5 years) with BSCP received a frNMS intervention targeting the gluteal muscles (12 sessions within 3 weeks). Results: In 77.1% of the sessions, no side effects were reported. In 16.7%, 6.3% and 5.2% of the sessions, a tingling sensation, feelings of pressure/warmth/cold or very shortly lasting pain appeared, respectively. frNMS was highly accepted by families (100% adherence) and highly feasible (97.9% of treatment per training protocol). A total of 100% of participants would repeat frNMS, and 87.5% would recommend it. The Canadian Occupational Performance Measure demonstrated clinically important benefits for performance in 28% and satisfaction in 42% of mobility-related tasks evaluated by caregivers for at least one follow-up time point (6 days and 6 weeks post intervention). Two patients accomplished goal attainment for one mobility-related goal each. One patient experienced improvement for both predefined goals, and another participant experienced improvement in one and outreach of the other goal as assessed with the goal attainment scale. Conclusions: frNMS is a safe and well-accepted neuromodulatory approach that could improve the quality of life, especially in regard to activity and participation, of children and adolescents with BSCP. Larger-scaled studies are needed to further explore the effects of frNMS in this setting.
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Affiliation(s)
- Leonie Grosse
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Julian F. Schnabel
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Corinna Börner-Schröder
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Malina A. Späh
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Anne C. Meuche
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany
| | - Ute Breuer
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Birgit Warken
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Matthias Hösl
- Gait and Motion Analysis Laboratory, Schoen Clinic Vogtareuth, 83569 Vogtareuth, Germany
| | - Florian Heinen
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Steffen Berweck
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- Specialist Center for Pediatric Neurology, Neurorehabilitation and Epileptology, Schoen Clinic Vogtareuth, 83569 Vogtareuth, Germany
| | - Sebastian A. Schröder
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
| | - Michaela V. Bonfert
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80337 Munich, Germany (S.B.)
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80337 Munich, Germany
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13
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Börner-Schröder C, Lang M, Urban G, Zaidenstadt E, Staisch J, Hauser A, Hannibal I, Huß K, Klose B, Lechner MF, Sollmann N, Landgraf MN, Heinen F, Bonfert MV. Neuromodulation in Pediatric Migraine using Repetitive Neuromuscular Magnetic Stimulation: A Feasibility Study. Children (Basel) 2023; 10:1764. [PMID: 38002855 PMCID: PMC10670480 DOI: 10.3390/children10111764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/23/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023]
Abstract
Migraine has a relevant impact on pediatric health. Non-pharmacological modalities for its management are urgently needed. This study assessed the safety, feasibility, acceptance, and efficacy of repetitive neuromuscular magnetic stimulation (rNMS) in pediatric migraine. A total of 13 patients with migraine, ≥6 headache days during baseline, and ≥1 myofascial trigger point in the upper trapezius muscles (UTM) received six rNMS sessions within 3 weeks. Headache frequency, intensity, and medication intake were monitored using headache calendars; headache-related impairment and quality of life were measured using PedMIDAS and KINDL questionnaires. Muscular involvement was assessed using pressure pain thresholds (PPT). Adherence yielded 100%. In 82% of all rNMS sessions, no side effects occurred. All participants would recommend rNMS and would repeat it. Headache frequency, medication intake, and PedMIDAS scores decreased from baseline to follow-up (FU), trending towards statistical significance (p = 0.089; p = 0.081, p = 0.055). A total of 7 patients were classified as responders, with a ≥25% relative reduction in headache frequency. PPT above the UTM significantly increased from pre- to post-assessment, which sustained until FU (p = 0.015 and 0.026, respectively). rNMS was safe, feasible, well-accepted, and beneficial on the muscular level. The potential to reduce headache-related symptoms together with PPT changes of the targeted UTM may underscore the interplay of peripheral and central mechanisms conceptualized within the trigemino-cervical complex.
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Affiliation(s)
- Corinna Börner-Schröder
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Magdalena Lang
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Giada Urban
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Erik Zaidenstadt
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Jacob Staisch
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Ari Hauser
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Iris Hannibal
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Kristina Huß
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Birgit Klose
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Matthias F. Lechner
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Mirjam N. Landgraf
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Florian Heinen
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
| | - Michaela V. Bonfert
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital, LMU Munich, 80337 Munich, Germany; (C.B.-S.); (I.H.); (M.N.L.); (F.H.)
- LMU Center for Children with Medical Complexity-iSPZ Hauner, LMU University Hospital, LMU Munich, 80337 Munich, Germany
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14
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Kreiser K, Sollmann N, Renz M. Importance and potential of simulation training in interventional radiology. ROFO-FORTSCHR RONTG 2023; 195:883-889. [PMID: 37137320 DOI: 10.1055/a-2066-8009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND Simulation training is a common method in many medical disciplines and is used to teach content knowledge, manual skills, and team skills without potential patient danger. METHODS Simulation models and methods in interventional radiology are explained. Strengths and weaknesses of both simulators for non-vascular and vascular radiological interventions are highlighted and necessary future developments are addressed. RESULTS Both custom-made and commercially available phantoms are available for non-vascular interventions. Interventions are performed under ultrasound guidance, with computed tomography assistance, or using mixed-reality methods. The wear and tear of physical phantoms can be countered with in-house production of 3D-printed models. Vascular interventions can be trained on silicone models or hightech simulators. Increasingly, patient-specific anatomies are replicated and simulated pre-intervention. The level of evidence of all procedures is low. CONCLUSION Numerous simulation methods are available in interventional radiology. Training on silicone models and hightech simulators for vascular interventions has the potential to reduce procedural time. This is associated with reduced radiation dose for both patient and physician, which can also contribute to improved patient outcome, at least in endovascular stroke treatment. Although a higher level of evidence should be achieved, simulation training should already be integrated into the guidelines of the professional societies and accordingly into the curricula of the radiology departments. KEY POINTS · There are numerous simulation methods for nonvascular and vascular radiologic interventions.. · Puncture models can be purchased commercially or made using 3D printing.. · Silicone models and hightech simulators allow patient-specific training.. · Simulation training reduces intervention time, benefiting both the patient and the physician.. · A higher level of evidence is possible via proof of reduced procedural times.. CITATION FORMAT · Kreiser K, Sollmann N, Renz M. Importance and potential of simulation training in interventional radiology. Fortschr Röntgenstr 2023; 195: 883 - 889.
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Affiliation(s)
- Kornelia Kreiser
- RKU, Department of Neuroradiology, University Hospital Ulm, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
| | - Martin Renz
- Departement of Diagnostic and Interventional Neuroradiology, Technical University of Munich Hospital Rechts der Isar, Munchen, Germany
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15
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Grosse L, Meuche AC, Parzefall B, Börner C, Schnabel JF, Späh MA, Klug P, Sollmann N, Klich L, Hösl M, Heinen F, Berweck S, Schröder SA, Bonfert MV. Functional Repetitive Neuromuscular Magnetic Stimulation (frNMS) Targeting the Tibialis Anterior Muscle in Children with Upper Motor Neuron Syndrome: A Feasibility Study. Children (Basel) 2023; 10:1584. [PMID: 37892247 PMCID: PMC10605892 DOI: 10.3390/children10101584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/07/2023] [Accepted: 09/11/2023] [Indexed: 10/29/2023]
Abstract
Non-invasive neurostimulation as an adjunctive intervention to task-specific motor training is an approach to foster motor performance in patients affected by upper motor neuron syndrome (UMNS). Here, we present first-line data of repetitive neuromuscular magnetic stimulation (rNMS) in combination with personalized task-specific physical exercises targeting the tibialis anterior muscle to improve ankle dorsiflexion (functional rNMS (frNMS)). The main objective of this pilot study was to assess the feasibility in terms of adherence to frNMS, safety and practicability of frNMS, and satisfaction with frNMS. First, during 10 training sessions, only physical exercises were performed (study period (SP) A). After a 1 week break, frNMS was delivered during 10 sessions (SPC). Twelve children affected by UMNS (mean age 8.9 ± 1.6 years) adhered to 93% (SPA) and 94% (SPC) of the sessions, and omittance was not related to the intervention itself in any case. frNMS was safe (no AEs reported in 88% of sessions, no AE-related discontinuation). The practicability of and satisfaction with frNMS were high. Patient/caregiver-reported outcomes revealed meaningful benefits on the individual level. The strength of the ankle dorsiflexors (MRC score) clinically meaningfully increased in four participants as spasticity of ankle plantar flexors (Tardieu scores) decreased in four participants after SPC. frNMS was experienced as a feasible intervention for children affected by UMNS. Together with the beneficial effects achieved on the individual level in some participants, this first study supports further real-world, large-scale, sham-controlled investigations to investigate the specific effects and distinct mechanisms of action of frNMS.
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Affiliation(s)
- Leonie Grosse
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Anne C. Meuche
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Barbara Parzefall
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Corinna Börner
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Julian F. Schnabel
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Malina A. Späh
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Pia Klug
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany
| | - Luisa Klich
- Specialist Center for Pediatric Neurology, Neurorehabilitation and Epileptology, Schoen Clinic Vogtareuth, 83569 Vogtareuth, Germany
| | - Matthias Hösl
- Gait and Motion Analysis Laboratory, Schoen Clinic Vogtareuth, Krankenhausstr. 20, 83569 Vogtareuth, Germany
| | - Florian Heinen
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Steffen Berweck
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- Specialist Center for Pediatric Neurology, Neurorehabilitation and Epileptology, Schoen Clinic Vogtareuth, 83569 Vogtareuth, Germany
| | - Sebastian A. Schröder
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
| | - Michaela V. Bonfert
- Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics—Dr. von Hauner Children’s Hospital, LMU Hospital, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
- LMU Center for Children with Medical Complexity—iSPZ Hauner, Ludwig-Maximilians-Universität München, 80336 Munich, Germany
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Bodden J, Dieckmeyer M, Sollmann N, Rühling S, Prucker P, Löffler MT, Burian E, Subburaj K, Zimmer C, Kirschke JS, Baum T. Long-term reproducibility of opportunistically assessed vertebral bone mineral density and texture features in routine clinical multi-detector computed tomography using an automated segmentation framework. Quant Imaging Med Surg 2023; 13:5472-5482. [PMID: 37711780 PMCID: PMC10498219 DOI: 10.21037/qims-23-19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 06/08/2023] [Indexed: 09/16/2023]
Abstract
Background To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment. Methods Patients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [varianceglobal, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t-tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability. Results SRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of varianceglobal ranged from 1.60% to 3.03%. Conclusions Opportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features.
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Affiliation(s)
- Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Sebastian Rühling
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Philipp Prucker
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian T. Löffler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Karupppasamy Subburaj
- Department of Mechanical and Production Engineering, Aarhus University, Aarhus, Denmark
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Dieckmeyer M, Sollmann N, Kupfer K, Löffler MT, Paprottka KJ, Kirschke JS, Baum T. Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose. Clin Neuroradiol 2023; 33:591-610. [PMID: 36862232 PMCID: PMC10449676 DOI: 10.1007/s00062-023-01271-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/24/2023] [Indexed: 03/03/2023]
Abstract
In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.
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Affiliation(s)
- Michael Dieckmeyer
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Karina Kupfer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian T. Löffler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Karolin J. Paprottka
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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18
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Feuerriegel GC, Burian E, Sollmann N, Leonhardt Y, Burian G, Griesbauer M, Bumm C, Makowski MR, Probst M, Probst FA, Karampinos DC, Folwaczny M. Evaluation of 3D MRI for early detection of bone edema associated with apical periodontitis. Clin Oral Investig 2023; 27:5403-5412. [PMID: 37464086 PMCID: PMC10492681 DOI: 10.1007/s00784-023-05159-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 07/11/2023] [Indexed: 07/20/2023]
Abstract
OBJECTIVES To detect and evaluate early signs of apical periodontitis using MRI based on a 3D short-tau-inversion-recovery (STIR) sequence compared to conventional panoramic radiography (OPT) and periapical radiographs in patients with apical periodontitis. MATERIALS AND METHODS Patients with clinical evidence of periodontal disease were enrolled prospectively and received OPT as well as MRI of the viscerocranium including a 3D-STIR sequence. The MRI sequences were assessed for the occurrence and extent of bone changes associated with apical periodontitis including bone edema, periradicular cysts, and dental granulomas. OPTs and intraoral periapical radiographs, if available, were assessed for corresponding periapical radiolucencies using the periapical index (PAI). RESULTS In total, 232 teeth of 37 patients (mean age 62±13.9 years, 18 women) were assessed. In 69 cases reactive bone edema was detected on MRI with corresponding radiolucency according to OPT. In 105 cases edema was detected without corresponding radiolucency on OPT. The overall extent of edema measured on MRI was significantly larger compared to the radiolucency on OPT (mean: STIR 2.4±1.4 mm, dental radiograph 1.3±1.2 mm, OPT 0.8±1.1 mm, P=0.01). The overall PAI score was significantly higher on MRI compared to OPT (mean PAI: STIR 1.9±0.7, dental radiograph 1.3±0.5, OPT 1.2±0.7, P=0.02). CONCLUSION Early detection and assessment of bone changes of apical periodontitis using MRI was feasible while the extent of bone edema measured on MRI exceeded the radiolucencies measured on OPT. CLINICAL RELEVANCE In clinical routine, dental MRI might be useful for early detection and assessment of apical periodontitis before irreversible bone loss is detected on conventional panoramic and intraoral periapical radiographs.
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Affiliation(s)
- Georg C. Feuerriegel
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675 Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675 Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Yannik Leonhardt
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675 Munich, Germany
| | - Gintare Burian
- Department of Prosthodontics, LMU University Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Magdalena Griesbauer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Caspar Bumm
- Department of Restorative Dentistry and Periodontology, LMU University Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Marcus R. Makowski
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675 Munich, Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Florian A. Probst
- Department of Restorative Dentistry and Periodontology, LMU University Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Dimitrios C. Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, 81675 Munich, Germany
| | - Matthias Folwaczny
- Department of Restorative Dentistry and Periodontology, LMU University Hospital, Ludwig-Maximilians-University, Munich, Germany
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19
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Pankatz L, Rojczyk P, Seitz-Holland J, Bouix S, Jung LB, Wiegand TLT, Bonke EM, Sollmann N, Kaufmann E, Carrington H, Puri T, Rathi Y, Coleman MJ, Pasternak O, George MS, McAllister TW, Zafonte R, Stein MB, Marx CE, Shenton ME, Koerte IK. Adverse Outcome Following Mild Traumatic Brain Injury Is Associated with Microstructure Alterations at the Gray and White Matter Boundary. J Clin Med 2023; 12:5415. [PMID: 37629457 PMCID: PMC10455493 DOI: 10.3390/jcm12165415] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/31/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
The gray matter/white matter (GM/WM) boundary of the brain is vulnerable to shear strain associated with mild traumatic brain injury (mTBI). It is, however, unknown whether GM/WM microstructure is associated with long-term outcomes following mTBI. The diffusion and structural MRI data of 278 participants between 18 and 65 years of age with and without military background from the Department of Defense INTRuST study were analyzed. Fractional anisotropy (FA) was extracted at the GM/WM boundary across the brain and for each lobe. Additionally, two conventional analytic approaches were used: whole-brain deep WM FA (TBSS) and whole-brain cortical thickness (FreeSurfer). ANCOVAs were applied to assess differences between the mTBI cohort (n = 147) and the comparison cohort (n = 131). Associations between imaging features and post-concussive symptom severity, and functional and cognitive impairment were investigated using partial correlations while controlling for mental health comorbidities that are particularly common among military cohorts and were present in both the mTBI and comparison group. Findings revealed significantly lower whole-brain and lobe-specific GM/WM boundary FA (p < 0.011), and deep WM FA (p = 0.001) in the mTBI cohort. Whole-brain and lobe-specific GM/WM boundary FA was significantly negatively correlated with post-concussive symptoms (p < 0.039), functional (p < 0.016), and cognitive impairment (p < 0.049). Deep WM FA was associated with functional impairment (p = 0.002). Finally, no significant difference was observed in cortical thickness, nor between cortical thickness and outcome (p > 0.05). Findings from this study suggest that microstructural alterations at the GM/WM boundary may be sensitive markers of adverse long-term outcomes following mTBI.
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Affiliation(s)
- Lara Pankatz
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
| | - Philine Rojczyk
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- Département de génie logiciel et TI, École de Technologie Supérieure, Université du Québec, Montreal, QC H3C 1K3, Canada
| | - Leonard B. Jung
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
| | - Tim L. T. Wiegand
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
| | - Elena M. Bonke
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- Graduate School of Systemic Neuroscience, Ludwig-Maximilians-Universität, 82152 Planegg, Germany
| | - Nico Sollmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Elisabeth Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- Department of Neurology, University Hospital, LMU, 81377 Munich, Germany
| | - Holly Carrington
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- Brain Injury Research Center of Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Twishi Puri
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
| | - Michael J. Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Mark S. George
- Psychiatry Department, Medical University of South Carolina, Charleston, SC 29425, USA;
- Ralph H. Johnson VA Medical Center, Charleston, SC 29401, USA
| | - Thomas W. McAllister
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Ross Zafonte
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Charlestown, MA 02129, USA;
- Department of Physical Medicine and Rehabilitation, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Murray B. Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- School of Public Health, University of California San Diego, La Jolla, CA 92093, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Christine E. Marx
- VA Mid-Atlantic Mental Illness Research and Clinical Center (MIRECC) and Durham VA Medical Center, Durham, NC 27705, USA;
- Department of Psychiatry and Behavior Sciences, Duke University School of Medicine, Durham, NC 27710, USA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Somerville, MA 02145, USA; (L.P.); (P.R.); (J.S.-H.); (S.B.); (L.B.J.); (T.L.T.W.); (E.M.B.); (N.S.); (E.K.); (H.C.); (T.P.); (Y.R.); (M.J.C.); (O.P.); (M.E.S.)
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, 80336 Munich, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Graduate School of Systemic Neuroscience, Ludwig-Maximilians-Universität, 82152 Planegg, Germany
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Schlaeger S, Drummer K, El Husseini M, Kofler F, Sollmann N, Schramm S, Zimmer C, Wiestler B, Kirschke JS. Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset. Eur Radiol 2023; 33:5882-5893. [PMID: 36928566 PMCID: PMC10326102 DOI: 10.1007/s00330-023-09512-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/17/2022] [Accepted: 02/03/2023] [Indexed: 03/18/2023]
Abstract
OBJECTIVES T2-weighted (w) fat sat (fs) sequences, which are important in spine MRI, require a significant amount of scan time. Generative adversarial networks (GANs) can generate synthetic T2-w fs images. We evaluated the potential of synthetic T2-w fs images by comparing them to their true counterpart regarding image and fat saturation quality, and diagnostic agreement in a heterogenous, multicenter dataset. METHODS A GAN was used to synthesize T2-w fs from T1- and non-fs T2-w. The training dataset comprised scans of 73 patients from two scanners, and the test dataset, scans of 101 patients from 38 multicenter scanners. Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured in true and synthetic T2-w fs. Two neuroradiologists graded image (5-point scale) and fat saturation quality (3-point scale). To evaluate whether the T2-w fs images are indistinguishable, a Turing test was performed by eleven neuroradiologists. Six pathologies were graded on the synthetic protocol (with synthetic T2-w fs) and the original protocol (with true T2-w fs) by the two neuroradiologists. RESULTS aSNR and aCNR were not significantly different between the synthetic and true T2-w fs images. Subjective image quality was graded higher for synthetic T2-w fs (p = 0.023). In the Turing test, synthetic and true T2-w fs could not be distinguished from each other. The intermethod agreement between synthetic and original protocol ranged from substantial to almost perfect agreement for the evaluated pathologies. DISCUSSION The synthetic T2-w fs might replace a physical T2-w fs. Our approach validated on a challenging, multicenter dataset is highly generalizable and allows for shorter scan protocols. KEY POINTS • Generative adversarial networks can be used to generate synthetic T2-weighted fat sat images from T1- and non-fat sat T2-weighted images of the spine. • The synthetic T2-weighted fat sat images might replace a physically acquired T2-weighted fat sat showing a better image quality and excellent diagnostic agreement with the true T2-weighted fat images. • The present approach validated on a challenging, multicenter dataset is highly generalizable and allows for significantly shorter scan protocols.
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Affiliation(s)
- Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
| | - Katharina Drummer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Malek El Husseini
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Munich, Germany
- TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany
- Helmholtz AI, Helmholtz Zentrum München, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Rühling S, Schwarting J, Froelich MF, Löffler MT, Bodden J, Hernandez Petzsche MR, Baum T, Wostrack M, Aftahy AK, Seifert-Klauss V, Sollmann N, Zimmer C, Kirschke JS, Tollens F. Cost-effectiveness of opportunistic QCT-based osteoporosis screening for the prediction of incident vertebral fractures. Front Endocrinol (Lausanne) 2023; 14:1222041. [PMID: 37576975 PMCID: PMC10422975 DOI: 10.3389/fendo.2023.1222041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023] Open
Abstract
Objectives Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening. Methods Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness. Results Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations. Conclusion oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice.
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Affiliation(s)
- Sebastian Rühling
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Julian Schwarting
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Matthias F. Froelich
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Mannheim, Germany
| | - Maximilian T. Löffler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Moritz R. Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maria Wostrack
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - A. Kaywan Aftahy
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Vanadin Seifert-Klauss
- Department of Gynecology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Fabian Tollens
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim-University of Heidelberg, Mannheim, Germany
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Bodden J, Dieckmeyer M, Sollmann N, Burian E, Rühling S, Löffler MT, Sekuboyina A, El Husseini M, Zimmer C, Kirschke JS, Baum T. Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans. Front Endocrinol (Lausanne) 2023; 14:1207949. [PMID: 37529605 PMCID: PMC10390306 DOI: 10.3389/fendo.2023.1207949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/14/2023] [Indexed: 08/03/2023] Open
Abstract
Objectives To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models. Methods This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC). Results 420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7). Conclusions VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data.
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Affiliation(s)
- Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Sebastian Rühling
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian T. Löffler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Anjany Sekuboyina
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Munich, Germany
- Munich School of BioEngineering, Technical University of Munich, Munich, Germany
| | - Malek El Husseini
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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23
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Sollmann N, Schandelmaier P, Weidlich D, Stelter J, Joseph GB, Börner C, Schramm S, Beer M, Zimmer C, Landgraf MN, Heinen F, Karampinos DC, Baum T, Bonfert MV. Headache frequency and neck pain are associated with trapezius muscle T2 in tension-type headache among young adults. J Headache Pain 2023; 24:84. [PMID: 37438700 DOI: 10.1186/s10194-023-01626-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 07/05/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Tension-type headache (TTH) is the most prevalent primary headache disorder. Neck pain is commonly associated with primary headaches and the trigemino-cervical complex (TCC) refers to the convergence of trigeminal and cervical afferents onto neurons of the brainstem, thus conceptualizes the emergence of headache in relation to neck pain. However, no objective biomarkers exist for the myofascial involvement in primary headaches. This study aimed to investigate the involvement of the trapezius muscles in primary headache disorders by quantitative magnetic resonance imaging (MRI), and to explore associations between muscle T2 values and headache frequency and neck pain. METHODS This cohort study prospectively enrolled fifty participants (41 females, age range 20-31 years): 16 subjects with TTH only (TTH-), 12 with mixed-type TTH plus migraine (TTH+), and 22 healthy controls (HC). The participants completed fat-suppressed T2-prepared three-dimensional turbo spin-echo MRI, a headache diary (over 30 days prior to MRI), manual palpation (two weeks before MRI), and evaluation of neck pain (on the day of MRI). The bilateral trapezius muscles were manually segmented, followed by muscle T2 extraction. Associations between muscle T2 and the presence of neck pain as well as the number of days with headache (considering the 30 days prior to imaging using the headache calendar) were analyzed using regression models (adjusting for age, sex, and body mass index). RESULTS The TTH+ group demonstrated the highest muscle T2 values (right side: 31.4 ± 1.2 ms, left side: 31.4 ± 0.8 ms) as compared to the TTH- group or HC group (p < 0.001). Muscle T2 was significantly associated with the number of headache days (β-coefficient: 2.04, p = 0.04) and the presence of neck pain (odds ratio: 2.26, p = 0.04). With muscle T2 as the predictor, the area under the curve for differentiating between HC and the TTH+ group was 0.82. CONCLUSIONS Increased T2 of trapezius muscles may represent an objective imaging biomarker for myofascial involvement in primary headache disorders, which could help to improve patient phenotyping and therapy evaluation. Pathophysiologically, the increased muscle T2 values could be interpreted as a surrogate of neurogenic inflammation and peripheral sensitization within myofascial tissues.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
| | - Paul Schandelmaier
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Dominik Weidlich
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jonathan Stelter
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Gabby B Joseph
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Corinna Börner
- Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Mirjam N Landgraf
- Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Florian Heinen
- Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Michaela V Bonfert
- Department of Pediatrics - Dr. von Hauner Children's Hospital, Division of Pediatric Neurology and Developmental Medicine, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
- LMU Center for Children with Medical Complexity - iSPZ Hauner, Ludwig-Maximilians-Universität München, Munich, Germany
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24
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Esopenko C, Sollmann N, Bonke EM, Wiegand TLT, Heinen F, de Souza NL, Breedlove KM, Shenton ME, Lin AP, Koerte IK. Current and Emerging Techniques in Neuroimaging of Sport-Related Concussion. J Clin Neurophysiol 2023; 40:398-407. [PMID: 36930218 PMCID: PMC10329721 DOI: 10.1097/wnp.0000000000000864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
SUMMARY Sport-related concussion (SRC) affects an estimated 1.6 to 3.8 million Americans each year. Sport-related concussion results from biomechanical forces to the head or neck that lead to a broad range of neurologic symptoms and impaired cognitive function. Although most individuals recover within weeks, some develop chronic symptoms. The heterogeneity of both the clinical presentation and the underlying brain injury profile make SRC a challenging condition. Adding to this challenge, there is also a lack of objective and reliable biomarkers to support diagnosis, to inform clinical decision making, and to monitor recovery after SRC. In this review, the authors provide an overview of advanced neuroimaging techniques that provide the sensitivity needed to capture subtle changes in brain structure, metabolism, function, and perfusion after SRC. This is followed by a discussion of emerging neuroimaging techniques, as well as current efforts of international research consortia committed to the study of SRC. Finally, the authors emphasize the need for advanced multimodal neuroimaging to develop objective biomarkers that will inform targeted treatment strategies after SRC.
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Affiliation(s)
- Carrie Esopenko
- Department of Rehabilitation and Movement Sciences, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - Nico Sollmann
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Elena M. Bonke
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität, Munich, Germany
| | - Tim L. T. Wiegand
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Felicitas Heinen
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Nicola L. de Souza
- School of Graduate Studies, Biomedical Sciences, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - Katherine M. Breedlove
- Center for Clinical Spectroscopy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Alexander P. Lin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Center for Clinical Spectroscopy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Inga K. Koerte
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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25
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Hangel G, Schmitz‐Abecassis B, Sollmann N, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda KM, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Hirschler L, Smits M, Petr J, Emblem KE. Advanced MR Techniques for Preoperative Glioma Characterization: Part 2. J Magn Reson Imaging 2023; 57:1676-1695. [PMID: 36912262 PMCID: PMC10947037 DOI: 10.1002/jmri.28663] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/14/2023] Open
Abstract
Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Medical Delta FoundationDelftthe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - N. Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Cancer Center AmsterdamAmsterdamNetherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyHaaglanden Medical CenterNetherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental HealthBabes‐Bolyai UniversityRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | | | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftthe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University HospitalBrnoCzechia
- Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Marion Smits
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamthe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
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26
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Hirschler L, Sollmann N, Schmitz‐Abecassis B, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda K, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Emblem KE, Smits M, Petr J, Hangel G. Advanced MR Techniques for Preoperative Glioma Characterization: Part 1. J Magn Reson Imaging 2023; 57:1655-1675. [PMID: 36866773 PMCID: PMC10946498 DOI: 10.1002/jmri.28662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/04/2023] Open
Abstract
Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.
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Affiliation(s)
- Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
- Medical Delta FoundationDelftThe Netherlands
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityKrems an der DonauAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - Nazmiye Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- Cancer Center AmsterdamAmsterdamThe Netherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenThe Netherlands
- Department of NeurologyHaaglanden Medical CenterThe HagueThe Netherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchLondonUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and PsychotherapyInternational Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes‐Bolyai UniversityCluj‐NapocaRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | - Kathleen Schmainda
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftThe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University Hospital, BrnoBrnoCzech Republic
- Faculty of Medicine, Masaryk UniversityBrnoCzech Republic
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
| | - Marion Smits
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
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27
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Burian E, Feuerriegel G, Sollmann N, Burian G, Palla B, Griesbauer M, Bumm C, Probst M, Beer M, Folwaczny M. Visualization of clinically silent, odontogenic maxillary sinus mucositis originating from periapical inflammation using MRI: a feasibility study. Clin Oral Investig 2023:10.1007/s00784-023-04986-4. [PMID: 37039958 DOI: 10.1007/s00784-023-04986-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/28/2023] [Indexed: 04/12/2023]
Abstract
OBJECTIVES Maxillary sinus mucositis is frequently associated with odontogenic foci. Periapical inflammation of maxillary molars and premolars cannot be visualized directly using radiation-based imaging. The purpose of this study was to answer the following clinical question: among patients with periapical inflammatory processes in the maxilla, does the use of magnetic resonance imaging (MRI), as compared to conventional periapical (AP) and panoramic radiography (OPT), improve diagnostic accuracy? METHODS Forty-two subjects with generalized periodontitis were scanned on a 3 T MRI. Sixteen asymptomatic subjects with mucosal swelling of the maxillary sinus were enrolled in the study. Periapical edema was assessed using short tau inversion recovery (STIR) sequence. Apical osteolysis and mucosal swelling were assessed by MRI, AP, and OPT imaging using the periapical index score (PAI). Comparisons between groups were performed with chi-squared tests with Yates' correction. Significance was set at p < 0.05. RESULTS Periapical lesions of maxillary premolars and molars were identified in 16 subjects, 21 sinuses, and 58 teeth. Bone edema and PAI scores were significantly higher using MRI as compared to OPT and AP (p < 0.05). Using the STIR sequence, a significant association of PAI score > 1 and the presence of mucosal swelling in the maxillary sinus was detected (p = 0.03). CONCLUSION Periapical inflammation and maxillary mucositis could be visualized using STIR imaging. The use of MRI may help detect early, subtle inflammatory changes in the periapical tissues surrounding maxillary dentition. Early detection could guide diagnostic criteria, as well as treatment and prevention.
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Affiliation(s)
- Egon Burian
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
| | - Georg Feuerriegel
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- TUM-Neuroimaging Center, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany
| | - Gintare Burian
- Department of Prosthodontics, LMU University Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Benjamin Palla
- Department of Oral and Maxillofacial Surgery, University of Illinois, Chicago, IL, USA
| | - Magdalena Griesbauer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Caspar Bumm
- Department of Restorative Dentistry and Periodontology, LMU University Hospital, Munich, Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Matthias Folwaczny
- Department of Restorative Dentistry and Periodontology, LMU University Hospital, Munich, Germany
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Umminger LF, Rojczyk P, Seitz-Holland J, Sollmann N, Kaufmann E, Kinzel P, Zhang F, Kochsiek J, Langhein M, Kim CL, Wiegand TLT, Kilts JD, Naylor JC, Grant GA, Rathi Y, Coleman MJ, Bouix S, Tripodis Y, Pasternak O, George MS, McAllister TW, Zafonte R, Stein MB, O'Donnell LJ, Marx CE, Shenton ME, Koerte IK. White Matter Microstructure Is Associated with Serum Neuroactive Steroids and Psychological Functioning. J Neurotrauma 2023; 40:649-664. [PMID: 36324218 PMCID: PMC10061338 DOI: 10.1089/neu.2022.0111] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Military service members are at increased risk for mental health issues, and comorbidity with mild traumatic brain injury (mTBI) is common. Largely overlapping symptoms between conditions suggest a shared pathophysiology. The present work investigates the associations among white matter microstructure, psychological functioning, and serum neuroactive steroids that are part of the stress-response system. Diffusion-weighted brain imaging was acquired from 163 participants (with and without military affiliation) and free-water-corrected fractional anisotropy (FAT) was extracted. Associations between serum neurosteroid levels of allopregnanolone (ALLO) and pregnenolone (PREGNE), psychological functioning, and whole-brain white matter microstructure were assessed using regression models. Moderation models tested the effect of mTBI and comorbid post-traumatic stress disorder (PTSD) and mTBI on these associations. ALLO is associated with whole-brain white matter FAT (β = 0.24, t = 3.05, p = 0.006). This association is significantly modulated by PTSD+mTBI comorbidity (β = 0.00, t = 2.50, p = 0.027), although an mTBI diagnosis alone did not significantly impact this association (p = 0.088). There was no significant association between PREGNE and FAT (p = 0.380). Importantly, lower FAT is associated with poor psychological functioning (β = -0.19, t = -2.35, p = 0.020). This study provides novel insight into a potential common pathophysiological mechanism of neurosteroid dysregulation underlying the high risk for mental health issues in military service members. Further, comorbidity of PTSD and mTBI may bring the compensatory effects of the brain's stress response to their limit. Future research is needed to investigate whether neurosteroid regulation may be a promising tool for restoring brain health and improving psychological functioning.
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Affiliation(s)
- Lisa F. Umminger
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Philine Rojczyk
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Nico Sollmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Elisabeth Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurology, Epilepsy Center, Ludwig-Maximilians-Universität, Munich, Germany
| | - Philipp Kinzel
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Fan Zhang
- Laboratory of Mathematics in Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Janna Kochsiek
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mina Langhein
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Cara L. Kim
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Tim L. T. Wiegand
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Jason D. Kilts
- VA Mid-Atlantic Mental Illness Research and Clinical Center (MIRECC) and Durham VA Medical Center, Durham, NorthCarolina, USA
- Department of Psychiatry and Behavior Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Jennifer C. Naylor
- VA Mid-Atlantic Mental Illness Research and Clinical Center (MIRECC) and Durham VA Medical Center, Durham, NorthCarolina, USA
- Department of Psychiatry and Behavior Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Gerald A. Grant
- Department of Neurosurgery, Duke University School of Medicine, Durham, North Carolina, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Michael J. Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Yorghos Tripodis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Boston University Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Mark S. George
- Psychiatry Department, Medical University of South Carolina, Charleston, South Carolina, USA
- Ralph H. Johnson VA Medical Center, Charleston, South Carolina, USA
| | - Thomas W. McAllister
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ross Zafonte
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Murray B. Stein
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- School of Public Health, University of California San Diego, La Jolla, California, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Lauren J. O'Donnell
- Laboratory of Mathematics in Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Christine E. Marx
- VA Mid-Atlantic Mental Illness Research and Clinical Center (MIRECC) and Durham VA Medical Center, Durham, NorthCarolina, USA
- Department of Psychiatry and Behavior Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Graduate School of Systemic Neuroscience, Ludwig-Maximilians-Universität, Munich, Germany
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Paprottka KJ, Kupfer K, Schultz V, Beer M, Zimmer C, Baum T, Kirschke JS, Sollmann N. Impact of radiation dose reduction and iterative image reconstruction on CT-guided spine biopsies. Sci Rep 2023; 13:5054. [PMID: 36977710 PMCID: PMC10050004 DOI: 10.1038/s41598-023-32102-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
This study aimed to systematically evaluate the impact of dose reduction on image quality and confidence for intervention planning and guidance regarding computed tomography (CT)-based intervertebral disc and vertebral body biopsies. We retrospectively analyzed 96 patients who underwent multi-detector CT (MDCT) acquired for the purpose of biopsies, which were either derived from scanning with standard dose (SD) or low dose (LD; using tube current reduction). The SD cases were matched to LD cases considering sex, age, level of biopsy, presence of spinal instrumentation, and body diameter. All images for planning (reconstruction: "IMR1") and periprocedural guidance (reconstruction: "iDose4") were evaluated by two readers (R1 and R2) using Likert scales. Image noise was measured using attenuation values of paraspinal muscle tissue. The dose length product (DLP) was statistically significantly lower for LD scans regarding the planning scans (SD: 13.8 ± 8.2 mGy*cm, LD: 8.1 ± 4.4 mGy*cm, p < 0.01) and the interventional guidance scans (SD: 43.0 ± 48.8 mGy*cm, LD: 18.4 ± 7.3 mGy*cm, p < 0.01). Image quality, contrast, determination of the target structure, and confidence for planning or intervention guidance were rated good to perfect for SD and LD scans, showing no statistically significant differences between SD and LD scans (p > 0.05). Image noise was similar between SD and LD scans performed for planning of the interventional procedures (SD: 14.62 ± 2.83 HU vs. LD: 15.45 ± 3.22 HU, p = 0.24). Use of a LD protocol for MDCT-guided biopsies along the spine is a practical alternative, maintaining overall image quality and confidence. Increasing availability of model-based iterative reconstruction in clinical routine may facilitate further radiation dose reductions.
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Affiliation(s)
- Karolin J Paprottka
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
| | - Karina Kupfer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Vivian Schultz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
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Schlaeger S, Drummer K, Husseini ME, Kofler F, Sollmann N, Schramm S, Zimmer C, Kirschke JS, Wiestler B. Implementation of GAN-Based, Synthetic T2-Weighted Fat Saturated Images in the Routine Radiological Workflow Improves Spinal Pathology Detection. Diagnostics (Basel) 2023; 13:diagnostics13050974. [PMID: 36900118 PMCID: PMC10000723 DOI: 10.3390/diagnostics13050974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/16/2023] [Accepted: 02/24/2023] [Indexed: 03/08/2023] Open
Abstract
(1) Background and Purpose: In magnetic resonance imaging (MRI) of the spine, T2-weighted (T2-w) fat-saturated (fs) images improve the diagnostic assessment of pathologies. However, in the daily clinical setting, additional T2-w fs images are frequently missing due to time constraints or motion artifacts. Generative adversarial networks (GANs) can generate synthetic T2-w fs images in a clinically feasible time. Therefore, by simulating the radiological workflow with a heterogenous dataset, this study's purpose was to evaluate the diagnostic value of additional synthetic, GAN-based T2-w fs images in the clinical routine. (2) Methods: 174 patients with MRI of the spine were retrospectively identified. A GAN was trained to synthesize T2-w fs images from T1-w, and non-fs T2-w images of 73 patients scanned in our institution. Subsequently, the GAN was used to create synthetic T2-w fs images for the previously unseen 101 patients from multiple institutions. In this test dataset, the additional diagnostic value of synthetic T2-w fs images was assessed in six pathologies by two neuroradiologists. Pathologies were first graded on T1-w and non-fs T2-w images only, then synthetic T2-w fs images were added, and pathologies were graded again. Evaluation of the additional diagnostic value of the synthetic protocol was performed by calculation of Cohen's ĸ and accuracy in comparison to a ground truth (GT) grading based on real T2-w fs images, pre- or follow-up scans, other imaging modalities, and clinical information. (3) Results: The addition of the synthetic T2-w fs to the imaging protocol led to a more precise grading of abnormalities than when grading was based on T1-w and non-fs T2-w images only (mean ĸ GT versus synthetic protocol = 0.65; mean ĸ GT versus T1/T2 = 0.56; p = 0.043). (4) Conclusions: The implementation of synthetic T2-w fs images in the radiological workflow significantly improves the overall assessment of spine pathologies. Thereby, high-quality, synthetic T2-w fs images can be virtually generated by a GAN from heterogeneous, multicenter T1-w and non-fs T2-w contrasts in a clinically feasible time, which underlines the reproducibility and generalizability of our approach.
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Affiliation(s)
- Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Correspondence:
| | - Katharina Drummer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Malek El Husseini
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Department of Informatics, Technical University of Munich, Boltzmannstr. 3, 85748 Garching, Germany
- TranslaTUM—Central Institute for Translational Cancer Research, Technical University of Munich, Einsteinstr. 25, 81675 Munich, Germany
- Helmholtz AI, Helmholtz Zentrum München, Ingostaedter Landstrasse 1, 85764 Oberschleissheim, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- TUM-NeuroImaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- TUM-NeuroImaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- TUM-NeuroImaging Center, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
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Zhylka A, Sollmann N, Kofler F, Radwan A, De Luca A, Gempt J, Wiestler B, Menze B, Schroeder A, Zimmer C, Kirschke JS, Sunaert S, Leemans A, Krieg SM, Pluim J. Reconstruction of the Corticospinal Tract in Patients with Motor-Eloquent High-Grade Gliomas Using Multilevel Fiber Tractography Combined with Functional Motor Cortex Mapping. AJNR Am J Neuroradiol 2023; 44:283-290. [PMID: 36797033 PMCID: PMC10187805 DOI: 10.3174/ajnr.a7793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 01/17/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND AND PURPOSE Tractography of the corticospinal tract is paramount to presurgical planning and guidance of intraoperative resection in patients with motor-eloquent gliomas. It is well-known that DTI-based tractography as the most frequently used technique has relevant shortcomings, particularly for resolving complex fiber architecture. The purpose of this study was to evaluate multilevel fiber tractography combined with functional motor cortex mapping in comparison with conventional deterministic tractography algorithms. MATERIALS AND METHODS Thirty-one patients (mean age, 61.5 [SD, 12.2] years) with motor-eloquent high-grade gliomas underwent MR imaging with DWI (TR/TE = 5000/78 ms, voxel size = 2 × 2 × 2 mm3, 1 volume at b = 0 s/mm2, 32 volumes at b = 1000 s/mm2). DTI, constrained spherical deconvolution, and multilevel fiber tractography-based reconstruction of the corticospinal tract within the tumor-affected hemispheres were performed. The functional motor cortex was enclosed by navigated transcranial magnetic stimulation motor mapping before tumor resection and used for seeding. A range of angular deviation and fractional anisotropy thresholds (for DTI) was tested. RESULTS For all investigated thresholds, multilevel fiber tractography achieved the highest mean coverage of the motor maps (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 71.8%, 22.6%, and 11.7%) and the most extensive corticospinal tract reconstructions (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 26,485 mm3, 6308 mm3, and 4270 mm3). CONCLUSIONS Multilevel fiber tractography may improve the coverage of the motor cortex by corticospinal tract fibers compared with conventional deterministic algorithms. Thus, it could provide a more detailed and complete visualization of corticospinal tract architecture, particularly by visualizing fiber trajectories with acute angles that might be of high relevance in patients with gliomas and distorted anatomy.
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Affiliation(s)
- A Zhylka
- From the Department of Biomedical Engineering (A.Z., J.P.), Eindhoven University of Technology, Eindhoven, The Netherlands
| | - N Sollmann
- Department of Diagnostic and Interventional Radiology (N.S.), University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology (N.S., F.K., B.W., C.Z., J.S.K.), School of Medicine, Klinikum rechts der Isar
- TUM-Neuroimaging Center (N.S., C.Z., J.S.K., S.M.K.), Klinikum rechts der Isar
- Department of Radiology and Biomedical Imaging (N.S.), University of California, San Francisco, San Francisco, California
| | - F Kofler
- Helmholtz AI (F.K.), Helmholtz Zentrum Munich, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology (N.S., F.K., B.W., C.Z., J.S.K.), School of Medicine, Klinikum rechts der Isar
- Image-Based Biomedical Modeling (F.K., B.M.)
- Department of Informatics, TranslaTUM (F.K., B.W.), Central Institute for Translational Cancer Research
| | - A Radwan
- Department of Imaging and Pathology (A.R., S.S.), Translational MRI
- Department of Neurosciences (A.R., S.S.), Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
| | - A De Luca
- Image Sciences Institute (A.D.L., A.L.)
- Neurology Department (A.D.L.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J Gempt
- Department of Neurosurgery (J.G., A.S., S.M.K.), School of Medicine, Klinikumrechts der Isar, Technical University of Munich, Munich, Germany
| | - B Wiestler
- Department of Diagnostic and Interventional Neuroradiology (N.S., F.K., B.W., C.Z., J.S.K.), School of Medicine, Klinikum rechts der Isar
- Department of Informatics, TranslaTUM (F.K., B.W.), Central Institute for Translational Cancer Research
| | - B Menze
- Image-Based Biomedical Modeling (F.K., B.M.)
- Department of Quantitative Biomedicine (B.M.), University of Zurich, Zurich, Switzerland
| | - A Schroeder
- Department of Neurosurgery (J.G., A.S., S.M.K.), School of Medicine, Klinikumrechts der Isar, Technical University of Munich, Munich, Germany
| | - C Zimmer
- Department of Diagnostic and Interventional Neuroradiology (N.S., F.K., B.W., C.Z., J.S.K.), School of Medicine, Klinikum rechts der Isar
- TUM-Neuroimaging Center (N.S., C.Z., J.S.K., S.M.K.), Klinikum rechts der Isar
| | - J S Kirschke
- Department of Diagnostic and Interventional Neuroradiology (N.S., F.K., B.W., C.Z., J.S.K.), School of Medicine, Klinikum rechts der Isar
- TUM-Neuroimaging Center (N.S., C.Z., J.S.K., S.M.K.), Klinikum rechts der Isar
| | - S Sunaert
- Department of Imaging and Pathology (A.R., S.S.), Translational MRI
- Department of Neurosciences (A.R., S.S.), Leuven Brain Institute, Katholieke Universiteit Leuven, Leuven, Belgium
| | - A Leemans
- Image Sciences Institute (A.D.L., A.L.)
| | - S M Krieg
- TUM-Neuroimaging Center (N.S., C.Z., J.S.K., S.M.K.), Klinikum rechts der Isar
- Department of Neurosurgery (J.G., A.S., S.M.K.), School of Medicine, Klinikumrechts der Isar, Technical University of Munich, Munich, Germany
| | - J Pluim
- From the Department of Biomedical Engineering (A.Z., J.P.), Eindhoven University of Technology, Eindhoven, The Netherlands
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Feuerriegel GC, Ritschl LM, Sollmann N, Palla B, Leonhardt Y, Maier L, Gassert FT, Karampinos DC, Makowski MR, Zimmer C, Wolff KD, Probst M, Fichter AM, Burian E. Imaging of traumatic mandibular fractures in young adults using CT-like MRI: a feasibility study. Clin Oral Investig 2023; 27:1227-1233. [PMID: 36208329 PMCID: PMC9985557 DOI: 10.1007/s00784-022-04736-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 10/01/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVES To assess and compare the diagnostic performance of CT-like images based on a three- dimensional (3D) T1-weighted spoiled gradient-echo sequence (3D T1 GRE) with CT in patients with acute traumatic fractures of the mandible. MATERIALS AND METHODS Subjects with acute mandibular fractures diagnosed on conventional CT were prospectively recruited and received an additional 3 T MRI with a CT-like 3D T1 GRE sequence. The images were assessed by two radiologists with regard to fracture localization, degree of dislocation, and number of fragments. Bone to soft tissue contrast, diagnostic confidence, artifacts, and overall image quality were rated using a five-point Likert-scale. Agreement of measurements was assessed using an independent t-test. RESULTS Fourteen subjects and 22 fracture sites were included (26 ± 3.9 years; 4 females, 10 males). All traumatic fractures were accurately detected on CT-like MRI (n = 22, κ 1.00 (95% CI 1.00-1.00)). There was no statistically significant difference in the assessment of the fracture dislocation (axial mean difference (MD) 0.06 mm, p = 0.93, coronal MD, 0.08 mm, p = 0.89 and sagittal MD, 0.04 mm, p = 0.96). The agreement for the fracture classification as well as the inter- and intra-rater agreement was excellent (range κ 0.92-0.98 (95% CI 0.96-0.99)). CONCLUSION Assessment of mandibular fractures was feasible and accurate using CT-like MRI based on a 3D T1 GRE sequence and is comparable to conventional CT. CLINICAL RELEVANCE For the assessment of acute mandibular fractures, CT-like MRI might become a useful alternative to CT in order to reduce radiation exposure particularly in young patients.
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Affiliation(s)
- Georg C Feuerriegel
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Lucas M Ritschl
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany.,Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Benjamin Palla
- Department of Oral and Maxillofacial Surgery, University of Illinois Chicago, Chicago, USA
| | - Yannik Leonhardt
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Lisa Maier
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Florian T Gassert
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Klaus-Dietrich Wolff
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Monika Probst
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andreas M Fichter
- Department of Oral and Maxillofacial Surgery, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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Strohm A, Braun M, Kloth C, Sollmann N, Ozpeynirci Y, Pala A, Beer M, Schmitz BL, Rosskopf J. Effectiveness and Safety of CT-Guided Facet Joint Cyst Rupture for Radicular Pain as First Choice Therapy: A Retrospective Analysis. Pain Med 2023; 24:158-164. [PMID: 35944225 DOI: 10.1093/pm/pnac116] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 07/25/2022] [Accepted: 07/28/2022] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To evaluate effectiveness and safety of computed tomography (CT)-guided cyst rupture with intraarticular contrast-enhanced injection of steroid and local anesthetic as first choice therapy in patients with facet joint cyst-induced radicular pain. DESIGN Retrospective data set analysis. SETTING University hospital. SUBJECTS One hundred and twenty-one patients suffering from radicular pain attributable to facet joint cysts were included. METHODS The rate of patients without following surgery was assessed and defined as surrogate to measure effectiveness. Patients' characteristics, procedure-associated complications, technical aspects, and imaging findings on magnetic resonance imaging (MRI) were analyzed. A subgroup of 65 patients (54%) underwent telephone interview to assess pain relief and clinical outcome measured by Numeric Rating Scale and Oswestry Disability Index. Analyses between the groups with and without surgery were performed by Fisher exact test and two-sample unpaired t-test, respectively. RESULTS The effectiveness of CT-guided cyst rupture was found to be 66.1%. Procedure-induced pain yielded in premature abort in two cases (1.7%). The detection of epidural contrast agent was statistically significantly associated with no need for surgery (P = .010). The cyst level was associated with the status of following surgery (P = .026), that is, cysts at lower lumbar spine were easier to rupture than cysts at other locations (cervical, thoracic, or upper lumbar spine). No further significant association was found. CONCLUSIONS CT-guided cyst rupture as the first-choice therapy in patients with cyst-induced radicular pain was safe and effective. Successful cyst rupture was associated with no need for surgery. Cysts at lower lumbar spine revealed the highest success rate.
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Affiliation(s)
- Alexa Strohm
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Section of Neuroradiology, University of Ulm, Bezirkskrankenhaus Guenzburg, Guenzburg, Germany
| | - Michael Braun
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Section of Neuroradiology, University of Ulm, Bezirkskrankenhaus Guenzburg, Guenzburg, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Yigit Ozpeynirci
- Institute of Neuroradiology, Ludwig-Maximilian-University, Munich, Germany
| | - Andrej Pala
- Department of Neurosurgery, University of Ulm, Bezirkskrankenhaus Guenzburg, Guenzburg, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Bernd L Schmitz
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Section of Neuroradiology, University of Ulm, Bezirkskrankenhaus Guenzburg, Guenzburg, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Section of Neuroradiology, University of Ulm, Bezirkskrankenhaus Guenzburg, Guenzburg, Germany
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Schramm S, Börner C, Reichert M, Baum T, Zimmer C, Heinen F, Bonfert MV, Sollmann N. Functional magnetic resonance imaging in migraine: A systematic review. Cephalalgia 2023; 43:3331024221128278. [PMID: 36751858 DOI: 10.1177/03331024221128278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
BACKGROUND Migraine is a highly prevalent primary headache disorder. Despite a high burden of disease, key disease mechanisms are not entirely understood. Functional magnetic resonance imaging is an imaging method using the blood-oxygen-level-dependent signal, which has been increasingly used in migraine research over recent years. This systematic review summarizes recent findings employing functional magnetic resonance imaging for the investigation of migraine. METHODS We conducted a systematic search and selection of functional magnetic resonance imaging applications in migraine from April 2014 to December 2021 (PubMed and references of identified articles according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines). Methodological details and main findings were extracted and synthesized. RESULTS Out of 224 articles identified, 114 were included after selection. Repeatedly emerging structures of interest included the insula, brainstem, limbic system, hypothalamus, thalamus, and functional networks. Assessment of functional brain changes in response to treatment is emerging, and machine learning has been used to investigate potential functional magnetic resonance imaging-based markers of migraine. CONCLUSIONS A wide variety of functional magnetic resonance imaging-based metrics were found altered across the brain for heterogeneous migraine cohorts, partially correlating with clinical parameters and supporting the concept to conceive migraine as a brain state. However, a majority of findings from previous studies have not been replicated, and studies varied considerably regarding image acquisition and analyses techniques. Thus, while functional magnetic resonance imaging appears to have the potential to advance our understanding of migraine pathophysiology, replication of findings in large representative datasets and precise, standardized reporting of clinical data would likely benefit the field and further increase the value of observations.
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Affiliation(s)
- Severin Schramm
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Corinna Börner
- LMU Hospital, Dr. von Hauner Children's Hospital, Department of Pediatric Neurology and Developmental Medicine, Munich, Germany.,LMU Center for Children with Medical Complexity, iSPZ Hauner, Ludwig Maximilian University, Munich, Germany
| | - Miriam Reichert
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Heinen
- LMU Hospital, Dr. von Hauner Children's Hospital, Department of Pediatric Neurology and Developmental Medicine, Munich, Germany
| | - Michaela V Bonfert
- LMU Hospital, Dr. von Hauner Children's Hospital, Department of Pediatric Neurology and Developmental Medicine, Munich, Germany.,LMU Center for Children with Medical Complexity, iSPZ Hauner, Ludwig Maximilian University, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
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Akkaya Z, Uzun C, Unal S, Gozukara C, Coruh AG, Kul M, Sahin G, Sollmann N. Multifocal concomitant scapulothoracic and subgluteal-ischiofemoral elastofibromas. Eur J Radiol 2023; 159:110683. [PMID: 36586194 DOI: 10.1016/j.ejrad.2022.110683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 12/20/2022] [Accepted: 12/24/2022] [Indexed: 12/27/2022]
Abstract
PURPOSE To evaluate the frequency, imaging findings, and patient demographics of synchronous elastofibroma dorsi (ED) and pelvic elastofibromas. METHODS Image archives between 2011 and 2021 were retrospectively searched for CT and MRI reports including the keyword "elastofibroma". Patients with concomitant CT and/or MRI of the chest and pelvic regions were included. The greatest thickness and side of ED were noted. Subsequently, pelvic soft tissues were evaluated for a soft tissue mass with similar radiological features to ED. When detected, its location, greatest transverse diameter, and ischiofemoral space widths were noted. Wilcoxon matched-pairs signed-rank and Mann-Whitney U-tests were performed when appropriate. Pearson's correlations were used to assess the association of presence of subgluteal-ischiofemoral elastofibromas (SGIFE) and ED thickness. The model discrimination of ED thickness was evaluated by calculating the AUC of the ROC. RESULTS Eighty-eight patients (Male:Female = 8:80) with a mean age of 70.6 (±10.3) years were included. 96.6 % of patients had bilateral ED. 18.2 % of patients (all females) had at least one concomitant SGIFE. Patients with SGIFE had significantly thicker ED (p < 0.001 right; p = 0.049 left). There was a significant positive correlation between the thickness of ED and presence of SGIFE (r = 0.43, p < 0.001 right; r = 0.25, p = 0.019 left). An AUC of 0.781 (p < 0.001, 95 %-CI:0.675-0.887) and 0.659 (p = 0.049, 95 %-CI:0.523-0.794) were revealed regarding the presence of ipsilateral right and left SGIFE, respectively. CONCLUSION Concomitant SGIFE may accompany ED in up to 18.2% of cases, particularly in women with thick ED. Knowledge of this co-occurrence and the described SGIFE characteristics can facilitate correct diagnosis.
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Affiliation(s)
- Zehra Akkaya
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey; Department of Radiology and Biomedical Imaging University of California San Francisco China Basin, Berry Street 185, Lobby 6, Suite 350, San Francisco, CA, USA.
| | - Caglar Uzun
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Sena Unal
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Cagdas Gozukara
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Aysegul Gursoy Coruh
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Melahat Kul
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Gulden Sahin
- Ankara University Faculty of Medicine Ibni Sina Hospital, Department of Radiology, 4th Floor Sıhhiye, Ankara, Turkey.
| | - Nico Sollmann
- Department of Radiology and Biomedical Imaging University of California San Francisco China Basin, Berry Street 185, Lobby 6, Suite 350, San Francisco, CA, USA; Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
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Riederer I, Mühlau M, Wiestler B, Bender B, Hempel JM, Kowarik M, Huber T, Zimmer C, Andrisan T, Patzig M, Zimmermann H, Havla J, Berlis A, Behrens L, Beer M, Dietrich J, Sollmann N, Kirschke JS. Structured Reporting in Multiple Sclerosis - Consensus-Based Reporting Templates for Magnetic Resonance Imaging of the Brain and Spinal Cord. ROFO-FORTSCHR RONTG 2023; 195:135-138. [PMID: 35913055 DOI: 10.1055/a-1867-3942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
As a result of technical developments and greater availability of imaging equipment, the number of neuroradiological examinations is steadily increasing [1]. Due to improved image quality and sensitivity, more details can be detected making reporting more complex and time-intensive. At the same time, reliable algorithms increasingly allow quantitative image analysis that should be integrated in reports in a standardized manner. Moreover, increasing digitalization is resulting in a decrease in the personal exchange between neuroradiologists and referring disciplines, thereby making communication more difficult. The introduction of structured reporting tailored to the specific disease and medical issue [2, 3] and corresponding to at least the second reporting level as defined by the German Radiological Society (https://www.befundung.drg.de/de-DE/2908/strukturierte-befundung/) is therefore desirable to ensure that the quality standards of neuroradiological reports continue to be met.The advantages of structured reporting include a reduced workload for neuroradiologists and an information gain for referring physicians. A complete and standardized list with relevant details for image reporting is provided to neuroradiologists in accordance with the current state of knowledge, thereby ensuring that important points are not forgotten [4]. A time savings and increase in efficiency during reporting were also seen [5]. Further advantages include report clarity and consistency and better comparability in follow-up examinations regardless of the neuroradiologist's particular reporting style. This results in better communication with the referring disciplines and makes clinical decision significantly easier [6, 7]. Although the advantages are significant, any potential disadvantages like the reduction of autonomy in reporting and inadequate coverage of all relevant details and any incidental findings not associated with the main pathology in complex cases or in rare diseases should be taken into consideration [4]. Therefore, studies examining the advantages of structured reporting, promoting the introduction of this system in the clinical routine, and increasing the acceptance among neuroradiologists are still needed.Numerous specific templates for structured reporting, e. g., regarding diseases in cardiology and oncology, are already available on the website www.befundung.drg.de . Multiple sclerosis (MS) is an idiopathic chronic inflammatory and neurodegenerative disease of the central nervous system and is the most common non-trauma-based inflammatory neurological disease in young adults. Therefore, it has significant individual and socioeconomic relevance [8]. Magnetic resonance imaging (MRI) plays an important role in the diagnosis, prognosis evaluation, and follow-up of this disease. MRI is established as the central diagnostic method in the diagnostic criteria. Therefore, specific changes are seen on MRI in almost all patients with a verified MS diagnosis [9]. Reporting of MRI datasets regarding the brain and spinal cord of patients with MS includes examination of the images with respect to the relevant medical issue in order to determine whether the McDonald criteria, which were revised in 2017 [10] and define dissemination in time and space clinically as well as with respect to MRI based on the recommendations of the MAGNIMS groups [11, 12], are fulfilled. A more precise definition of lesion types and locations according to the recommendations of an international expert group [13] is discussed in the supplementary material. Spinal cord signal abnormalities are seen in up to 92 % of MS patients [14-16] and are primarily located in the cervical spine [15]. The recommendations of the MAGNIMS-CMSC-NAIMS working group published in 2021 [11] explicitly recommend the use of structured reporting for MS patients.Therefore, a reporting template for evaluating MRI examinations of the brain and spinal cord of patients with MS was created as part of the BMBF-funded DIFUTURE consortium in consensus with neuroradiological and neurological experts in concordance with the recommendations mentioned above [11] and was made available for broad use (https://github.com/DRGagit/ak_befundung). The goal is to facilitate efficient and comprehensive evaluation of patients with MS in the primary diagnostic workup and follow-up imaging. These reporting templates are consensus-based recommendations and do not make any claim to general validity or completeness. The information technology working group (@GIT) of the German Radiological Society and the German Society for Neuroradiology strive to keep the reporting templates presented here up-to-date with respect to new research data and recommendations of the MAGNIMS-CMSC-NAIMS group [11]. KEY POINTS:: · consensus-based reporting templates. · template for the structured reporting of MRI examinations of patients with multiple sclerosis. · structured reporting might facilitate communication between neuroradiologists and referring disciplines. CITATION FORMAT: · Riederer I, Mühlau M, Wiestler B et al. Structured Reporting in Multiple Sclerosis - Consensus-Based Reporting Templates for Magnetic Resonance Imaging of the Brain and Spinal Cord. Fortschr Röntgenstr 2023; 195: 135 - 138.
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Affiliation(s)
- Isabelle Riederer
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland
| | - Mark Mühlau
- Klinikum rechts der Isar, Technische Universität München, Neurologische Klinik und Poliklinik, München, Deutschland
| | - Benedikt Wiestler
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland
| | - Benjamin Bender
- Radiologische Universitätsklinik Tübingen, Abteilung Diagnostische und Interventionelle Neuroradiologie, Tübingen, Deutschland
| | - Johann-Martin Hempel
- Radiologische Universitätsklinik Tübingen, Abteilung Diagnostische und Interventionelle Neuroradiologie, Tübingen, Deutschland
| | - Markus Kowarik
- Radiologische Universitätsklinik Tübingen, Abteilung Diagnostische und Interventionelle Neuroradiologie, Tübingen, Deutschland
| | - Thomas Huber
- Universitätsmedizin Mannheim, Klinik für Radiologie und Nuklearmedizin, Mannheim, Deutschland
| | - Claus Zimmer
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland
| | - Tiberiu Andrisan
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland
| | - Maximilian Patzig
- Klinikum der Universität München, LMU, Institut für diagnostische und interventionelle Neuroradiologie, München, Deutschland
| | - Hanna Zimmermann
- Klinikum der Universität München, LMU, Institut für diagnostische und interventionelle Neuroradiologie, München, Deutschland
| | - Joachim Havla
- LMU Klinikum, Institut für Klinische Neuroimmunologie, Ludwig-Maximilians-Universität, München, Deutschland
| | - Ansgar Berlis
- Universitätsklinikum Augsburg, Klinik für Diagnostische und Interventionelle Neuroradiologie, Augsburg, Deutschland
| | - Lars Behrens
- Universitätsklinikum Augsburg, Klinik für Diagnostische und Interventionelle Neuroradiologie, Augsburg, Deutschland
| | - Meinrad Beer
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Ulm, Ulm, Deutschland
| | - Jennifer Dietrich
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Ulm, Ulm, Deutschland
| | - Nico Sollmann
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland.,Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Ulm, Ulm, Deutschland
| | - Jan Stefan Kirschke
- Klinikum rechts der Isar, Technische Universität München, Abteilung für Diagnostische und Interventionelle Neuroradiologie, München, Deutschland
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Batorsky A, Bowden AE, Darwin J, Fields AJ, Greco CM, Harris RE, Hue TF, Kakyomya J, Mehling W, O'Neill C, Patterson CG, Piva SR, Sollmann N, Toups V, Wasan AD, Wasserman R, Williams DA, Vo NV, Psioda MA, McCumber M. The BACPAC Research Program Data Harmonization: Rationale for Data Elements and Standards. Pain Med 2023:7017526. [PMID: 36721327 DOI: 10.1093/pm/pnad008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/19/2023] [Accepted: 01/19/2023] [Indexed: 02/02/2023]
Abstract
OBJECTIVE One aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses. METHODS Consortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and non-tabular data (e.g., imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium. RESULTS Clinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected using questionnaires across projects. Other non-required domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed based on the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC. CONCLUSIONS BACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.
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Affiliation(s)
- Anna Batorsky
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anton E Bowden
- Department of Mechanical Engineering, Brigham Young University, Provo, UT, USA
| | - Jessa Darwin
- Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Aaron J Fields
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Carol M Greco
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Physical Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Richard E Harris
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Trisha F Hue
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Joseph Kakyomya
- School of Health and Rehabilitation Sciences Data Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wolf Mehling
- Department of Family and Community Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Conor O'Neill
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Charity G Patterson
- Department of Physical Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.,School of Health and Rehabilitation Sciences Data Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sara R Piva
- Department of Physical Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nico Sollmann
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.,Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Vincent Toups
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ajay D Wasan
- Department of Anesthesiology and Perioperative Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ronald Wasserman
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.,Back and Pain Center, University of Michigan, Ann Arbor, MI, USA
| | - David A Williams
- Chronic Pain and Fatigue Research Center, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA.,Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, USA.,Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Nam V Vo
- Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Ferguson Laboratory for Orthopaedic and Spine Research, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matthew A Psioda
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Micah McCumber
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Haggenmüller B, Kreiser K, Sollmann N, Huber M, Vogele D, Schmidt SA, Beer M, Schmitz B, Ozpeynirci Y, Rosskopf J, Kloth C. Pictorial Review on Imaging Findings in Cerebral CTP in Patients with Acute Stroke and Its Mimics: A Primer for General Radiologists. Diagnostics (Basel) 2023; 13:diagnostics13030447. [PMID: 36766552 PMCID: PMC9914845 DOI: 10.3390/diagnostics13030447] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/19/2023] [Accepted: 01/21/2023] [Indexed: 01/28/2023] Open
Abstract
The imaging evaluation of computed tomography (CT), CT angiography (CTA), and CT perfusion (CTP) is of crucial importance in the setting of each emergency department for suspected cerebrovascular impairment. A fast and clear assignment of characteristic imaging findings of acute stroke and its differential diagnoses is essential for every radiologist. Different entities can mimic clinical signs of an acute stroke, thus the knowledge and fast identification of stroke mimics is important. A fast and clear assignment is necessary for a correct diagnosis and a rapid initiation of appropriate therapy. This pictorial review describes the most common imaging findings in CTP with clinical signs for acute stroke or other acute neurological disorders. The knowledge of these pictograms is therefore essential and should also be addressed in training and further education of radiologists.
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Affiliation(s)
- Benedikt Haggenmüller
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
- Correspondence:
| | - Kornelia Kreiser
- Department of Radiology and Neuroradiology, RKU—Universitäts- und Rehabilitationskliniken Ulm, Oberer Eselsberg 45, 89081 Ulm, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Magdalena Huber
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Daniel Vogele
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Stefan A. Schmidt
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Bernd Schmitz
- Department of Neuroradiology, Bezirkskrankenhaus Günzburg, Lindenallee 2, 89312 Günzburg, Germany
| | - Yigit Ozpeynirci
- Institute of Neuroradiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
| | - Johannes Rosskopf
- Department of Neuroradiology, Bezirkskrankenhaus Günzburg, Lindenallee 2, 89312 Günzburg, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, Ulm University Medical Center, Albert-Einstein-Allee 23, 89081 Ulm, Germany
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Vogele D, Otto S, Sollmann N, Haggenmüller B, Wolf D, Beer M, Schmidt SA. Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. ROFO-FORTSCHR RONTG 2023; 195:393-405. [PMID: 36630983 DOI: 10.1055/a-1990-0201] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND Sarcopenia is an age-related syndrome characterized by a loss of muscle mass and strength. As a result, the independence of the elderly is reduced and the hospitalization rate and mortality increase. The onset of sarcopenia often begins in middle age due to an unbalanced diet or malnutrition in association with a lack of physical activity. This effect is intensified by concomitant diseases such as obesity or metabolic diseases including diabetes mellitus. METHOD With effective preventative diagnostic procedures and specific therapeutic treatment of sarcopenia, the negative effects on the individual can be reduced and the negative impact on health as well as socioeconomic effects can be prevented. Various diagnostic options are available for this purpose. In addition to basic clinical methods such as measuring muscle strength, sarcopenia can also be detected using imaging techniques like dual X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and sonography. DXA, as a simple and cost-effective method, offers a low-dose option for assessing body composition. With cross-sectional imaging techniques such as CT and MRI, further diagnostic possibilities are available, including MR spectroscopy (MRS) for noninvasive molecular analysis of muscle tissue. CT can also be used in the context of examinations performed for other indications to acquire additional parameters of the skeletal muscles (opportunistic secondary use of CT data), such as abdominal muscle mass (total abdominal muscle area - TAMA) or the psoas as well as the pectoralis muscle index. The importance of sarcopenia is already well studied for patients with various tumor entities and also infections such as SARS-COV2. RESULTS AND CONCLUSION Sarcopenia will become increasingly important, not least due to demographic changes in the population. In this review, the possibilities for the diagnosis of sarcopenia, the clinical significance, and therapeutic options are described. In particular, CT examinations, which are repeatedly performed on tumor patients, can be used for diagnostics. This opportunistic use can be supported by the use of artificial intelligence. KEY POINTS · Sarcopenia is an age-related syndrome with loss of muscle mass and strength.. · Early detection and therapy can prevent negative effects of sarcopenia.. · In addition to DEXA, cross-sectional imaging techniques (CT, MRI) are available for diagnostic purposes.. · The use of artificial intelligence (AI) offers further possibilities in sarcopenia diagnostics.. CITATION FORMAT · Vogele D, Otto S, Sollmann N et al. Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. Fortschr Röntgenstr 2023; DOI: 10.1055/a-1990-0201.
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Affiliation(s)
- Daniel Vogele
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
| | - Stephanie Otto
- Comprehensive Cancer Center (CCCU), University Hospital Ulm, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
| | - Benedikt Haggenmüller
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
| | - Daniel Wolf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Germany
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Diehl CD, Rosenkranz E, Schwendner M, Mißlbeck M, Sollmann N, Ille S, Meyer B, Combs SE, Krieg SM. Dose Reduction to Motor Structures in Adjuvant Fractionated Stereotactic Radiotherapy of Brain Metastases: nTMS-Derived DTI-Based Motor Fiber Tracking in Treatment Planning. Cancers (Basel) 2022; 15:cancers15010282. [PMID: 36612277 PMCID: PMC9818359 DOI: 10.3390/cancers15010282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/07/2022] [Accepted: 12/19/2022] [Indexed: 01/03/2023] Open
Abstract
Background: Resection of brain metastases (BM) close to motor structures is challenging for treatment. Navigated transcranial magnetic stimulation (nTMS) motor mapping, combined with diffusion tensor imaging (DTI)-based fiber tracking (DTI-FTmot.TMS), is a valuable tool in neurosurgery to preserve motor function. This study aimed to assess the practicability of DTI-FTmot.TMS for local adjuvant radiotherapy (RT) planning of BM. Methods: Presurgically generated DTI-FTmot.TMS-based corticospinal tract (CST) reconstructions (FTmot.TMS) of 24 patients with 25 BM resected during later surgery were incorporated into the RT planning system. Completed fractionated stereotactic intensity-modulated RT (IMRT) plans were retrospectively analyzed and adapted to preserve FTmot.TMS. Results: In regular plans, mean dose (Dmean) of complete FTmot.TMS was 5.2 ± 2.4 Gy. Regarding planning risk volume (PRV-FTTMS) portions outside of the planning target volume (PTV) within the 17.5 Gy (50%) isodose line, the DTI-FTmot.TMS Dmean was significantly reduced by 33.0% (range, 5.9−57.6%) from 23.4 ± 3.3 Gy to 15.9 ± 4.7 Gy (p < 0.001). There was no significant decline in the effective treatment dose, with PTV Dmean 35.6 ± 0.9 Gy vs. 36.0 ± 1.2 Gy (p = 0.063) after adaption. Conclusions: The DTI-FTmot.TMS-based CST reconstructions could be implemented in adjuvant IMRT planning of BM. A significant dose reduction regarding motor structures within critical dose levels seems possible.
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Affiliation(s)
- Christian D. Diehl
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), DKTK Partner Site, 81675 Munich, Germany
- Correspondence:
| | - Enrike Rosenkranz
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
| | - Maximilian Schwendner
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
| | - Martin Mißlbeck
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany
| | - Sebastian Ille
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
| | - Stephanie E. Combs
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), DKTK Partner Site, 81675 Munich, Germany
| | - Sandro M. Krieg
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich (TUM), 81675 Munich, Germany
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Diehl C, Rosenkranz E, Mißlbeck M, Schwendner M, Sollmann N, Eitz K, Bernhardt D, Ille S, Meyer B, Combs S, Krieg S. RADT-06. SPARING OF MOTOR STRUCTURES IN ADJUVANT RADIATION THERAPY AFTER RESECTION OF BRAIN METASTASES: APPLICATION OF NTMS-DERIVED DTI-BASED MOTOR FIBER TRACKING IN ADJUVANT STEREOTACTIC RT TREATMENT PLANNING. Neuro Oncol 2022. [DOI: 10.1093/neuonc/noac209.196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
BACKGROUND
Resection of brain metastases (BM) close to the motor cortex and the corticospinal tract (CST) bears a significant risk for treatment-related morbidity. Navigated transcranial mapping (nTMS) combined with diffusion-tensor-imaging (DTI) based fiber tracking (DTI-FTTMS) is a valuable tool to guide the neurosurgeon along the CST to preserve motor function. This study aims to proof the practicability of DTI-FTTMS in local adjuvant stereotactic RT planning in the management of BM. Method: Pre-surgical generated DTI-FTTMS-based CST reconstructions of 24 patients with 25 resected BM were incorporated into the RT planning system and elastic fused with planning imaging. The CST was delineated as the planning risk volume (PRV-FTTMS). Fractionated stereotactic intensity-modulated RT (IMRT) plans (7 x 5 Gy) were retrospectively calculated and then optimized to preserve PRV-FTTMS. Areas covered by the planning target volume (PTV) were not spared (overlap).
RESULTS
In regular plans mean dose (Dmean) of complete PRV-FTTMS was 5.4 ± 2.5 Gy. Regarding PRV-FTTMS portions within the 8.75 Gy (25% of prescription dose) isodose level Dmean was 18.2 ± 4.3 Gy and after plan optimization 13.1 ± 3.8Gy (-28.0%, p < 0.001). Within the 17.5 Gy (50%) isodose line PRV-FTTMS Dmean was reduced by 31.7% from 24.3 ± 3 Gy to 16.6 ± 4.8 Gy (p< 0.001). There was no decline of the effective treatment dose, PTV Dmean in regular plans was 36.9 ± 0.7 Gy vs. 37.7 ± 1.4Gy (p=0.013) after adaption. PTV coverage (V35Gy(%)*100) did not change with plan optimization: 0.99 vs. 0.99 (p=0.43). Dose constraints of organs at risk were all met both in regular and optimized plans.
CONCLUSION
DTI-FTTMS based motor tracts could be implemented in the adjuvant stereotactic RT planning of cavities after resection of BM. A significant dose reduction of motor structures within critical dose levels seems possible without reducing PTV treatment dose. However, the functional benefit needs to be investigated prospectively within clinical trials.
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Affiliation(s)
- Christian Diehl
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | | | - Martin Mißlbeck
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Maximilian Schwendner
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Kerstin Eitz
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Sebastian Ille
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Bernhard Meyer
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
| | - Stephanie Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM) , Munich , Germany
| | - Sandro Krieg
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich (TUM) , 81675 Munich , Germany
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Sollmann N, Bonnheim NB, Joseph GB, Chachad R, Zhou J, Akkaya Z, Pirmoazen AM, Bailey JF, Guo X, Lazar AA, Link TM, Fields AJ, Krug R. Paraspinal Muscle in Chronic Low Back Pain: Comparison Between Standard Parameters and Chemical Shift Encoding-Based Water-Fat MRI. J Magn Reson Imaging 2022; 56:1600-1608. [PMID: 35285561 PMCID: PMC9470775 DOI: 10.1002/jmri.28145] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/23/2022] [Accepted: 02/25/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding-based water-fat MRI (CSE-MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP. PURPOSE To investigate associations between PSM parameters from conventional MRI and CSE-MRI and between PSM parameters and pain. STUDY TYPE Prospective, cross-sectional. POPULATION Eighty-four adults with chronic LBP (44.6 ± 13.4 years; 48 males). FIELD STRENGTH/SEQUENCE 3-T, T1-weighted fast spin-echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences. ASSESSMENT T1-weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle-fat index, CSE-MRI for FF extraction (L1/2-L5/S1). Pain was self-reported using a visual analogue scale (VAS). Intra- and/or interreader agreement was assessed for MRI-derived parameters. STATISTICAL TESTS Mixed-effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra- and/or interreader agreement. RESULTS The FF showed excellent intra- and interreader agreement (ICC range: 0.97-0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P-value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores. DATA CONCLUSION In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE-MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Nico Sollmann
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Noah B. Bonnheim
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, USA
| | - Gabby B. Joseph
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Ravi Chachad
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Jiamin Zhou
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Zehra Akkaya
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Amir M. Pirmoazen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Jeannie F. Bailey
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, USA
| | - Xiaojie Guo
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, USA
| | - Ann A. Lazar
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Thomas M. Link
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Aaron J. Fields
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, USA
| | - Roland Krug
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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Sollmann N, Fields AJ, O'Neill C, Nardo L, Majumdar S, Chin CT, Tosun D, Han M, Vu AT, Ozhinsky E, Shah LM, Harris RE, Lobo R, Anderst W, Herzog R, Psioda MA, Standaert CJ, Price RT, Lotz JC, Link TM, Krug R. Magnetic resonance imaging of the lumbar spine-recommendations for acquisition and image evaluation from the BACPAC Spine Imaging Working Group. Pain Med 2022:6687139. [PMID: 36069660 PMCID: PMC10403314 DOI: 10.1093/pm/pnac130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Management of patients suffering from low back pain (LBP) is challenging and requires development of diagnostic techniques to identify specific patient subgroups and phenotypes in order to customize treatment and predict clinical outcome. The Back Pain Consortium (BACPAC) Spine Imaging Working Group has developed standard operating procedures (SOPs) for spinal imaging protocols to be used in all BACPAC studies. These SOPs include procedures to conduct spinal imaging assessments with guidelines for standardizing the collection, reading/grading (using structured reporting with semi-quantitative evaluation using ordinal rating scales), and storage of images. This article presents the approach to image acquisition and evaluation recommended by the BACPAC Spine Imaging Working Group. While the approach is specific to BACPAC studies, it is general enough to be applied at other centers performing MRI acquisitions in patients with LBP. The herein presented SOPs are meant to improve understanding of pain mechanisms and facilitate patient phenotyping by codifying MRI-based methods that provide standardized, non-invasive assessments of spinal pathologies. Finally, these recommended procedures may facilitate the integration of better harmonized MRI data of the lumbar spine across studies and sites within and outside of BACPAC studies.
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Affiliation(s)
- Nico Sollmann
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.,Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.,Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.,TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Aaron J Fields
- Department of Orthopaedic Surgery, University of California, San Francisco, CA, USA
| | - Conor O'Neill
- Department of Orthopaedic Surgery, University of California, San Francisco, CA, USA
| | - Lorenzo Nardo
- Department of Radiology, University of California, Davis, Sacramento, CA, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.,Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA
| | - Cynthia T Chin
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Misung Han
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - An T Vu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.,VA Advanced Imaging Research Center, San Francisco VA Health Care System, San Francisco, CA, USA
| | - Eugene Ozhinsky
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.,VA Advanced Imaging Research Center, San Francisco VA Health Care System, San Francisco, CA, USA
| | - Lubdha M Shah
- Department of Radiology, University of Utah, Salt Lake City, UT, USA
| | - Richard E Harris
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Remy Lobo
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - William Anderst
- Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Richard Herzog
- Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA
| | - Matthew A Psioda
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher J Standaert
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - River T Price
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeffrey C Lotz
- Department of Orthopaedic Surgery, University of California, San Francisco, CA, USA
| | - Thomas M Link
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Roland Krug
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
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Boerner C, Lang M, Urban G, Staisch J, Hauser A, Frohnmueller M, Hannibal I, Huss K, Kruse S, Klose B, Lechner M, Sollmann N, Landgraf M, Heinen F, Bonfert M. TU-195. Effects of repetitive neuromuscular magnetic stimulation targeting the upper trapezius muscles in children and adolescents with episodic migraine. Clin Neurophysiol 2022. [DOI: 10.1016/j.clinph.2022.07.099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Kaufmann E, Rojczyk P, Sydnor VJ, Guenette JP, Tripodis Y, Kaufmann D, Umminger L, Seitz-Holland J, Sollmann N, Rathi Y, Bouix S, Fortier CB, Salat D, Pasternak O, Hinds SR, Milberg WP, McGlinchey RE, Shenton ME, Koerte IK. Association of War Zone-Related Stress With Alterations in Limbic Gray Matter Microstructure. JAMA Netw Open 2022; 5:e2231891. [PMID: 36112375 PMCID: PMC9482063 DOI: 10.1001/jamanetworkopen.2022.31891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
IMPORTANCE Military service members returning from theaters of war are at increased risk for mental illness, but despite high prevalence and substantial individual and societal burden, the underlying pathomechanisms remain largely unknown. Exposure to high levels of emotional stress in theaters of war and mild traumatic brain injury (mTBI) are presumed factors associated with risk for the development of mental disorders. OBJECTIVE To investigate (1) whether war zone-related stress is associated with microstructural alterations in limbic gray matter (GM) independent of mental disorders common in this population, (2) whether associations between war zone-related stress and limbic GM microstructure are modulated by a history of mTBI, and (3) whether alterations in limbic GM microstructure are associated with neuropsychological functioning. DESIGN, SETTING, AND PARTICIPANTS This cohort study was part of the TRACTS (Translational Research Center for TBI and Stress Disorders) study, which took place in 2010 to 2014 at the Veterans Affair Rehabilitation Research and Development TBI National Network Research Center. Participants included male veterans (aged 18-65 years) with available diffusion tensor imaging data enrolled in the TRACTS study. Data analysis was performed between December 2017 to September 2021. EXPOSURES The Deployment Risk and Resilience Inventory (DRRI) was used to measure exposure to war zone-related stress. The Boston Assessment of TBI-Lifetime was used to assess history of mTBI. Stroop Inhibition (Stroop-IN) and Inhibition/Switching (Stroop-IS) Total Error Scaled Scores were used to assess executive or attentional control functions. MAIN OUTCOMES AND MEASURES Diffusion characteristics (fractional anisotropy of tissue [FAT]) of 16 limbic and paralimbic GM regions and measures of functional outcome. RESULTS Among 384 male veterans recruited, 168 (mean [SD] age, 31.4 [7.4] years) were analyzed. Greater war zone-related stress was associated with lower FAT in the cingulate (DRRI-combat left: P = .002, partial r = -0.289; DRRI-combat right: P = .02, partial r = -0.216; DRRI-aftermath left: P = .004, partial r = -0.281; DRRI-aftermath right: P = .02, partial r = -0.219), orbitofrontal (DRRI-combat left medial orbitofrontal cortex: P = .02, partial r = -0.222; DRRI-combat right medial orbitofrontal cortex: P = .005, partial r = -0.256; DRRI-aftermath left medial orbitofrontal cortex: P = .02, partial r = -0.214; DRRI-aftermath right medial orbitofrontal cortex: P = .005, partial r = -0.260; DRRI-aftermath right lateral orbitofrontal cortex: P = .03, partial r = -0.196), and parahippocampal (DRRI-aftermath right: P = .03, partial r = -0.191) gyrus, as well as with higher FAT in the amygdala-hippocampus complex (DRRI-combat: P = .005, partial r = 0.254; DRRI-aftermath: P = .02, partial r = 0.223). Lower FAT in the cingulate-orbitofrontal gyri was associated with impaired response inhibition (Stroop-IS left cingulate: P < .001, partial r = -0.440; Stroop-IS right cingulate: P < .001, partial r = -0.372; Stroop-IS left medial orbitofrontal cortex: P < .001, partial r = -0.304; Stroop-IS right medial orbitofrontal cortex: P < .001, partial r = -0.340; Stroop-IN left cingulate: P < .001, partial r = -0.421; Stroop-IN right cingulate: P < .001, partial r = -0.300; Stroop-IN left medial orbitofrontal cortex: P = .01, partial r = -0.223; Stroop-IN right medial orbitofrontal cortex: P < .001, partial r = -0.343), whereas higher FAT in the mesial temporal regions was associated with improved short-term memory and processing speed (left amygdala-hippocampus complex: P < .001, partial r = -0.574; right amygdala-hippocampus complex: P < .001, partial r = 0.645; short-term memory left amygdala-hippocampus complex: P < .001, partial r = 0.570; short-term memory right amygdala-hippocampus complex: P < .001, partial r = 0.633). A history of mTBI did not modulate the association between war zone-related stress and GM diffusion. CONCLUSIONS AND RELEVANCE This study revealed an association between war zone-related stress and alteration of limbic GM microstructure, which was associated with cognitive functioning. These results suggest that altered limbic GM microstructure may underlie the deleterious outcomes of war zone-related stress on brain health. Military service members may benefit from early therapeutic interventions after deployment to a war zone.
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Affiliation(s)
- Elisabeth Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Neurology, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Philine Rojczyk
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Valerie J. Sydnor
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Jeffrey P. Guenette
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yorghos Tripodis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Boston University Alzheimer’s Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts
| | - David Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Diagnostic and Interventional Radiology and Neuroradiology, Klinikum Augsburg, Germany
| | - Lisa Umminger
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Nico Sollmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Catherine B. Fortier
- Translational Research Center for TBI and Stress Disorders and Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - David Salat
- Translational Research Center for TBI and Stress Disorders and Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Sidney R. Hinds
- Department of Neurology, Uniformed Services University of the Health Science, Bethesda, Maryland
| | - William P. Milberg
- Translational Research Center for TBI and Stress Disorders and Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Regina E. McGlinchey
- Translational Research Center for TBI and Stress Disorders and Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Neurology, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Boston, Massachusetts
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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46
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Leonhardt Y, Dieckmeyer M, Zoffl F, Feuerriegel GC, Sollmann N, Junker D, Greve T, Holzapfel C, Hauner H, Subburaj K, Kirschke JS, Karampinos DC, Zimmer C, Makowski MR, Baum T, Burian E. Associations of Texture Features of Proton Density Fat Fraction Maps between Lumbar Vertebral Bone Marrow and Paraspinal Musculature. Biomedicines 2022; 10:biomedicines10092075. [PMID: 36140176 PMCID: PMC9495779 DOI: 10.3390/biomedicines10092075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 12/02/2022] Open
Abstract
Chemical shift encoding-based water−fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) has been used for non-invasive assessment of regional body fat distributions. More recently, texture analysis (TA) has been proposed to reveal even more detailed information about the vertebral or muscular composition beyond PDFF. The aim of this study was to investigate associations between vertebral bone marrow and paraspinal muscle texture features derived from CSE-MRI-based PDFF maps in a cohort of healthy subjects. In this study, 44 healthy subjects (13 males, 55 ± 30 years; 31 females, 39 ± 17 years) underwent 3T MRI including a six-echo three-dimensional (3D) spoiled gradient echo sequence used for CSE-MRI at the lumbar spine and the paraspinal musculature. The erector spinae muscles (ES), the psoas muscles (PS), and the vertebral bodies L1-4 (LS) were manually segmented. Mean PDFF values and texture features were extracted for each compartment. Features were compared between males and females using logistic regression analysis adjusted for age and body mass index (BMI). All texture features of ES except for Sum Average were significantly (p < 0.05) different between men and women. The three global texture features (Variance, Skewness, Kurtosis) for PS as well as LS showed a significant difference between male and female subjects (p < 0.05). Mean PDFF measured in PS and ES was significantly higher in females, but no difference was found for the vertebral bone marrow’s PDFF. Partial correlation analysis between the texture features of the spine and the paraspinal muscles revealed a highly significant correlation for Variance(global) (r = 0.61 for ES, r = 0.62 for PS; p < 0.001 respectively). Texture analysis using PDFF maps based on CSE-MRI revealed differences between healthy male and female subjects. Global texture features in the lumbar vertebral bone marrow allowed for differentiation between men and women, when the overall PDFF was not significantly different, indicating that PDFF maps may contain detailed and subtle textural information beyond fat fraction. The observed significant correlation of Variance(global) suggests a metabolic interrelationship between vertebral bone marrow and the paraspinal muscles.
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Affiliation(s)
- Yannik Leonhardt
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Correspondence:
| | - Michael Dieckmeyer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Florian Zoffl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Georg C. Feuerriegel
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89070 Ulm, Germany
| | - Daniela Junker
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Tobias Greve
- Department of Neurosurgery, University Hospital, Ludwig-Maximilians-University (LMU) Munich, 81377 Munich, Germany
| | - Christina Holzapfel
- Institute of Nutritional Medicine, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Hans Hauner
- Institute of Nutritional Medicine, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | | | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Dimitrios C. Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Marcus R. Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
| | - Egon Burian
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
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47
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Sollmann N. Editorial for “Magnetic Resonance
Imaging‐Based
Radiomics Nomogram for Preoperative Differentiation Between Ocular Adnexal Lymphoma and Idiopathic Orbital Inflammation”. J Magn Reson Imaging 2022; 57:1605-1606. [PMID: 35986563 DOI: 10.1002/jmri.28405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 08/03/2022] [Indexed: 11/11/2022] Open
Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology University Hospital Ulm Ulm Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine Klinikum rechts der Isar, Technical University of Munich Munich Germany
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48
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Vogele D, Kloth C, Linderich L, Sollmann N, Beck A, Formentini A, Albers R, Schultheiß M, Vogele D. Autounfall mit schwerer Bauchwandverletzung. ROFO-FORTSCHR RONTG 2022. [DOI: 10.1055/s-0042-1756580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- D Vogele
- Uniklinik Ulm, Diagnostische und Interventionelle Radiologie,
Ulm
| | - C Kloth
- Universitätsklinikum Ulm, Klinik für Diagnostische und
Interventionelle Radiologie, Ulm
| | - L Linderich
- Klinik für Diagnostische und Interventionelle Radiologie,
Uniklinik Ulm, Ulm
| | - N Sollmann
- Klinik für Diagnostische und Interventionelle Radiologie,
Uniklinkium Ulm, Ulm
| | - A Beck
- Institut für Pathologie, Uniklinikum Ulm, Ulm
| | - A Formentini
- Klinik für Allgemein- und Viszeralchirurgie, Uniklinikum Ulm,
Ulm
| | - R Albers
- Klinik für Allgemein- und Viszeralchirurgie, Uniklinikum Ulm,
Ulm
| | - M Schultheiß
- Klinik für Unfall-, Hand-, Plastische und
Wiederherstellungschirurgie, Uniklinik Ulm, Ulm
| | - D Vogele
- Klinik für Diagnostische und Interventionelle Radiologie,
Uniklinikum Ulm, Ulm
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49
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Börner C, Renner T, Trepte-Freisleder F, Urban G, Schandelmaier P, Lang M, Lechner MF, Koenig H, Klose B, Albers L, Krieg SM, Baum T, Heinen F, Landgraf MN, Sollmann N, Bonfert MV. Response Predictors of Repetitive Neuromuscular Magnetic Stimulation in the Preventive Treatment of Episodic Migraine. Front Neurol 2022; 13:919623. [PMID: 35989916 PMCID: PMC9384696 DOI: 10.3389/fneur.2022.919623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundRepetitive neuromuscular magnetic stimulation (rNMS) of the trapezius muscles showed beneficial effects in preventing episodic migraine. However, clinical characteristics that predict a favorable response to rNMS are unknown. The objective of this analysis is to identify such predictors.MethodsThirty participants with a diagnosis of episodic migraine (mean age: 24.8 ± 4.0 years, 29 females), who were prospectively enrolled in two non-sham-controlled studies evaluating the effects of rNMS were analyzed. In these studies, the interventional stimulation of the bilateral trapezius muscles was applied in six sessions and distributed over two consecutive weeks. Baseline and follow-up assessments included the continuous documentation of a headache calendar over 30 days before and after the stimulation period, the Migraine Disability Assessment Score (MIDAS) questionnaire (before stimulation and 90 days after stimulation), and measurements of pain pressure thresholds (PPTs) above the trapezius muscles by algometry (before and after each stimulation session). Participants were classified as responders based on a ≥25% reduction in the variable of interest (headache frequency, headache intensity, days with analgesic intake, MIDAS score, left-sided PPTs, right-sided PPTs). Post-hoc univariate and multivariate binary logistic regression analyses were performed.ResultsLower headache frequency (P = 0.016) and intensity at baseline (P = 0.015) and a migraine diagnosis without a concurrent tension-type headache component (P = 0.011) were significantly related to a ≥25% reduction in headache frequency. Higher headache frequency (P = 0.052) and intensity at baseline (P = 0.014) were significantly associated with a ≥25% reduction in monthly days with analgesic intake. Lower right-sided PPTs at baseline were significantly related to a ≥25% increase in right-sided PPTs (P = 0.0.015) and left-sided PPTs (P =0.030). Performance of rNMS with higher stimulation intensities was significantly associated with a ≥25% reduction in headache intensity (P = 0.046).ConclusionsClinical headache characteristics at baseline, the level of muscular hyperalgesia, and stimulation intensity may inform about how well an individual patient responds to rNMS. These factors may allow an early identification of patients that would most likely benefit from rNMS.
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Affiliation(s)
- Corinna Börner
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Tabea Renner
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Florian Trepte-Freisleder
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Giada Urban
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Paul Schandelmaier
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Magdalena Lang
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Matthias F. Lechner
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Helene Koenig
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Birgit Klose
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Lucia Albers
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Sandro M. Krieg
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Heinen
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mirjam N. Landgraf
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- *Correspondence: Nico Sollmann
| | - Michaela V. Bonfert
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, Dr. von Hauner Children's Hospital, LMU Hospital, Ludwig-Maximilians-Universität, Munich, Germany
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50
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Börner C, Staisch J, Lang M, Hauser A, Hannibal I, Huß K, Klose B, Lechner MF, Sollmann N, Heinen F, Landgraf MN, Bonfert MV. Repetitive Neuromuscular Magnetic Stimulation for Pediatric Headache Disorders: Muscular Effects and Factors Affecting Level of Response. Brain Sci 2022; 12:brainsci12070932. [PMID: 35884738 PMCID: PMC9320292 DOI: 10.3390/brainsci12070932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 02/04/2023] Open
Abstract
Repetitive neuromuscular magnetic stimulation (rNMS) for pediatric headache disorders is feasible, safe, and alleviates headache symptoms. This study assesses muscular effects and factors affecting response to rNMS. A retrospective chart review included children with headaches receiving six rNMS sessions targeting the upper trapezius muscles. Pressure pain thresholds (PPT) were measured before and after rNMS, and at 3-month follow-up (FU). Mean headache frequency, duration, and intensity within the last 3 months were documented. In 20 patients (14.1 ± 2.7 years), PPT significantly increased from pre- to post-treatment (p < 0.001) sustaining until FU. PPT changes significantly differed between primary headache and post-traumatic headache (PTH) (p = 0.019−0.026). Change in headache frequency was significantly higher in patients with than without neck pain (p = 0.032). A total of 60% of patients with neck pain responded to rNMS (≥25%), while 20% of patients without neck pain responded (p = 0.048). 60% of patients receiving rNMS twice a week were responders, while 33% of patients receiving rNMS less or more frequently responded to treatment, respectively. Alleviation of muscular hyperalgesia was demonstrated sustaining for 3 months, which was emphasized in PTH. The rNMS sessions may positively modulate headache symptoms regardless of headache diagnosis. Patients with neck pain profit explicitly well. Two rNMS sessions per week led to the highest reduction in headache frequency.
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Affiliation(s)
- Corinna Börner
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Jacob Staisch
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Magdalena Lang
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Ari Hauser
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Iris Hannibal
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Kristina Huß
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Birgit Klose
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Matthias F. Lechner
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany;
- TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany
| | - Florian Heinen
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Mirjam N. Landgraf
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
| | - Michaela V. Bonfert
- LMU Hospital, Department of Pediatrics—Dr. von Hauner Children’s Hospital, Division of Pediatric Neurology and Developmental Medicine, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany; (C.B.); (J.S.); (M.L.); (A.H.); (I.H.); (K.H.); (B.K.); (M.F.L.); (F.H.); (M.N.L.)
- LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians Universität, Lindwurm Str. 4, 80337 Munich, Germany
- Correspondence:
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