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Michael FA, Hessz D, Graf C, Zimmer C, Nour S, Jung M, Kloka J, Knabe M, Welsch C, Blumenstein I, Dultz G, Finkelmeier F, Walter D, Mihm U, Lingwal N, Zeuzem S, Bojunga J, Friedrich-Rust M. Thoracic impedance pneumography in propofol-sedated patients undergoing percutaneous endoscopic gastrostomy (PEG) placement in gastrointestinal endoscopy: A prospective, randomized trial. J Clin Anesth 2024; 94:111403. [PMID: 38368798 DOI: 10.1016/j.jclinane.2024.111403] [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: 06/06/2023] [Revised: 11/25/2023] [Accepted: 01/23/2024] [Indexed: 02/20/2024]
Abstract
STUDY OBJECTIVE To assess the efficacy of an ECG-based method called thoracic impedance pneumography to reduce hypoxic events in endoscopy. DESIGN This was a single center, 1:1 randomized controlled trial. SETTING The trial was conducted during the placement of percutaneous endoscopic gastrostomy (PEG). PATIENTS 173 patients who underwent PEG placement were enrolled in the present trial. Indication was oncological in most patients (89%). 58% of patients were ASA class II and 42% of patients ASA class III. INTERVENTIONS Patients were randomized in the standard monitoring group (SM) with pulse oximetry and automatic blood pressure measurement or in the intervention group with additional thoracic impedance pneumography (TIM). Sedation was performed with propofol by gastroenterologists or trained nurses. MEASUREMENTS Hypoxic episodes defined as SpO2 < 90% for >15 s were the primary endpoint. Secondary endpoints were minimal SpO2, apnea >10s/>30s and incurred costs. MAIN RESULTS Additional use of thoracic impedance pneumography reduced hypoxic episodes (TIM: 31% vs SM: 49%; p = 0.016; OR 0.47; NNT 5.6) and elevated minimal SpO2 per procedure (TIM: 90.0% ± 8.9; SM: 84.0% ± 17.6; p = 0.007) significantly. Apnea events >10s and > 30s were significantly more often detected in TIM (43%; 7%) compared to SM (1%; 0%; p < 0.001; p = 0.014) resulting in a time advantage of 17 s before the occurrence of hypoxic events. As a result, adjustments of oxygen flow were significantly more often necessary in SM than in TIM (p = 0.034) and assisted ventilation was less often needed in TIM (2%) compared with SM (9%; p = 0.053). Calculated costs for the additional use of thoracic impedance pneumography were 0.13$ (0.12 €/0.11 £) per procedure. CONCLUSIONS Additional thoracic impedance pneumography reduced the quantity and extent of hypoxic events with less need of assisted ventilation. Supplemental costs per procedure were negligible. KEY WORDS thoracic impedance pneumography, capnography, sedation, monitoring, gastrointestinal endoscopy, percutaneous endoscopic gastrostomy.
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Affiliation(s)
- F A Michael
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany.
| | - D Hessz
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - C Graf
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - C Zimmer
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - S Nour
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - M Jung
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - J Kloka
- Goethe University Frankfurt, University Hospital, Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Frankfurt am Main, Germany
| | - M Knabe
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - C Welsch
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - I Blumenstein
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - G Dultz
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - F Finkelmeier
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - D Walter
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - U Mihm
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - N Lingwal
- Goethe University Frankfurt, University Hospital, Institute of Biostatistics and Mathematical Modeling, Frankfurt am Main, Germany
| | - S Zeuzem
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - J Bojunga
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
| | - M Friedrich-Rust
- Goethe University Frankfurt, University Hospital, Department of Internal Medicine 1, Frankfurt am Main, Germany
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Schultz V, Hedderich DM, Schmitz-Koep B, Schinz D, Zimmer C, Yakushev I, Apostolova I, Özden C, Opfer R, Buchert R. Removing outliers from the normative database improves regional atrophy detection in single-subject voxel-based morphometry. Neuroradiology 2024; 66:507-519. [PMID: 38378906 PMCID: PMC10937771 DOI: 10.1007/s00234-024-03304-3] [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: 10/31/2023] [Accepted: 02/03/2024] [Indexed: 02/22/2024]
Abstract
PURPOSE Single-subject voxel-based morphometry (VBM) compares an individual T1-weighted MRI to a sample of normal MRI in a normative database (NDB) to detect regional atrophy. Outliers in the NDB might result in reduced sensitivity of VBM. The primary aim of the current study was to propose a method for outlier removal ("NDB cleaning") and to test its impact on the performance of VBM for detection of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). METHODS T1-weighted MRI of 81 patients with biomarker-confirmed AD (n = 51) or FTLD (n = 30) and 37 healthy subjects with simultaneous FDG-PET/MRI were included as test dataset. Two different NDBs were used: a scanner-specific NDB (37 healthy controls from the test dataset) and a non-scanner-specific NDB comprising 164 normal T1-weighted MRI from 164 different MRI scanners. Three different quality metrics based on leave-one-out testing of the scans in the NDB were implemented. A scan was removed if it was an outlier with respect to one or more quality metrics. VBM maps generated with and without NDB cleaning were assessed visually for the presence of AD or FTLD. RESULTS Specificity of visual interpretation of the VBM maps for detection of AD or FTLD was 100% in all settings. Sensitivity was increased by NDB cleaning with both NDBs. The effect was statistically significant for the multiple-scanner NDB (from 0.47 [95%-CI 0.36-0.58] to 0.61 [0.49-0.71]). CONCLUSION NDB cleaning has the potential to improve the sensitivity of VBM for the detection of AD or FTLD without increasing the risk of false positive findings.
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Affiliation(s)
- Vivian Schultz
- Department of Neuroradiology, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Ismaninger Str. 22, 81675, Munich, Germany.
| | - Dennis M Hedderich
- Department of Neuroradiology, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Ismaninger Str. 22, 81675, Munich, Germany
| | - Benita Schmitz-Koep
- Department of Neuroradiology, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Ismaninger Str. 22, 81675, Munich, Germany
| | - David Schinz
- Department of Neuroradiology, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Ismaninger Str. 22, 81675, Munich, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen (FAU), Nürnberg, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Ismaninger Str. 22, 81675, Munich, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts Der Isar, Technical University of Munich, School of Medicine and Health, Munich, Germany
| | - Ivayla Apostolova
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Cansu Özden
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Ralph Buchert
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Straube C, Combs SE, Bernhardt D, Gempt J, Meyer B, Zimmer C, Schmidt-Graf F, Vajkoczy P, Grün A, Ehret F, Zips D, Kaul D. Adjuvant re-irradiation vs. no early re-irradiation of resected recurrent glioblastoma: pooled comparative cohort analysis from two tertiary centers. J Neurooncol 2024:10.1007/s11060-024-04633-2. [PMID: 38520571 DOI: 10.1007/s11060-024-04633-2] [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: 12/10/2023] [Accepted: 03/04/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND The optimal management strategy for recurrent glioblastoma (rGBM) remains uncertain, and the impact of re-irradiation (Re-RT) on overall survival (OS) is still a matter of debate. This study included patients who achieved gross total resection (GTR) after a second surgery after recurrence, following the GlioCave criteria. METHODS Inclusion criteria include being 18 years or older, having histologically confirmed locally recurrent IDHwt or IDH unknown GBM, achieving MRI-proven GTR after the second surgery, having a Karnofsky performance status of at least 60% after the second surgery, having a minimum interval of 6 months between the first radiotherapy and the second surgery, and a maximum of 8 weeks from second surgery to the start of Re-RT. RESULTS A total of 44 patients have met the inclusion criteria. The median OS after the second surgery was 14 months. All patients underwent standard treatment after initial diagnosis, including maximum safe resection, adjuvant radiochemotherapy and adjuvant chemotherapy. Re-RT did not significantly impact OS. However, MGMT promoter methylation status and a longer interval (> 12 months) between treatments were associated with better OS. Multivariate analysis revealed the MGMT status as the only significant predictor of OS. CONCLUSION Factors such as MGMT promoter methylation status and treatment interval play crucial roles in determining patient outcomes after second surgery. Personalized treatment strategies should consider these factors to optimize the management of rGBM. Prospective research is needed to define the value of re-RT after second surgery and to inform decision making in this situation.
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Affiliation(s)
- Christoph Straube
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
- Department of Radiation Oncology and Radiotherapy, Klinikum Landshut, Landshut, Germany.
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, University Hamburg-Eppendorf, Hamburg, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Friederike Schmidt-Graf
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Arne Grün
- Department of Radiation Oncology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Felix Ehret
- Department of Radiation Oncology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Berlin, Germany
- Partner Site Berlin, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Berlin, Germany
- Partner Site Berlin, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David Kaul
- Department of Radiation Oncology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Berlin, Germany
- Partner Site Berlin, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
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4
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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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Wiltgen T, McGinnis J, Schlaeger S, Kofler F, Voon C, Berthele A, Bischl D, Grundl L, Will N, Metz M, Schinz D, Sepp D, Prucker P, Schmitz-Koep B, Zimmer C, Menze B, Rueckert D, Hemmer B, Kirschke J, Mühlau M, Wiestler B. LST-AI: a Deep Learning Ensemble for Accurate MS Lesion Segmentation. medRxiv 2024:2023.11.23.23298966. [PMID: 38045345 PMCID: PMC10690346 DOI: 10.1101/2023.11.23.23298966] [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: 12/05/2023]
Abstract
Automated segmentation of brain white matter lesions is crucial for both clinical assessment and scientific research in multiple sclerosis (MS). Over a decade ago, we introduced an engineered lesion segmentation tool, LST. While recent lesion segmentation approaches have leveraged artificial intelligence (AI), they often remain proprietary and difficult to adopt. As an open-source tool, we present LST-AI, an advanced deep learning-based extension of LST that consists of an ensemble of three 3D-UNets. LST-AI explicitly addresses the imbalance between white matter (WM) lesions and non-lesioned WM. It employs a composite loss function incorporating binary cross-entropy and Tversky loss to improve segmentation of the highly heterogeneous MS lesions. We train the network ensemble on 491 MS pairs of T1w and FLAIR images, collected in-house from a 3T MRI scanner, and expert neuroradiologists manually segmented the utilized lesion maps for training. LST-AI additionally includes a lesion location annotation tool, labeling lesion location according to the 2017 McDonald criteria (periventricular, infratentorial, juxtacortical, subcortical). We conduct evaluations on 103 test cases consisting of publicly available data using the Anima segmentation validation tools and compare LST-AI with several publicly available lesion segmentation models. Our empirical analysis shows that LST-AI achieves superior performance compared to existing methods. Its Dice and F1 scores exceeded 0.62, outperforming LST, SAMSEG (Sequence Adaptive Multimodal SEGmentation), and the popular nnUNet framework, which all scored below 0.56. Notably, LST-AI demonstrated exceptional performance on the MSSEG-1 challenge dataset, an international WM lesion segmentation challenge, with a Dice score of 0.65 and an F1 score of 0.63-surpassing all other competing models at the time of the challenge. With increasing lesion volume, the lesion detection rate rapidly increased with a detection rate of >75% for lesions with a volume between 10mm3 and 100mm3. Given its higher segmentation performance, we recommend that research groups currently using LST transition to LST-AI. To facilitate broad adoption, we are releasing LST-AI as an open-source model, available as a command-line tool, dockerized container, or Python script, enabling diverse applications across multiple platforms.
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Affiliation(s)
- Tun Wiltgen
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julian McGinnis
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Computer Science, Institute for AI in Medicine, Technical University of Munich, Munich, Germany
| | - Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Kofler
- Department of Computer Science, Institute for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM, Center for Translational Cancer Research, Munich, Germany
- Helmholtz AI, Helmholtz Munich, Neuherberg, Germany
| | - CuiCi Voon
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Daria Bischl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Lioba Grundl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nikolaus Will
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - David Schinz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Dominik Sepp
- 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
| | - Benita Schmitz-Koep
- 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
| | - Bjoern Menze
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Daniel Rueckert
- Department of Computer Science, Institute for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Computing, Imperial College London, London, United Kingdom
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jan Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, 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
- TranslaTUM, Center for Translational Cancer Research, Munich, Germany
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6
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Ray D, Sheldon EL, Zimmer C, Martin LB, Schrey AW. Screening H3 Histone Acetylation in a Wild Bird, the House Sparrow ( Passer Domesticus). Integr Org Biol 2024; 6:obae004. [PMID: 38516554 PMCID: PMC10956398 DOI: 10.1093/iob/obae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/07/2024] [Accepted: 02/26/2024] [Indexed: 03/23/2024] Open
Abstract
Epigenetic mechanisms are increasingly understood to have major impacts across ecology. However, one molecular epigenetic mechanism, DNA methylation, currently dominates the literature. A second mechanism, histone modification, is likely important to ecologically relevant phenotypes and thus warrants investigation, especially because molecular interplay between methylation and histone acetylation can strongly affect gene expression. There are a limited number of histone acetylation studies on non-model organisms, yet those that exist show that it can impact gene expression and phenotypic plasticity. Wild birds provide an excellent system to investigate histone acetylation, as free-living individuals must rapidly adjust to environmental change. Here, we screen histone acetylation in the house sparrow (Passer domesticus); we studied this species because DNA methylation was important in the spread of this bird globally. This species has one of the broadest geographic distributions in the world, and part of this success is related to the way that it uses methylation to regulate its gene expression. Here, we verify that a commercially available assay that was developed for mammals can be used in house sparrows. We detected high variance in histone acetylation among individuals in both liver and spleen tissue. Further, house sparrows with higher epigenetic potential in the Toll Like Receptor-4 (TLR-4) promoter (i.e., CpG content) had higher histone acetylation in liver. Also, there was a negative correlation between histone acetylation in spleen and TLR-4 expression. In addition to validating a method for measuring histone acetylation in wild songbirds, this study also shows that histone acetylation is related to epigenetic potential and gene expression, adding a new study option for ecological epigenetics.
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Affiliation(s)
- D Ray
- Department of Biology, Georgia Southern University, Savannah, GA 31419, United States
| | - E L Sheldon
- USF Global Health and Infectious Disease Research Center and USF Genomics Center, College of Public Health University of South Florida, Tampa, FL 33612, United States
| | - C Zimmer
- Laboratoire d'Ethologie Expérimentale et Comparée, LEEC, Université Sorbonne Paris Nord, UR 4443, 93430 Villetaneuse, France
| | - L B Martin
- USF Global Health and Infectious Disease Research Center and USF Genomics Center, College of Public Health University of South Florida, Tampa, FL 33612, United States
| | - A W Schrey
- Department of Biology, Georgia Southern University, Savannah, GA 31419, United States
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7
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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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8
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Krug N, Braun H, Knez A, Auerbach H, Bodenberger S, Eglseder B, Kirschke J, Boeckh-Behrens T, Wunderlich S, Henninger J, Boy S, Renz M, Sepp D, Zimmer C, Maegerlein C. Interdisciplinary Rendez-Vous Approach in Endovascular Stroke Treatment: A New Concept to Accelerate Mechanical Thrombectomy in Primary Stroke Centers. Cardiovasc Intervent Radiol 2024; 47:109-114. [PMID: 37989788 PMCID: PMC10769944 DOI: 10.1007/s00270-023-03610-y] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 10/26/2023] [Indexed: 11/23/2023]
Abstract
PURPOSE Prompt endovascular treatment of patients with stroke due to intracranial Large Vessel Occlusion (LVO) is a major challenge in rural areas because neurointerventionalists are usually not available. As a result, treatment is delayed, and clinical outcomes are worse compared with patients primarily treated in comprehensive stroke centers (CSC). To address this problem, we present a concept in which interdisciplinary, on-site endovascular treatment is performed in a Primary Stroke Center (PSC) by a team of interventional neuroradiologists and cardiologists: the Rendez-Vous approach. METHODS Thirty-five patients with LVO who underwent interdisciplinary thrombectomy on-site at the PSC as part of the Rendez-Vous concept were compared with 72 patients who were transferred from a PSCs to the CSC for thrombectomy when diagnosed with LVO in terms of temporal sequences and clinical outcomes. RESULTS Patients treated on-site at the PSC as part of the Rendez-Vous approach were managed as successfully and without an increase in complication rates compared with patients treated secondarily at a CSC (91.7% successful interventions in Rendez-Vous vs. 87.3% in control group, p = 0.57). The time from diagnosis of LVO to groin puncture was reduced by mean 74.3 min with the Rendez-Vous concept (p < 0.01). Regarding the clinical outcome, a functionally independent status was achieved in 45.5% in the Rendez-Vous group and in 22.6% in the control group (p = 0.029). CONCLUSION Thanks to interdisciplinary teamwork between cardiology and interventional neuroradiology in local PSCs, times to successful reperfusion can be reduced. This has a potentially positive impact on the clinical outcome of stroke patients.
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Affiliation(s)
- Nadja Krug
- Diagnostic and Interventional Neuroradiology, University Hospital Basel, Basel, Switzerland
| | - Holger Braun
- Medical Department, Krankenhaus Weilheim, Weilheim, Germany
| | - Andreas Knez
- Medical Department, Krankenhaus Weilheim, Weilheim, Germany
| | | | | | | | - Jan Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Silke Wunderlich
- Department of Neurology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | | | - Sandra Boy
- Department of Neurology, Asklepios Stadtklinik Bad Tölz, Bad Tölz, Germany
| | - Martin Renz
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Dominik Sepp
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Christian Maegerlein
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany.
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9
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Metz MC, Ezhov I, Peeken JC, Buchner JA, Lipkova J, Kofler F, Waldmannstetter D, Delbridge C, Diehl C, Bernhardt D, Schmidt-Graf F, Gempt J, Combs SE, Zimmer C, Menze B, Wiestler B. Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model. Neurooncol Adv 2024; 6:vdad171. [PMID: 38435962 PMCID: PMC10907005 DOI: 10.1093/noajnl/vdad171] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024] Open
Abstract
Background The diffuse growth pattern of glioblastoma is one of the main challenges for accurate treatment. Computational tumor growth modeling has emerged as a promising tool to guide personalized therapy. Here, we performed clinical and biological validation of a novel growth model, aiming to close the gap between the experimental state and clinical implementation. Methods One hundred and twenty-four patients from The Cancer Genome Archive (TCGA) and 397 patients from the UCSF Glioma Dataset were assessed for significant correlations between clinical data, genetic pathway activation maps (generated with PARADIGM; TCGA only), and infiltration (Dw) as well as proliferation (ρ) parameters stemming from a Fisher-Kolmogorov growth model. To further evaluate clinical potential, we performed the same growth modeling on preoperative magnetic resonance imaging data from 30 patients of our institution and compared model-derived tumor volume and recurrence coverage with standard radiotherapy plans. Results The parameter ratio Dw/ρ (P < .05 in TCGA) as well as the simulated tumor volume (P < .05 in TCGA/UCSF) were significantly inversely correlated with overall survival. Interestingly, we found a significant correlation between 11 proliferation pathways and the estimated proliferation parameter. Depending on the cutoff value for tumor cell density, we observed a significant improvement in recurrence coverage without significantly increased radiation volume utilizing model-derived target volumes instead of standard radiation plans. Conclusions Identifying a significant correlation between computed growth parameters and clinical and biological data, we highlight the potential of tumor growth modeling for individualized therapy of glioblastoma. This might improve the accuracy of radiation planning in the near future.
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Affiliation(s)
- Marie-Christin Metz
- Department of Diagnostic and Interventional Neuroradiology, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Germany
- TranslaTUM—Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany
| | - Jan C Peeken
- Department of Radiation Oncology, Technical University of Munich, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Munich, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Josef A Buchner
- Department of Radiation Oncology, Technical University of Munich, Munich, Germany
| | - Jana Lipkova
- Department of Pathology and Molecular Medicine, University of California, Irvine, Irvine, CA, USA
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Munich, Germany
- Helmholtz Artificial Intelligence Cooperation Unit, Helmholtz Zentrum Munich, Munich, Germany
- TranslaTUM—Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany
| | | | - Claire Delbridge
- Department of Neuropathology, Institute of Pathology, Technical University of Munich, Munich, Germany
| | - Christian Diehl
- Department of Radiation Oncology, Technical University of Munich, Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Technical University of Munich, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Munich, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | | | - Jens Gempt
- Department of Neurosurgery, Technical University of Munich, Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Technical University of Munich, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Helmholtz Zentrum München, Munich, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Technical University of Munich, Munich, Germany
| | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, Technical University of Munich, Munich, Germany
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10
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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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11
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Tahedl M, Wiltgen T, Voon CC, Berthele A, Kirschke JS, Hemmer B, Mühlau M, Zimmer C, Wiestler B. Cortical Thin Patch Fraction Reflects Disease Burden in MS: The Mosaic Approach. AJNR Am J Neuroradiol 2023; 45:82-89. [PMID: 38164526 PMCID: PMC10756581 DOI: 10.3174/ajnr.a8064] [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: 08/04/2023] [Accepted: 10/18/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND PURPOSE GM pathology plays an essential role in MS disability progression, emphasizing the importance of neuroradiologic biomarkers to capture the heterogeneity of cortical disease burden. This study aimed to assess the validity of a patch-wise, individual interpretation of cortical thickness data to identify GM pathology, the "mosaic approach," which was previously suggested as a biomarker for assessing and localizing atrophy. MATERIALS AND METHODS We investigated the mosaic approach in a cohort of 501 patients with MS with respect to 89 internal and 651 external controls. The resulting metric of the mosaic approach is the so-called thin patch fraction, which is an estimate of overall cortical disease burden per patient. We evaluated the mosaic approach with respect to the following: 1) discrimination between patients with MS and controls, 2) classification between different MS phenotypes, and 3) association with established biomarkers reflecting MS disease burden, using general linear modeling. RESULTS The thin patch fraction varied significantly between patients with MS and healthy controls and discriminated among MS phenotypes. Furthermore, the thin patch fraction was associated with disease burden, including the Expanded Disability Status Scale, cognitive and fatigue scores, and lesion volume. CONCLUSIONS This study demonstrates the validity of the mosaic approach as a neuroradiologic biomarker in MS. The output of the mosaic approach, namely the thin patch fraction, is a candidate biomarker for assessing and localizing cortical GM pathology. The mosaic approach can furthermore enhance the development of a personalized cortical MS biomarker, given that the thin patch fraction provides a feature on which artificial intelligence methods can be trained. Most important, we showed the validity of the mosaic approach when referencing data with respect to external control MR imaging repositories.
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Affiliation(s)
- Marlene Tahedl
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Tun Wiltgen
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Cui Ci Voon
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (B.H.), Munich, Germany
| | - Mark Mühlau
- Department of Neurology (T.W., C.C.V., A.B., B.H., M.M.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- From the Department of Neuroradiology (M.T., J.S.K., C.Z., B.W.), School of Medicine, Technical University of Munich, Munich, Germany
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12
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Lauerer M, McGinnis J, Bussas M, El Husseini M, Pongratz V, Engl C, Wuschek A, Berthele A, Riederer I, Kirschke JS, Zimmer C, Hemmer B, Mühlau M. Prognostic value of spinal cord lesion measures in early relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2023; 95:37-43. [PMID: 37495267 PMCID: PMC10804039 DOI: 10.1136/jnnp-2023-331799] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND Spinal cord (SC) lesions have been associated with unfavourable clinical outcomes in multiple sclerosis (MS). However, the relation of whole SC lesion number (SCLN) and volume (SCLV) to the future occurrence and type of confirmed disability accumulation (CDA) remains largely unexplored. METHODS In this monocentric retrospective study, SC lesions were manually delineated. Inclusion criteria were: age between 18 and 60 years, relapsing-remitting MS, disease duration under 2 years and clinical follow-up of 5 years. The first CDA event after baseline, determined by a sustained increase in the Expanded Disability Status Scale over 6 months, was classified as either progression independent of relapse activity (PIRA) or relapse-associated worsening (RAW). SCLN and SCLV were compared between different (sub)groups to assess their prospective value. RESULTS 204 patients were included, 148 of which had at least one SC lesion and 59 experienced CDA. Patients without any SC lesions experienced significantly less CDA (OR 5.8, 95% CI 2.1 to 19.8). SCLN and SCLV were closely correlated (rs=0.91, p<0.001) and were both significantly associated with CDA on follow-up (p<0.001). Subgroup analyses confirmed this association for patients with PIRA on CDA (34 events, p<0.001 for both SC lesion measures) but not for RAW (25 events, p=0.077 and p=0.22). CONCLUSION Patients without any SC lesions are notably less likely to experience CDA. Both the number and volume of SC lesions on MRI are associated with future accumulation of disability largely independent of relapses.
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Affiliation(s)
- Markus Lauerer
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University, Munich, Germany
| | - Julian McGinnis
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- Institute for AI in Medicine, Technical University, Munich, Germany
| | - Matthias Bussas
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University, Munich, Germany
| | - Malek El Husseini
- Department of Neuroradiology, School of Medicine, Technical University, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University, Munich, Germany
| | - Christina Engl
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
| | - Alexander Wuschek
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
| | - Isabelle Riederer
- Department of Neuroradiology, School of Medicine, Technical University, Munich, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, School of Medicine, Technical University, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University, Munich, Germany
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13
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Gasperi C, Wiltgen T, McGinnis J, Cerri S, Moridi T, Ouellette R, Pukaj A, Voon C, Bafligil C, Lauerer M, Andlauer TFM, Held F, Aly L, Shchetynsky K, Stridh P, Harroud A, Wiestler B, Kirschke JS, Zimmer C, Baras A, Piehl F, Berthele A, Granberg T, Kockum I, Hemmer B, Mühlau M. A Genetic Risk Variant for Multiple Sclerosis Severity is Associated with Brain Atrophy. Ann Neurol 2023; 94:1080-1085. [PMID: 37753809 DOI: 10.1002/ana.26807] [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: 07/21/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 09/28/2023]
Abstract
The minor allele of the genetic variant rs10191329 in the DYSF-ZNF638 locus is associated with unfavorable long-term clinical outcomes in multiple sclerosis patients. We investigated if rs10191329 is associated with brain atrophy measured by magnetic resonance imaging in a discovery cohort of 748 and a replication cohort of 360 people with relapsing multiple sclerosis. We observed an association with 28% more brain atrophy per rs10191329*A allele. Our results encourage stratification for rs10191329 in clinical trials. Unraveling the underlying mechanisms may enhance our understanding of pathophysiology and identify treatment targets. ANN NEUROL 2023;94:1080-1085.
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Affiliation(s)
- Christiane Gasperi
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Tun Wiltgen
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julian McGinnis
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Institute for AI in Medicine, Technical University of Munich, Munich, Germany
| | - Stefano Cerri
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas Moridi
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Russell Ouellette
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Albert Pukaj
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Cuici Voon
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Cemsel Bafligil
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Markus Lauerer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Till F M Andlauer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Friederike Held
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Lilian Aly
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | | | - Pernilla Stridh
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Adil Harroud
- Department of Neurology and Neurosurgery and Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- The Neuro (Montreal Neurological Institute and Hospital), McGill University, Montréal, Quebec, Canada
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals Inc, Tarrytown, New York, USA
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Ingrid Kockum
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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14
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Tahedl M, Wiltgen T, Voon CC, Berthele A, Kirschke JS, Hemmer B, Mühlau M, Zimmer C, Wiestler B. Benefits of a mosaic approach for assessing cortical atrophy in individual multiple sclerosis patients. Brain Behav 2023; 13:e3327. [PMID: 37961043 PMCID: PMC10726853 DOI: 10.1002/brb3.3327] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 10/31/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023] Open
Abstract
OBJECTIVE Cortical gray matter (GM) atrophy plays a central role in multiple sclerosis (MS) pathology. However, it is not commonly assessed in clinical routine partly because a number of methodological problems hamper the development of a robust biomarker to quantify GM atrophy. In previous work, we have demonstrated the clinical utility of the "mosaic approach" (MAP) to assess individual GM atrophy in the motor neuron disease spectrum and frontotemporal dementia. In this study, we investigated the clinical utility of MAP in MS, comparing this novel biomarker to existing methods for computing GM atrophy in single patients. We contrasted the strategies based on correlations with established biomarkers reflecting MS disease burden. METHODS We analyzed T1-weighted MPRAGE magnetic resonance imaging data from 465 relapsing-remitting MS patients and 89 healthy controls. We inspected how variations of existing strategies to estimate individual GM atrophy ("standard approaches") as well as variations of MAP (i.e., different parcellation schemes) impact downstream analysis results, both on a group and an individual level. We interpreted individual cortical disease burden as single metric reflecting the fraction of significantly atrophic data points with respect to the control group. In addition, we evaluated the correlations to lesion volume (LV) and Expanded Disability Status Scale (EDSS). RESULTS We found that the MAP method yielded highest correlations with both LV and EDSS as compared to all other strategies. Although the parcellation resolution played a minor role in terms of absolute correlations with clinical variables, higher resolutions provided more clearly defined statistical brain maps which may facilitate clinical interpretability. CONCLUSION This study provides evidence that MAP yields high potential for a clinically relevant biomarker in MS, outperforming existing methods to compute cortical disease burden in single patients. Of note, MAP outputs brain maps illustrating individual cortical disease burden which can be directly interpreted in daily clinical routine.
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Affiliation(s)
- Marlene Tahedl
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Tun Wiltgen
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Cui Ci Voon
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Achim Berthele
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Jan S. Kirschke
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Bernhard Hemmer
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Mark Mühlau
- Department of Neurology, School of MedicineTechnical University of MunichMunichGermany
| | - Claus Zimmer
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
| | - Benedikt Wiestler
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
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15
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Romahn EF, Wiltgen T, Bussas M, Aly L, Wicklein R, Noll C, Berthele A, Dehmelt V, Mardin C, Zimmer C, Korn T, Hemmer B, Kirschke JS, Mühlau M, Knier B. Association of retinal vessel pathology and brain atrophy in relapsing-remitting multiple sclerosis. Front Immunol 2023; 14:1284986. [PMID: 38090586 PMCID: PMC10715309 DOI: 10.3389/fimmu.2023.1284986] [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] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
Background Optical coherence tomography angiography (OCTA) allows non-invasive assessment of retinal vessel structures. Thinning and loss of retinal vessels is evident in eyes of patients with multiple sclerosis (MS) and might be associated with a proinflammatory disease phenotype and worse prognosis. We investigated whether changes of the retinal vasculature are linked to brain atrophy and disability in MS. Material and methods This study includes one longitudinal observational cohort (n=79) of patients with relapsing-remitting MS. Patients underwent annual assessment of the expanded disability status scale (EDSS), timed 25-foot walk, symbol digit modalities test (SDMT), retinal optical coherence tomography (OCT), OCTA, and brain MRI during a follow-up duration of at least 20 months. We investigated intra-individual associations between changes in the retinal architecture, vasculature, brain atrophy and disability. Eyes with a history of optic neuritis (ON) were excluded. Results We included 79 patients with a median disease duration of 12 (interquartile range 2 - 49) months and a median EDSS of 1.0 (0 - 2.0). Longitudinal retinal axonal and ganglion cell loss were linked to grey matter atrophy, cortical atrophy, and volume loss of the putamen. We observed an association between vessel loss of the superficial vascular complex (SVC) and both grey and white matter atrophy. Both observations were independent of retinal ganglion cell loss. Moreover, patients with worsening of the EDSS and SDMT revealed a pronounced longitudinal rarefication of the SVC and the deep vascular complex. Discussion ON-independent narrowing of the retinal vasculature might be linked to brain atrophy and disability in MS. Our findings suggest that retinal OCTA might be a new tool for monitoring neurodegeneration during MS.
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Affiliation(s)
- Eva Feodora Romahn
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Tun Wiltgen
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Matthias Bussas
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Lilian Aly
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Rebecca Wicklein
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Christina Noll
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Vera Dehmelt
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Christian Mardin
- Department of Ophthalmology, University Hospital of Erlangen-Nuremberg, Erlangen, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Thomas Korn
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Institute for Experimental Neuroimmunology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jan S. Kirschke
- Department of Neuroradiology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Benjamin Knier
- Department of Neurology, Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
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16
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Schinz D, Schmitz-Koep B, Tahedl M, Teckenberg T, Schultz V, Schulz J, Zimmer C, Sorg C, Gaser C, Hedderich DM. Lower cortical thickness and increased brain aging in adults with cocaine use disorder. Front Psychiatry 2023; 14:1266770. [PMID: 38025412 PMCID: PMC10679447 DOI: 10.3389/fpsyt.2023.1266770] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Background Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Methods Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. Results We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Conclusion Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.
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Affiliation(s)
- David Schinz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen- (FAU), Nürnberg, Germany
| | - Benita Schmitz-Koep
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marlene Tahedl
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Timo Teckenberg
- Digital Management & Transformation, SRH Fernhochschule - The Mobile University, Riedlingen, Germany
| | - Vivian Schultz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julia Schulz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Dennis M. Hedderich
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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17
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Schmitz‐Koep B, Menegaux A, Zimmermann J, Thalhammer M, Neubauer A, Wendt J, Schinz D, Daamen M, Boecker H, Zimmer C, Priller J, Wolke D, Bartmann P, Sorg C, Hedderich DM. Altered gray-to-white matter tissue contrast in preterm-born adults. CNS Neurosci Ther 2023; 29:3199-3211. [PMID: 37365964 PMCID: PMC10580354 DOI: 10.1111/cns.14320] [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: 12/16/2022] [Revised: 06/01/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023] Open
Abstract
AIMS To investigate cortical organization in brain magnetic resonance imaging (MRI) of preterm-born adults using percent contrast of gray-to-white matter signal intensities (GWPC), which is an in vivo proxy measure for cortical microstructure. METHODS Using structural MRI, we analyzed GWPC at different percentile fractions across the cortex (0%, 10%, 20%, 30%, 40%, 50%, and 60%) in a large and prospectively collected cohort of 86 very preterm-born (<32 weeks of gestation and/or birth weight <1500 g, VP/VLBW) adults and 103 full-term controls at 26 years of age. Cognitive performance was assessed by full-scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. RESULTS GWPC was significantly decreased in VP/VLBW adults in frontal, parietal, and temporal associative cortices, predominantly in the right hemisphere. Differences were pronounced at 20%, 30%, and 40%, hence, in middle cortical layers. GWPC was significantly increased in right paracentral lobule in VP/VLBW adults. GWPC in frontal and temporal cortices was positively correlated with birth weight, and negatively with duration of ventilation (p < 0.05). Furthermore, GWPC in right paracentral lobule was negatively correlated with IQ (p < 0.05). CONCLUSIONS Widespread aberrant gray-to-white matter contrast suggests lastingly altered cortical microstructure after preterm birth, mainly in middle cortical layers, with differential effects on associative and primary cortices.
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Affiliation(s)
- Benita Schmitz‐Koep
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Aurore Menegaux
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Juliana Zimmermann
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Melissa Thalhammer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Antonia Neubauer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Jil Wendt
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - David Schinz
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Marcel Daamen
- Department of Diagnostic and Interventional RadiologyUniversity Hospital Bonn, Clinical Functional Imaging GroupBonnGermany
- Department of Neonatology and Pediatric Intensive CareUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Department of Diagnostic and Interventional RadiologyUniversity Hospital Bonn, Clinical Functional Imaging GroupBonnGermany
| | - Claus Zimmer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Josef Priller
- Department of PsychiatryTechnical University of Munich, School of MedicineMunichGermany
| | - Dieter Wolke
- Department of PsychologyUniversity of WarwickCoventryUK
- Warwick Medical SchoolUniversity of WarwickCoventryUK
| | - Peter Bartmann
- Department of Neonatology and Pediatric Intensive CareUniversity Hospital BonnBonnGermany
| | - Christian Sorg
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
- Department of PsychiatryTechnical University of Munich, School of MedicineMunichGermany
| | - Dennis M. Hedderich
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
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18
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Schwarting J, Trost D, Albrecht C, Jörger AK, Zimmer C, Wostrack M, Meyer B, Bodden J, Boeckh-Behrens T. Risk identification for the development of large-artery vasospasm after aneurysmatic subarachnoid hemorrhage - a multivariate, risk-, and location-adjusted prediction model. J Neurointerv Surg 2023:jnis-2023-020649. [PMID: 37914393 DOI: 10.1136/jnis-2023-020649] [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: 05/31/2023] [Accepted: 10/19/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Vasospasm of the large cerebral arteries (CVS) after aneurysmatic subarachnoid hemorrhage (aSAH) reduces cerebral perfusion and causes delayed cerebral ischemia. Although endovascular spasmolysis shows convincing angiographic results, patients often do not improve in outcome. Delayed recognition of CVS contributes substantially to this effect. Therefore, this study aimed to confirm established and to identify unknown risk factors for CVS, which can be used for risk stratification. METHODS In this monocentric, retrospective cohort study of 853 patients with aSAH, we compared demographics, clinical, and radiographic parameters at the time of aneurysm occlusion between patients who developed CVS and those who did not. Significant cohort differences were included as predictors in a multivariate analysis to address confounding. Logistic regression models were used to determine odds ratios (ORs) for the presence of CVS for each predictor. RESULTS Of the 853 patients treated with aSAH, 304 (32%) developed CVS. In the univariable analysis, CVS was significantly associated with young age, female sex, aneurysm location, modified Fisher score, Barrow Neurological Institute (BNI) score, and surgical interventions. In the multivariable regression analysis, we identified BNI score (OR 1.33, 95% CI 1.11 to 1.58, p=0.002), decompressive craniectomy (OR 1.93, 95% CI 1.22 to 3.04, p=0.005), and aneurysm clipping (OR 2.22, 95% CI 1.50 to 3.29, p<0.001), as independent risk factors. CONCLUSIONS Young female patients with high BNI scores who undergo surgical interventions are more likely to develop CVS and should therefore be monitored most intensively after aneurysm occlusion.
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Affiliation(s)
- Julian Schwarting
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology/Neuroradiology, BGU, Berufsgenossenschaftliche Unfallklinik, Murnau, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Dominik Trost
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Carolin Albrecht
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Ann-Kathrin Jörger
- Department of Neurosurgery, 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
| | - Maria Wostrack
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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19
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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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20
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Schneider SC, Kaczmarz S, Göttler J, Kufer J, Zott B, Priller J, Kallmayer M, Zimmer C, Sorg C, Preibisch C. Stronger influence of systemic than local hemodynamic-vascular factors on resting-state BOLD functional connectivity. Neuroimage 2023; 281:120380. [PMID: 37741595 DOI: 10.1016/j.neuroimage.2023.120380] [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: 04/06/2023] [Revised: 08/28/2023] [Accepted: 09/13/2023] [Indexed: 09/25/2023] Open
Abstract
Correlated fluctuations in the blood oxygenation level dependent (BOLD) signal of resting-state functional MRI (i.e., BOLD-functional connectivity, BOLD-FC) reflect a spectrum of neuronal and non-neuronal processes. In particular, there are multiple hemodynamic-vascular influences on BOLD-FC on both systemic (e.g., perfusion delay) and local levels (e.g., neurovascular coupling). While the influence of individual factors has been studied extensively, combined and comparative studies of systemic and local hemodynamic-vascular factors on BOLD-FC are scarce, notably in humans. We employed a multi-modal MRI approach to investigate and compare distinct hemodynamic-vascular processes and their impact on homotopic BOLD-FC in healthy controls and patients with unilateral asymptomatic internal carotid artery stenosis (ICAS). Asymptomatic ICAS is a cerebrovascular disorder, in which neuronal functioning is largely preserved but hemodynamic-vascular processes are impaired, mostly on the side of stenosis. Investigated indicators for local hemodynamic-vascular processes comprise capillary transit time heterogeneity (CTH) and cerebral blood volume (CBV) from dynamic susceptibility contrast (DSC) MRI, and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL). Indicators for systemic processes are time-to-peak (TTP) from DSC MRI and BOLD lags from functional MRI. For each of these parameters, their influence on BOLD-FC was estimated by a comprehensive linear mixed model. Equally across groups, we found that individual mean BOLD-FC, local (CTH, CBV, and CBF) and systemic (TTP and BOLD lag) hemodynamic-vascular factors together explain 40.7% of BOLD-FC variance, with 20% of BOLD-FC variance explained by hemodynamic-vascular factors, with an about two-times larger contribution of systemic versus local factors. We conclude that regional differences in blood supply, i.e., systemic perfusion delays, exert a stronger influence on BOLD-FC than impairments in local neurovascular coupling.
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Affiliation(s)
- Sebastian C Schneider
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany.
| | - Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Philips GmbH Market DACH, Hamburg, Germany
| | - Jens Göttler
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Jan Kufer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, United States of America
| | - Benedikt Zott
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Josef Priller
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany
| | - Michael Kallmayer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for vascular surgery, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Claus Zimmer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
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21
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Hernandez Petzsche MR, Boeckh-Behrens T, Bernkopf K, Henze S, Maegerlein C, Sepp D, Zimmer C, Wunderlich S, Ikenberg B, Berndt MT. Breaking with a dogma: persisting diffusion restrictions (pDWI) in follow-up after endovascular treatment for stroke. J Neurointerv Surg 2023; 15:1129-1135. [PMID: 36539271 DOI: 10.1136/jnis-2022-019678] [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: 09/26/2022] [Accepted: 11/24/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Post-stroke diffusion weighted imaging (DWI) signal transformation of the infarct core, which results in high apparent diffusion coefficient (ADC) values and variable DWI signal intensity, is completed no later than 1 month after onset of ischemia. We observed frequent exceptions to this timeline of change in DWI signal, which led to uncertainties in further clinical patient management. METHODS A prospective single-center study of patients treated with mechanical thrombectomy of a large vessel occlusion in the anterior circulation was conducted. Patients received high-resolution MRI at 3T, including DWI, in the acute post-stroke phase and in the follow-up after 3-12 months. RESULTS Overall, 78 patients (45 men) of mean age 63.6 years were evaluated. We identified persisting or new diffusion restriction in 29 of the 78 patients (37.2%) on follow-up imaging. Diffusion restrictions in a different location from the infarct core, representing new (sub-)acute ischemia, were observed in four patients (5.1%). Smaller areas of persisting diffusion restriction (pDWI lesions with high DWI signal and reduced ADC values) within the former infarct core were observed in 25 patients (32.1%) without clinical evidence of recurrent stroke, but with worse outcome scores at follow-up compared with patients without pDWI lesions. The presence of pDWI lesions is associated with a large primary infarct core (multivariate regression OR 1.03 (95% CI 1.01 to 1.05); p<0.01), mediating the relationship between pDWI lesions and clinical outcome. CONCLUSION Smaller foci of persisting diffusion restriction (pDWI lesions) in the follow-up after endovascular treatment for stroke are frequent and likely represent a slowed ADC signal progression within a formerly large infarct core.
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Affiliation(s)
- Moritz Roman Hernandez Petzsche
- Department of diagnostic and interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of diagnostic and interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Kathleen Bernkopf
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Simone Henze
- Department of diagnostic and interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Maegerlein
- Department of diagnostic and interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dominik Sepp
- Department of diagnostic and interventional Neuroradiology, 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
| | - Silke Wunderlich
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benno Ikenberg
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Maria Teresa Berndt
- Department of diagnostic and interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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22
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Buchner JA, Peeken JC, Etzel L, Ezhov I, Mayinger M, Christ SM, Brunner TB, Wittig A, Menze BH, Zimmer C, Meyer B, Guckenberger M, Andratschke N, El Shafie RA, Debus J, Rogers S, Riesterer O, Schulze K, Feldmann HJ, Blanck O, Zamboglou C, Ferentinos K, Bilger A, Grosu AL, Wolff R, Kirschke JS, Eitz KA, Combs SE, Bernhardt D, Rueckert D, Piraud M, Wiestler B, Kofler F. Identifying core MRI sequences for reliable automatic brain metastasis segmentation. Radiother Oncol 2023; 188:109901. [PMID: 37678623 DOI: 10.1016/j.radonc.2023.109901] [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: 04/27/2023] [Revised: 08/27/2023] [Accepted: 09/01/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation. METHODS We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers. A baseline 3D U-Net with all four sequences and six U-Nets with plausible sequence combinations (T1-CE, T1, T2-FLAIR, T1-CE + T2-FLAIR, T1-CE + T1 + T2-FLAIR, T1-CE + T1) were trained on 239 patients from two centers and subsequently tested on an external cohort of 100 patients from five centers. RESULTS The model based on T1-CE alone achieved the best segmentation performance for BM segmentation with a median Dice similarity coefficient (DSC) of 0.96. Models trained without T1-CE performed worse (T1-only: DSC = 0.70 and T2-FLAIR-only: DSC = 0.73). For edema segmentation, models that included both T1-CE and T2-FLAIR performed best (DSC = 0.93), while the remaining four models without simultaneous inclusion of these both sequences reached a median DSC of 0.81-0.89. CONCLUSIONS A T1-CE-only protocol suffices for the segmentation of BMs. The combination of T1-CE and T2-FLAIR is important for edema segmentation. Missing either T1-CE or T2-FLAIR decreases performance. These findings may improve imaging routines by omitting unnecessary sequences, thus allowing for faster procedures in daily clinical practice while enabling optimal neural network-based target definitions.
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Affiliation(s)
- Josef A Buchner
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
| | - Jan C Peeken
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany; Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Center Munich, Munich, Germany
| | - Lucas Etzel
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Germany; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany
| | - Michael Mayinger
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Sebastian M Christ
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Thomas B Brunner
- Department of Radiation Oncology, University Hospital Magdeburg, Magdeburg, Germany
| | - Andrea Wittig
- Department of Radiotherapy and Radiation Oncology, University Hospital Jena, Friedrich-Schiller University, Jena, Germany
| | - Bjoern H Menze
- Department of Informatics, Technical University of Munich, Munich, Germany; Department of Quantitative Biomedicine, University Hospital and University of Zurich, Zurich, Switzerland
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Nicolaus Andratschke
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Rami A El Shafie
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Heidelberg Institute for Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg, Germany; Department of Radiation Oncology, University Medical Center Göttingen, Göttingen, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Heidelberg Institute for Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg, Germany
| | - Susanne Rogers
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Aarau, Switzerland
| | - Oliver Riesterer
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Aarau, Switzerland
| | - Katrin Schulze
- Department of Radiation Oncology, General Hospital Fulda, Fulda, Germany
| | - Horst J Feldmann
- Department of Radiation Oncology, General Hospital Fulda, Fulda, Germany
| | - Oliver Blanck
- Department of Radiation Oncology, University Medical Center Schleswig Holstein, Kiel, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, University of Freiburg - Medical Center, Freiburg, Germany; German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany; Department of Radiation Oncology, German Oncology Center, European University of Cyprus, Limassol, Cyprus
| | - Konstantinos Ferentinos
- Department of Radiation Oncology, German Oncology Center, European University of Cyprus, Limassol, Cyprus
| | - Angelika Bilger
- Department of Radiation Oncology, University of Freiburg - Medical Center, Freiburg, Germany; German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, University of Freiburg - Medical Center, Freiburg, Germany; German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Robert Wolff
- Saphir Radiosurgery Center Frankfurt and Northern Germany, Guestrow, Germany; Department of Neurosurgery, University Hospital Frankfurt, Frankfurt, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Kerstin A Eitz
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany; Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Center Munich, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany; Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Center Munich, Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Daniel Rueckert
- Institute for Artificial Intelligence and Informatics in Medicine, Technical University of Munich, Munich, Germany
| | - Marie Piraud
- Helmholtz AI, Helmholtz Zentrum Munich, Neuherberg, Germany
| | - Benedikt Wiestler
- TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany; Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Kofler
- Helmholtz AI, Helmholtz Zentrum Munich, Neuherberg, Germany; Department of Informatics, Technical University of Munich, Munich, Germany; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany; Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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23
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Schinz D, Schmitz‐Koep B, Zimmermann J, Brandes E, Tahedl M, Menegaux A, Dukart J, Zimmer C, Wolke D, Daamen M, Boecker H, Bartmann P, Sorg C, Hedderich DM. Indirect evidence for altered dopaminergic neurotransmission in very premature-born adults. Hum Brain Mapp 2023; 44:5125-5138. [PMID: 37608591 PMCID: PMC10502650 DOI: 10.1002/hbm.26451] [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: 12/30/2022] [Revised: 06/23/2023] [Accepted: 07/28/2023] [Indexed: 08/24/2023] Open
Abstract
While animal models indicate altered brain dopaminergic neurotransmission after premature birth, corresponding evidence in humans is scarce due to missing molecular imaging studies. To overcome this limitation, we studied dopaminergic neurotransmission changes in human prematurity indirectly by evaluating the spatial co-localization of regional alterations in blood oxygenation fluctuations with the distribution of adult dopaminergic neurotransmission. The study cohort comprised 99 very premature-born (<32 weeks of gestation and/or birth weight below 1500 g) and 107 full-term born young adults, being assessed by resting-state functional MRI (rs-fMRI) and IQ testing. Normative molecular imaging dopamine neurotransmission maps were derived from independent healthy control groups. We computed the co-localization of local (rs-fMRI) activity alterations in premature-born adults with respect to term-born individuals to different measures of dopaminergic neurotransmission. We performed selectivity analyses regarding other neuromodulatory systems and MRI measures. In addition, we tested if the strength of the co-localization is related to perinatal measures and IQ. We found selectively altered co-localization of rs-fMRI activity in the premature-born cohort with dopamine-2/3-receptor availability in premature-born adults. Alterations were specific for the dopaminergic system but not for the used MRI measure. The strength of the co-localization was negatively correlated with IQ. In line with animal studies, our findings support the notion of altered dopaminergic neurotransmission in prematurity which is associated with cognitive performance.
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Affiliation(s)
- David Schinz
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Benita Schmitz‐Koep
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Elin Brandes
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Marlene Tahedl
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Aurore Menegaux
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Juergen Dukart
- Institute of Neuroscience and MedicineBrain & Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical FacultyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Claus Zimmer
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
| | - Dieter Wolke
- Department of PsychologyUniversity of WarwickCoventryUK
- Warwick Medical SchoolUniversity of WarwickCoventryUK
| | - Marcel Daamen
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
- Department of NeonatologyUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Clinical Functional Imaging Group, Department of Diagnostic and Interventional RadiologyUniversity Hospital BonnBonnGermany
| | - Peter Bartmann
- Department of NeonatologyUniversity Hospital BonnBonnGermany
| | - Christian Sorg
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
- Department of Psychiatry, School of MedicineTechnical University of MunichMunichGermany
| | - Dennis M. Hedderich
- Department of Neuroradiology, School of MedicineTechnical University of MunichMunichGermany
- TUM‐NIC Neuroimaging Center, School of MedicineTechnical University of MunichMunichGermany
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24
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Buchner JA, Kofler F, Mayinger MC, Brunner TB, Wittig A, Menze B, Zimmer C, Meyer B, Guckenberger M, Andratschke N, Shafie RE, Rogers S, Schulze K, Blanck O, Zamboglou C, Grosu A, Combs SE, Bernhardt D, Wiestler B, Peeken JC. What MRI Sequences are Necessary for Automated Neural Network-Based Metastasis Segmentation - An Ablation Study. Int J Radiat Oncol Biol Phys 2023; 117:e704-e705. [PMID: 37786065 DOI: 10.1016/j.ijrobp.2023.06.2195] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Brain metastasis (BM) delineation is a time-consuming process in both daily clinical practice and research. Automated BM segmentation algorithms can be used to assist in this task. Most approaches to brain tumor segmentation, such as algorithms trained on the BraTS challenge, use four magnetic resonance imaging (MRI) sequences as input, making them susceptible to missing or corrupted sequences and increase the number of sequences necessary for MRI RT planning. The goal of this project is to compare neural networks with different combinations of input sequences for the segmentation of the contrast-enhancing metastasis and the surrounding FLAIR hyperintense edema. All models were tested in a multicenter international external test cohort. This allows us to determine which MRI sequences are needed for effective automated segmentations. MATERIALS/METHODS In total, we had T1-weighted sequences without (T1) and with contrast enhancement (T1-CE), T2-weighted sequences (T2), and T2 fluid-attenuated inversion recovery (FLAIR) sequences from 339 patients with at least one brain metastasis from seven centers available. Preprocessing yielded co-registered, skull-stripped sequences with an isotropic resolution of 1 millimeter. The contrast-enhancing metastasis as well as the surrounding FLAIR hyperintense edema were manually segmented to create reference labels. A baseline 3D U-Net with all four sequences as well as six additional U-Nets with different clinically plausible combinations (T1-CE; T1; FLAIR; T1-CE+FLAIR; T1-CE+T1+FLAIR; T1-CE+T1) of input sequences were trained on a cohort of 239 patients from two centers and subsequently tested on an external cohort of 100 patients from the remaining five centers. RESULTS All models that included T1-CE in their selected sequences showed similar performance for metastasis segmentation with a median Dice similarity coefficient (DSC) of 0.93-0.96. T1-CE alone likewise achieved a performance of 0.96 (IQR 0.93-0.97). The model trained with only FLAIR performed worse (DSC = 0.73, IQR 0.54-0.84). For edema segmentation, models that included both T1-CE and FLAIR performed best (median DSC = 0.93), while the remaining four models without simultaneous inclusion of these two sequences (T1-CE; T1; FLAIR; T1-CE+T1) reached a median DSC of 0.81-0.89. CONCLUSION Automatic segmentation of brain metastases with less than four input sequences is feasible with minimal or no loss of quality. A T1-CE-only protocol suffices for metastasis segmentation. In contrast, for edema segmentation, the combination of T1-CE and FLAIR seems to be important. Missing either T1-CE or FLAIR decreases performance. These findings may improve future imaging routines by omitting unnecessary sequences, thus speeding up procedures in daily clinical practice while allowing for optimal neural network-based target definitions.
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Affiliation(s)
- J A Buchner
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - F Kofler
- Helmholtz AI, Helmholtz Zentrum Munich, Munich, Germany; Department of Informatics, Technical University of Munich, Munich, Germany
| | - M C Mayinger
- Department of Radiation Oncology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - T B Brunner
- Medical University of Graz, Dept. of Radiation Oncology, Graz, Austria; Department of Radiation Oncology, University Hospital Magdeburg, Magdeburg, Germany
| | - A Wittig
- Department of Radiotherapy and Radiation Oncology, University Hospital Jena, Friedrich-Schiller University, Jena, Germany
| | - B Menze
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - C Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - B Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - M Guckenberger
- Department of Radiation Oncology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - N Andratschke
- Department of Radiation Oncology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - R El Shafie
- Heidelberg Institute for Radiation Oncology (HIRO), National Center for Radiation Oncology (NCRO), Heidelberg, Germany; Department of Radiation Oncology, University Medical Center Göttingen, Göttingen, Germany
| | - S Rogers
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Aarau, Switzerland
| | - K Schulze
- Department of Radiation Oncology, General Hospital Fulda, Fulda, Germany
| | - O Blanck
- Department of Radiation Oncology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - C Zamboglou
- Department of Radiation Oncology, German Oncology Center, European University of Cyprus, Limassol, Cyprus; Department of Radiation Oncology, University of Freiburg - Medical Center, Freiburg, Germany
| | - A Grosu
- Department of Radiation Oncology, University of Freiburg - Medical Center, Freiburg, Germany; German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - S E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Center Munich, Munich, Germany
| | - D Bernhardt
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, Munich, Germany
| | - B Wiestler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany
| | - J C Peeken
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Center Munich, Munich, Germany
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Waltenberger M, Bernhardt D, Diehl C, Meyer B, Straube C, Wiestler B, Wilkens J, Zimmer C, Combs SE. Hypofractionated Stereotactic Radiotherapy vs. Single Fraction Stereotactic Radiosurgery to the Resection Cavity of Brain Metastases after Surgical Resection (SATURNUS trial): A Prospective, Randomized Phase III Trial. Int J Radiat Oncol Biol Phys 2023; 117:e155. [PMID: 37784743 DOI: 10.1016/j.ijrobp.2023.06.979] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The brain is a common site for metastases. Resection of large or symptomatic metastases is followed by stereotactic radiotherapy to prevent local recurrence. The optimal fractionation scheme is subject of ongoing research. Supported by emerging retrospective data, we hypothesize that hypofractionated stereotactic radiotherapy (HFSRT) is superior to single-fraction stereotactic radiosurgery (SRS) in terms of local control (LC). We designed the SATURNUS trial to prospectively demonstrate the superiority of HFSRT over SRS after resection of brain metastases in terms of LC. MATERIALS/METHODS The SATURNUS trial is a prospective, randomized phase III trial, currently recruiting patients at a single institution. Patients are 1:1 allocated to HFSRT or SRS using permuted block randomization. Affiliation to the treatment arm is solely blinded to the neuroradiologist assessing therapy response. HFSRT will be delivered with 6 - 7 x 5 Gy and SRS with 1 x 12-20 Gy, prescribed to the surrounding isodose, depending on cavity size and proximity to structures at risk. For SRS, doses do not exceed the maximum doses according to RTOG 90-05. Case number calculation was based on own institutional data on HFSRT (mean LC rate of 88% at 12 months) and data from large phase III trials on SRS (pooled mean LC rate of 66% at 12 months). Using a Chi-squared test of equal proportions (odds ratio = 1), setting test significance level (α) to 0.05, and allocating an equal number of patients to both treatment arms, 114 patients are needed to detect the superiority of HFSRT in terms of LC at 12 months (primary endpoint) with a power of at least 80%. Estimating a dropout rate of 10%, the case number was set to 126. The trial was registered with clinicaltrials.gov (NCT05160818). The first patient was enrolled in May 2021 and recruitment is ongoing. Patients with up to three resected brain metastases are considered for study participation. Further eligibility criteria are histologically confirmed solid tumor disease, resection cavity diameter ≤ 4 cm, consent to perform adjuvant radiotherapy by an interdisciplinary tumor board, completed wound healing, resection within the last six weeks at the time of study inclusion, age ≥ 18 years, KPS ≥ 60%, adequate contraceptive measures for fertile women / men and written informed consent. Patients are followed up clinically and with MRI at 6 weeks and 3, 6, 9 and 12 months after treatment. LC is assessed according to RANO-BM. Toxicity (CTCAE v4.03) is assessed as a secondary endpoint. The rather broad dose corridors allowed within the trial do justice to clinical reality, however, may represent a limitation of the trial. They are therefore addressed with a predefined subgroup analysis, as will be cavity size, among others. Participation of further study centers is desired. To the best of our knowledge, the SATURNUS trial is the only randomized phase III trial adequately powered to detect the superiority of HFSRT over SRS with regard to LC for resected brain metastases. RESULTS To be determined. CONCLUSION To be determined.
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Affiliation(s)
- M Waltenberger
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, Munich, Germany
| | - D Bernhardt
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, Munich, Germany
| | - C Diehl
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - B Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | | | - B Wiestler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - J Wilkens
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - C Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - S E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, 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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Demler VF, Sterner EF, Wilson M, Zimmer C, Knolle F. Association between increased anterior cingulate glutamate and psychotic-like experiences, but not autistic traits in healthy volunteers. Sci Rep 2023; 13:12792. [PMID: 37550354 PMCID: PMC10406950 DOI: 10.1038/s41598-023-39881-1] [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: 04/14/2023] [Accepted: 08/01/2023] [Indexed: 08/09/2023] Open
Abstract
Despite many differences, autism spectrum disorder and schizophrenia spectrum disorder share environmental risk factors, genetic predispositions as well as neuronal abnormalities, and show similar cognitive deficits in working memory, perspective taking, or response inhibition. These shared abnormalities are already present in subclinical traits of these disorders. The literature proposes that changes in the inhibitory GABAergic and the excitatory glutamatergic system could explain underlying neuronal commonalities and differences. Using magnetic resonance spectroscopy (1H-MRS), we investigated the associations between glutamate concentrations in the anterior cingulate cortex (ACC), the left/right putamen, and left/right dorsolateral prefrontal cortex and psychotic-like experiences (Schizotypal Personality Questionnaire) and autistic traits (Autism Spectrum Quotient) in 53 healthy individuals (26 women). To investigate the contributions of glutamate concentrations in different cortical regions to symptom expression and their interactions, we used linear regression analyses. We found that only glutamate concentration in the ACC predicted psychotic-like experiences, but not autistic traits. Supporting this finding, a binomial logistic regression predicting median-split high and low risk groups for psychotic-like experiences revealed ACC glutamate levels as a significant predictor for group membership. Taken together, this study provides evidence that glutamate levels in the ACC are specifically linked to the expression of psychotic-like experiences, and may be a potential candidate in identifying early risk individuals prone to developing psychotic-like experiences.
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Affiliation(s)
- Verena F Demler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany
| | - Elisabeth F Sterner
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany
| | - Franziska Knolle
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany.
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
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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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Waltenberger M, Bernhardt D, Diehl C, Gempt J, Meyer B, Straube C, Wiestler B, Wilkens JJ, Zimmer C, Combs SE. Hypofractionated stereotactic radiotherapy (HFSRT) versus single fraction stereotactic radiosurgery (SRS) to the resection cavity of brain metastases after surgical resection (SATURNUS): study protocol for a randomized phase III trial. BMC Cancer 2023; 23:709. [PMID: 37516835 PMCID: PMC10385881 DOI: 10.1186/s12885-023-11202-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 07/19/2023] [Indexed: 07/31/2023] Open
Abstract
BACKGROUND The brain is a common site for cancer metastases. In case of large and/or symptomatic brain metastases, neurosurgical resection is performed. Adjuvant radiotherapy is a standard procedure to minimize the risk of local recurrence and is increasingly performed as local stereotactic radiotherapy to the resection cavity. Both hypofractionated stereotactic radiotherapy (HFSRT) and single fraction stereotactic radiosurgery (SRS) can be applied in this case. Although adjuvant stereotactic radiotherapy to the resection cavity is widely used in clinical routine and recommended in international guidelines, the optimal fractionation scheme still remains unclear. The SATURNUS trial prospectively compares adjuvant HFSRT with SRS and seeks to detect the superiority of HFSRT over SRS in terms of local tumor control. METHODS In this single center two-armed randomized phase III trial, adjuvant radiotherapy to the resection cavity of brain metastases with HFSRT (6 - 7 × 5 Gy prescribed to the surrounding isodose) is compared to SRS (1 × 12-20 Gy prescribed to the surrounding isodose). Patients are randomized 1:1 into the two different treatment arms. The primary endpoint of the trial is local control at the resected site at 12 months. The trial is based on the hypothesis that HFSRT is superior to SRS in terms of local tumor control. DISCUSSION Although adjuvant stereotactic radiotherapy after resection of brain metastases is considered standard of care treatment, there is a need for further prospective research to determine the optimal fractionation scheme. To the best of our knowledge, the SATURNUS study is the only randomized phase III study comparing different regimes of postoperative stereotactic radiotherapy to the resection cavity adequately powered to detect the superiority of HFSRT regarding local control. TRIAL REGISTRATION The study was retrospectively registered with ClinicalTrials.gov, number NCT05160818, on December 16, 2021. The trial registry record is available on https://clinicaltrials.gov/study/NCT05160818 . The presented protocol refers to version V1.3 from March 21, 2021.
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Affiliation(s)
- Maria Waltenberger
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany.
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christian Diehl
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | | | - Benedikt Wiestler
- Institute of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Jan J Wilkens
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Claus Zimmer
- Institute of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Straße 22, 81675, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Institute of Radiation Medicine (IRM), Helmholtz Zentrum, Ingolstädter Landstraße 1, 85764, Neuherberg, 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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Schlaeger S, Shit S, Eichinger P, Hamann M, Opfer R, Krüger J, Dieckmeyer M, Schön S, Mühlau M, Zimmer C, Kirschke JS, Wiestler B, Hedderich DM. AI-based detection of contrast-enhancing MRI lesions in patients with multiple sclerosis. Insights Imaging 2023; 14:123. [PMID: 37454342 DOI: 10.1186/s13244-023-01460-3] [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: 01/18/2023] [Accepted: 06/03/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE lesion detection are emerging; however, independent validation of artificial intelligence (AI) tools in the clinical routine is still rare. METHODS A three-dimensional convolutional neural network for CE lesion segmentation was trained externally on 1488 datasets of 934 MS patients from 81 scanners using concatenated information from FLAIR and T1-weighted post-contrast imaging. This externally trained model was tested on an independent dataset comprising 504 T1-weighted post-contrast and FLAIR image datasets of MS patients from clinical routine. Two neuroradiologists (R1, R2) labeled CE lesions for gold standard definition in the clinical test dataset. The algorithmic output was evaluated on both patient- and lesion-level. RESULTS On a patient-level, recall, specificity, precision, and accuracy of the AI tool to predict patients with CE lesions were 0.75, 0.99, 0.91, and 0.96. The agreement between the AI tool and both readers was within the range of inter-rater agreement (Cohen's kappa; AI vs. R1: 0.69; AI vs. R2: 0.76; R1 vs. R2: 0.76). On a lesion-level, false negative lesions were predominately found in infratentorial location, significantly smaller, and at lower contrast than true positive lesions (p < 0.05). CONCLUSIONS AI-based identification of CE lesions on brain MRI is feasible, approaching human reader performance in independent clinical data and might be of help as a second reader in the neuroradiological assessment of active inflammation in MS patients. CRITICAL RELEVANCE STATEMENT Al-based detection of contrast-enhancing multiple sclerosis lesions approaches human reader performance, but careful visual inspection is still needed, especially for infratentorial, small and low-contrast lesions.
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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.
| | - Suprosanna Shit
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Paul Eichinger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | | | | | | | - Michael Dieckmeyer
- 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 Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital, University of Bern, Bern, Switzerland
| | - Simon Schön
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
- DIE RADIOLOGIE, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, 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, Ismaninger Str. 22, 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
| | - 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
| | - Dennis M Hedderich
- 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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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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Finck T, Sperl P, Hernandez-Petzsche M, Boeckh-Behrens T, Maegerlein C, Wunderlich S, Zimmer C, Kirschke J, Berndt M. Inflammation in stroke: initial CRP levels can predict poor outcomes in endovascularly treated stroke patients. Front Neurol 2023; 14:1167549. [PMID: 37360331 PMCID: PMC10289003 DOI: 10.3389/fneur.2023.1167549] [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: 02/16/2023] [Accepted: 05/08/2023] [Indexed: 06/28/2023] Open
Abstract
Background and purpose Inflammation has been linked to poor prognoses in cardio- and cerebrovascular conditions. As it is known to increase after ischemia, C-reactive protein (CRP) may serve as a surrogate for systemic inflammation and thus be a hallmark of increased tissue vulnerability. The question arises whether CRP in the acute phase of ischemic stroke, prior to mechanical thrombectomy (MT), might help predict outcomes. Materials and methods A single-center collective of patients with large-vessel occlusion, who were treated via MT, was analyzed in this observational case-control study. Univariate and multivariate models were designed to test the prognostic value of inflammatory markers (CRP and leukocytosis) in predicting clinical outcomes (modified Rankin score >2) and all-cause mortality 90 days after MT. Results A total of 676 ischemic stroke patients treated with MT were included. Of these, 313 (46.3%) showed elevated CRP levels (≥5 mg/l) on admission. Poor clinical outcome and mortality at 90 days occurred in 113 (16.7%) and 335 (49.6%) patients and significantly more frequently when initial CRP levels were elevated [213 (64.5%) vs. 122 (42.1%), p < 0.0001, and 79 (25.2%) vs. 34 (9.4%), p < 0.0001, respectively]. CRP levels were highly predictive for impaired outcomes, especially in patients with atrial fibrillation, in both univariate and multivariate models. Interestingly, patients with initially elevated CRP levels also showed more pronounced increases in CRP post-MT. Conclusion Poor outcome and death occur significantly more often in stroke patients with elevated CRP levels before MT. Our findings suggest that stroke patients with atrial fibrillation and elevated inflammatory markers are of particular risk for poor outcomes.
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Affiliation(s)
- Tom Finck
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Philipp Sperl
- 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
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christian Maegerlein
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Silke Wunderlich
- Department of Neurology, 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
| | - Jan Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maria Berndt
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
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Schlaeger S, Li HB, Baum T, Zimmer C, Moosbauer J, Byas S, Mühlau M, Wiestler B, Finck T. Longitudinal Assessment of Multiple Sclerosis Lesion Load With Synthetic Magnetic Resonance Imaging-A Multicenter Validation Study. Invest Radiol 2023; 58:320-326. [PMID: 36730638 DOI: 10.1097/rli.0000000000000938] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
INTRODUCTION Double inversion recovery (DIR) has been validated as a sensitive magnetic resonance imaging (MRI) contrast in multiple sclerosis (MS). Deep learning techniques can use basic input data to generate synthetic DIR (synthDIR) images that are on par with their acquired counterparts. As assessment of longitudinal MRI data is paramount in MS diagnostics, our study's purpose is to evaluate the utility of synthDIR longitudinal subtraction imaging for detection of disease progression in a multicenter data set of MS patients. METHODS We implemented a previously established generative adversarial network to synthesize DIR from input T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences for 214 MRI data sets from 74 patients and 5 different centers. One hundred and forty longitudinal subtraction maps of consecutive scans (follow-up scan-preceding scan) were generated for both acquired FLAIR and synthDIR. Two readers, blinded to the image origin, independently quantified newly formed lesions on the FLAIR and synthDIR subtraction maps, grouped into specific locations as outlined in the McDonald criteria. RESULTS Both readers detected significantly more newly formed MS-specific lesions in the longitudinal subtractions of synthDIR compared with acquired FLAIR (R1: 3.27 ± 0.60 vs 2.50 ± 0.69 [ P = 0.0016]; R2: 3.31 ± 0.81 vs 2.53 ± 0.72 [ P < 0.0001]). Relative gains in detectability were most pronounced in juxtacortical lesions (36% relative gain in lesion counts-pooled for both readers). In 5% of the scans, synthDIR subtraction maps helped to identify a disease progression missed on FLAIR subtraction maps. CONCLUSIONS Generative adversarial networks can generate high-contrast DIR images that may improve the longitudinal follow-up assessment in MS patients compared with standard sequences. By detecting more newly formed MS lesions and increasing the rates of detected disease activity, our methodology promises to improve clinical decision-making.
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Affiliation(s)
- Sarah Schlaeger
- From the Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar
| | | | - Thomas Baum
- From the Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar
| | - Claus Zimmer
- From the Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar
| | | | | | - Mark Mühlau
- Department of Neurology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- From the Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar
| | - Tom Finck
- From the Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum Rechts der Isar
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Schmitz-Koep B, Menegaux A, Gaser C, Brandes E, Schinz D, Thalhammer M, Daamen M, Boecker H, Zimmer C, Priller J, Wolke D, Bartmann P, Sorg C, Hedderich DM. Altered Gray Matter Cortical and Subcortical T1-Weighted/T2-Weighted Ratio in Premature-Born Adults. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:495-504. [PMID: 35276405 DOI: 10.1016/j.bpsc.2022.02.013] [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: 10/05/2021] [Revised: 02/16/2022] [Accepted: 02/28/2022] [Indexed: 05/09/2023]
Abstract
BACKGROUND Microscopic studies in newborns and animal models indicate impaired myelination after premature birth, particularly for cortical myelination; however, it remains unclear whether such myelination impairments last into adulthood and, if so, are relevant for impaired cognitive performance. It has been suggested that the ratio of T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging signal intensity (T1w/T2w ratio) is a proxy for myelin content. We hypothesized altered gray matter (GM) T1w/T2w ratio in premature-born adults, which is associated with lower cognitive performance after premature birth. METHODS We analyzed GM T1w/T2w ratio in 101 adults born very premature (VP) and/or at very low birth weight (VLBW) (<32 weeks of gestation and/or birth weight <1500 g) and 109 full-term control subjects at 26 years of age, controlled for voxelwise volume alterations. Cognitive performance was assessed by verbal, performance, and full scale IQ using the Wechsler Adult Intelligence Scale. RESULTS Significantly higher T1w/T2w ratio in VP/VLBW subjects was found bilaterally in widespread cortical areas, particularly in frontal, parietal, and temporal cortices, and in putamen and pallidum. In these areas, T1w/T2w ratio was not related to birth variables, such as gestational age, or IQ scores. In contrast, significantly lower T1w/T2w ratio in VP/VLBW subjects was found in bilateral clusters in superior temporal gyrus, which was associated with birth weight in the VP/VLBW group. Furthermore, lower T1w/T2w ratio in left superior temporal gyrus was associated with lower full scale and verbal IQ. CONCLUSIONS Results demonstrate GM T1w/T2w ratio alterations in premature-born adults and suggest altered GM myelination development after premature birth with lasting and functionally relevant effects into early adulthood.
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Affiliation(s)
- Benita Schmitz-Koep
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Aurore Menegaux
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Departments of Psychiatry, University Hospital Jena, Jena, Germany; Departments of Neurology, University Hospital Jena, Jena, Germany
| | - Elin Brandes
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - David Schinz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Melissa Thalhammer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marcel Daamen
- Functional Neuroimaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany; Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Henning Boecker
- Functional Neuroimaging Group, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Josef Priller
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany; Department of Neuropsychiatry, Charité - Universitätsmedizin Berlin and Deutsches Zentrum für Neurodegenerative Erkrankungen e.V., Berlin, Germany; UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Dieter Wolke
- Department of Psychology, University of Warwick, Coventry, United Kingdom; Warwick Medical School, University of Warwick, Coventry, United Kingdom
| | - Peter Bartmann
- Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Christian Sorg
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany; Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dennis M Hedderich
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany; Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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Schwarting J, Rühling S, Bodden J, Schwarting SK, Zimmer C, Mehrens D, Kirschke JS, Kunz WG, Boeckh-Behrens T, Froelich MF. Endovascular thrombectomy is cost-effective in acute basilar artery occlusion stroke. Front Neurol 2023; 14:1185304. [PMID: 37181579 PMCID: PMC10169675 DOI: 10.3389/fneur.2023.1185304] [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: 03/13/2023] [Accepted: 04/10/2023] [Indexed: 05/16/2023] Open
Abstract
Objective Endovascular thrombectomy is a long-established therapy for acute basilar artery occlusion (aBAO). Unlike for anterior circulation stroke, cost-effectiveness of endovascular treatment has not been evaluated and is urgently needed to calculate expected health benefits and financial rewards. The aim of this study was therefore to simulate patient-level costs, analyze the economic potential of endovascular thrombectomy in patients with acute basilar artery occlusion (aBAO), and identify major determinants of cost-effectiveness. Methods A Markov model was developed to compare outcome and cost parameters between patients treated by endovascular thrombectomy and patients treated by best medical care, based on four recent prospective clinical trials (ATTENTION, BAOCHE, BASICS, and BEST). Treatment outcomes were derived from the most recent literature. Uncertainty was addressed by deterministic and probabilistic sensitivity analyses. Willingness to pay per QALY thresholds were set at 1x gross domestic product per capita, as recommended by the World Health Organization. Results Endovascular treatment of acute aBAO stroke yielded an incremental gain of 1.71 quality-adjusted life-years per procedure with an incremental cost-effectiveness ratio of $7,596 per QALY. This was substantially lower than the Willingness to pay of $63,593 per QALY. Lifetime costs were most sensitive to costs of the endovascular procedure. Conclusion Endovascular treatment is cost-effective in patients with aBAO stroke.
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Affiliation(s)
- Julian Schwarting
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Sebastian Rühling
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Jannis Bodden
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | | | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Dirk Mehrens
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Wolfgang G. Kunz
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Matthias F. Froelich
- Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany
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Griessmair M, Delbridge C, Ziegenfeuter J, Bernhardt D, Gempt J, Schmidt-Graf F, Kertels O, Thomas M, Meyer HS, Zimmer C, Meyer B, Combs SE, Yakushev I, Wiestler B, Metz MC. Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas. Cancers (Basel) 2023; 15:cancers15082355. [PMID: 37190283 DOI: 10.3390/cancers15082355] [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: 01/22/2023] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. MATERIALS AND METHODS We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4. RESULTS Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA). CONCLUSIONS This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.
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Affiliation(s)
- Michael Griessmair
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Claire Delbridge
- Department of Pathology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Julian Ziegenfeuter
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | | | - Olivia Kertels
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Marie Thomas
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Hanno S Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- TranslaTUM, TU Munich, 81675 Munich, Germany
| | - Marie-Christin Metz
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
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Sepp D, Hernandez Petzsche MR, Zarth T, Wunderlich S, Ikenberg B, Maegerlein C, Zimmer C, Berndt MT, Boeckh-Behrens T, Kirschke JS. Mechanical thrombectomy of distal cerebral vessel occlusions of the anterior circulation. Sci Rep 2023; 13:5730. [PMID: 37029202 PMCID: PMC10082188 DOI: 10.1038/s41598-023-32634-0] [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: 09/14/2022] [Accepted: 03/30/2023] [Indexed: 04/09/2023] Open
Abstract
Mechanical thrombectomy (MT) is frequently performed for distal medium vessel occlusions (DMVO) of the anterior circulation in acute stroke patients. However, evidence for its clinical benefit remains scarce. In this study, we aim to investigate clinical course and safety outcomes of MT in comparison to standard medical therapy (SMT) in DMVO. This single-center retrospective observational study included 138 consecutive patients treated for DMVO of the anterior circulation between 2015 and 2021. To reduce the risk of selection bias, propensity score matching (PSM) of patients with MT versus SMT was performed for the covariates NIHSS and mRS at admission. Out of all 138 patients, 48 (34.8%) received MT and 90 (65.2%) received SMT only. Overall, patients treated with MT showed significantly higher NIHSS and mRS scores at admission. Post 1:1 PSM, there was a trend toward a better NIHSS improvement in patients with MT (median 4 vs. 1, P = 0.1). No significant differences were observed in the occurrence of symptomatic intracranial hemorrhage or mortality between the groups before and after PSM. A subgroup analysis showed significantly higher NIHSS improvement (median 5 versus 1, P = 0.01) for patients with successful MT (≥ mTICI 2b). Mechanical thrombectomy for distal medium vessel occlusions (DMVO) in the anterior circulation appeared safe and feasible. Successful recanalization was associated with clinical improvement. Larger, multi-center, randomized-controlled trials are required to corroborate these findings.
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Affiliation(s)
- Dominik Sepp
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany.
| | - Moritz Roman Hernandez Petzsche
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Teresa Zarth
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Silke Wunderlich
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Straße 22, 81675, München, Germany
| | - Benno Ikenberg
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Straße 22, 81675, München, Germany
| | - Christian Maegerlein
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Maria Teresa Berndt
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
| | - Jan Stefan Kirschke
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, München, Germany
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Schinz D, Zimmermann T, Göttler J, Sepp D, Zimmer C, Boeckh-Behrens T, Kirschke JS, Kreiser K, Liebl H. Incidence, Clinical Significance, and Longitudinal Signal Characteristics of Ischemic Lesions Related to Diagnostic Cerebral Catheter Angiography. Cardiovasc Intervent Radiol 2023:10.1007/s00270-023-03415-z. [PMID: 36991095 PMCID: PMC10322964 DOI: 10.1007/s00270-023-03415-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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 03/06/2023] [Indexed: 03/31/2023]
Abstract
PURPOSE Cerebral DSA is a routine procedure with few complications. However, it is associated with presumably clinically inapparent lesions detectable on diffusion-weighted MRI imaging (DWI lesions). However, there are insufficient data regarding incidence, etiology, clinical relevance, and longitudinal development of these lesions. This study prospectively evaluated subjects undergoing elective diagnostic cerebral DSA for the occurrence of DWI lesions, potentially associated clinical symptoms and risk factors, and longitudinally monitored the lesions using state-of-the-art MRI. MATERIALS AND METHODS Eighty-two subjects were examined by high-resolution MRI within 24 h after elective diagnostic DSA and lesion occurrence was qualitatively and quantitatively evaluated. Subjects' neurological status was assessed before and after DSA by clinical neurological examination and a perceived deficit questionnaire. Patient-related risk factors and procedural DSA data were documented. Subjects with lesions received a follow-up MRI and were questioned for neurological deficits after a median of 5.1 months. RESULTS After DSA, 23(28%) subjects had a total of 54 DWI lesions. Significantly associated risk factors were number of vessels probed, intervention time, age, arterial hypertension, visible calcified plaques, and less examiner experience. Twenty percent of baseline lesions converted to persistent FLAIR lesions at follow-up. After DSA, none of the subjects had a clinically apparent neurological deficit. Self-perceived deficits were nonsignificantly higher at follow-up. CONCLUSION Cerebral DSA is associated with a considerable number of postinterventional lesions, some persisting as scars in brain tissue. Presumably because of the small lesion size and inconsistent location, no clinically apparent neurological deficits have been observed. However, subtle self-perceived changes may occur. Therefore, special attention is needed to minimize avoidable risk factors.
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Affiliation(s)
- David Schinz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany.
| | - Thomas Zimmermann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Jens Göttler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Dominik Sepp
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Jan S Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
| | - Kornelia Kreiser
- Department of Radiology/Neuroradiology, RKU, Universitäts- und Rehabilitationskliniken Ulm, gGmbH, Oberer Eselsberg 45, 89081, Ulm, Germany
| | - Hans Liebl
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der isar, Technical University of Munich, Ismaninger Street 22, 81675, Munich, Germany
- Department of Radiology/Neuroradiology, BGU, Berufsgenossenschaftliche Unfallklinik, Murnau, Professor-Kuentscher-Straße 8, 82418, Murnau Am Staffelsee, Germany
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41
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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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44
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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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Sepp D, Berndt M, Mönch S, Ikenberg B, Wunderlich S, Maegerlein C, Zimmer C, Boeckh-Behrens T, Friedrich B. Outcome and risk of hemorrhage in patients with tandem lesions after endovascular treatment: A propensity score-matched case-control study. Heliyon 2023; 9:e14508. [PMID: 36942245 PMCID: PMC10024127 DOI: 10.1016/j.heliyon.2023.e14508] [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: 09/09/2022] [Revised: 02/26/2023] [Accepted: 03/08/2023] [Indexed: 03/16/2023] Open
Abstract
Objectives Endovascular treatment of acute stroke patients with large vessel occlusions is well established. But tandem lesions of the internal carotid artery and the intracranial anterior circulation remain a challenge regarding the technical conditions and the putative higher risk of hemorrhage due to often required antiplatelet therapy.This study aims to evaluate the clinical outcome and the risk of hemorrhage after endovascular treatment of tandem lesions, with special regard to the periprocedural antiplatelet regimen. Materials and Methods In this retrospective study, we included 63 consecutive stroke patients with endovascular treated tandem lesions. One hundred eleven patients with a solitary intracranial occlusion were matched using a "propensity score-matched analysis" with the covariates sex, age, wake-up stroke, iv-thrombolysis and NIHSS. Results Rates of successful recanalization (mTICI 2b/3) and periprocedural complications were equal in both groups (P = 0.19; P = 0.35). The rate of good clinical outcome (mRS≤2) was similar, and the incidence of symptomatic hemorrhages was not significantly different (7.9% tandem lesions vs. 5.4% isolated intracranial occlusion, P = 0.51). Even intensified antiplatelet therapy in patients with tandem lesions did not increase the rate of symptomatic intracranial hemorrhages (P = 0.87). Conclusions Clinical outcome and symptomatic intracranial hemorrhages did not differ significantly between endovascular treated patients with tandem lesions and matched patients with solitary intracranial occlusions, regardless of the antiplatelet regimen. Therefore, the complex technical requirements for recanalization of a tandem lesion and the putative higher risk should not result in reluctant treatment that would decrease the chance of a good clinical outcome.
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Affiliation(s)
- Dominik Sepp
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Corresponding author. Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany.
| | - Maria Berndt
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sebastian Mönch
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benno Ikenberg
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Silke Wunderlich
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Maegerlein
- Department of Diagnostic and Interventional Neuroradiology, 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
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benjamin Friedrich
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, 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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47
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Wuschek A, Bussas M, El Husseini M, Harabacz L, Pineker V, Pongratz V, Berthele A, Riederer I, Zimmer C, Hemmer B, Kirschke JS, Mühlau M. Somatosensory evoked potentials and magnetic resonance imaging of the central nervous system in early multiple sclerosis. J Neurol 2023; 270:824-830. [PMID: 36205793 PMCID: PMC9886619 DOI: 10.1007/s00415-022-11407-1] [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: 05/31/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Somatosensory evoked potentials (SSEP) are still broadly used, although not explicitly recommended, for the diagnostic work-up of suspected multiple sclerosis (MS). OBJECTIVE To relate disability, SSEP, and lesions on T2-weighted magnetic resonance imaging (MRI) in patients with early MS. METHODS In this monocentric retrospective study, we analyzed a cohort of patients with relapsing-remitting MS or clinically isolated syndrome, with a maximum disease duration of two years, as well as with available data on the score at the expanded disability status scale (EDSS), on SSEP, on whole spinal cord (SC) MRI, and on brain MRI. RESULTS Complete data of 161 patients were available. Tibial nerve SSEP (tSSEP) were less frequently abnormal than SC MRI (22% vs. 68%, p < 0.001). However, higher EDSS scores were significantly associated with abnormal tSSEP (median, 2.0 vs. 1.0; p = 0.001) but not with abnormal SC MRI (i.e., at least one lesion; median, 1.5 vs. 1.5; p = 0.7). Of the 35 patients with abnormal tSSEP, 32 had lesions on SC MRI, and 2 had corresponding lesions on brain MRI. CONCLUSION Compared to tSSEP, SC MRI is the more sensitive diagnostic biomarker regarding SC involvement. In early MS, lesions as detectable by T2-weighted MRI are the main driver of abnormal tSSEP. However, tSSEP were more closely associated with disability, which is compatible with a potential role of tSSEP as prognostic biomarker in complementation of MRI.
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Affiliation(s)
- Alexander Wuschek
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.,TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Matthias Bussas
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.,TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Malek El Husseini
- Dept. of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Laura Harabacz
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Viktor Pineker
- Dept. of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.,TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Isabelle Riederer
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Dept. of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Dept. of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jan S Kirschke
- Dept. of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. .,TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
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48
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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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Feil K, Berndt MT, Wunderlich S, Maegerlein C, Bernkopf K, Zimmermann H, Herzberg M, Tiedt S, Küpper C, Wischmann J, Schönecker S, Dimitriadis K, Liebig T, Dieterich M, Zimmer C, Kellert L, Boeckh-Behrens T, Boeckh-Behrens T, Wunderlich S, Ludolph A, Henn KH, Reich A, Nikoubashman O, Wiesmann M, Ernemann U, Poli S, Nolte CH, Siebert E, Zweynert S, Bohner G, Solymosi L, Petzold G, Pfeilschifter W, Keil F, Röther J, Eckert B, Berrouschot J, Bormann A, Alegiani A, Fiehler J, Gerloff C, Thomalla G, Thonke S, Bangard C, Kraemer C, Dichgans M, Psychogios M, Liman J, Petersen M, Stögbauer F, Kraft P, Pham M, Braun M, Hamann GF, Roth C, Gröschel K, Uphaus T, Limmroth V. Endovascular thrombectomy for basilar artery occlusion stroke: Analysis of the German Stroke Registry-Endovascular Treatment. Eur J Neurol 2023; 30:1293-1302. [PMID: 36692229 DOI: 10.1111/ene.15694] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [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: 12/06/2022] [Revised: 01/05/2023] [Accepted: 01/09/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND AND PURPOSE Acute ischemic stroke due to basilar artery occlusion (BAO) causes the most severe strokes and has a poor prognosis. Data regarding efficacy of endovascular thrombectomy in BAO are sparse. Therefore, in this study, we performed an analysis of the therapy of patients with BAO in routine clinical practice. METHODS Patients enrolled between June 2015 and December 2019 in the German Stroke Registry-Endovascular Treatment (GSR-ET) were analyzed. Primary outcomes were successful reperfusion (modified Thrombolysis in Cerebral Infarction [mTICI] score of 2b-3), substantial neurological improvement (≥8-point National Institute of Health Stroke Scale [NIHSS] score reduction from admission to discharge or NIHSS score at discharge ≤1), and good functional outcome at 3 months (modified Rankin Scale [mRS] score of 0-2). RESULTS Out of 6635 GSR-ET patients, 640 (9.6%) patients (age 72.2 ± 13.3, 43.3% female) experienced BAO (median [interquartile range] NIHSS score 17 [8, 27]). Successful reperfusion was achieved in 88.4%. Substantial neurological improvement at discharge was reached by 45.5%. At 3-month follow-up, good clinical outcome was observed in 31.1% of patients and the mortality rate was 39.2%. Analysis of mTICI3 versus mTICI2b groups showed considerable better outcome in those with mTICI3 (38.9% vs. 24.4%; p = 0.005). The strongest predictors of good functional outcome were intravenous thrombolysis (IVT) treatment (odds ratio [OR] 3.04, 95% confidence interval [CI] 1.76-5.23) and successful reperfusion (OR 4.92, 95% CI 1.15-21.11), while the effect of time between symptom onset and reperfusion seemed to be small. CONCLUSIONS Acute reperfusion strategies in BAO are common in daily practice and can achieve good rates of successful reperfusion, neurological improvement and good functional outcome. Our data suggest that, in addition to IVT treatment, successful and, in particular, complete reperfusion (mTICI3) strongly predicts good outcome, while time from symptom onset seemed to have a lower impact.
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Affiliation(s)
- Katharina Feil
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany.,Department of Neurology and Stroke, Eberhard-Karls University Tübingen/Universitätsklinikum Tübingen (UKT), Tübingen, Germany
| | - Maria Teresa Berndt
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Silke Wunderlich
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Maegerlein
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Kathleen Bernkopf
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | | | - Moriz Herzberg
- Institute of Neuroradiology, LMU, Munich, Germany.,Department of Radiology, University Hospital, Würzburg, Germany
| | - Steffen Tiedt
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Clemens Küpper
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany
| | - Johannes Wischmann
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany
| | - Sonja Schönecker
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany
| | - Konstantin Dimitriadis
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | | | - Marianne Dieterich
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Vertigo and Balance Disorders, LMU, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Lars Kellert
- Department of Neurology, Ludwig Maximilians Universität (LMU), Munich, Germany
| | - Tobias Boeckh-Behrens
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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Gleißner C, Kaczmarz S, Kufer J, Schmitzer L, Kallmayer M, Zimmer C, Wiestler B, Preibisch C, Göttler J. Hemodynamic MRI parameters to predict asymptomatic unilateral carotid artery stenosis with random forest machine learning. Front Neuroimaging 2023; 1:1056503. [PMID: 37555162 PMCID: PMC10406220 DOI: 10.3389/fnimg.2022.1056503] [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] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/20/2022] [Indexed: 08/10/2023]
Abstract
BACKGROUND Internal carotid artery stenosis (ICAS) can cause stroke and cognitive decline. Associated hemodynamic impairments, which are most pronounced within individual watershed areas (iWSA) between vascular territories, can be assessed with hemodynamic-oxygenation-sensitive MRI and may help to detect severely affected patients. We aimed to identify the most sensitive parameters and volumes of interest (VOI) to predict high-grade ICAS with random forest machine learning. We hypothesized an increased predictive ability considering iWSAs and a decreased cognitive performance in correctly classified patients. MATERIALS AND METHODS Twenty-four patients with asymptomatic, unilateral, high-grade carotid artery stenosis and 24 age-matched healthy controls underwent MRI comprising pseudo-continuous arterial spin labeling (pCASL), breath-holding functional MRI (BH-fMRI), dynamic susceptibility contrast (DSC), T2 and T2* mapping, MPRAGE and FLAIR. Quantitative maps of eight perfusion, oxygenation and microvascular parameters were obtained. Mean values of respective parameters within and outside of iWSAs split into gray (GM) and white matter (WM) were calculated for both hemispheres and for interhemispheric differences resulting in 96 features. Random forest classifiers were trained on whole GM/WM VOIs, VOIs considering iWSAs and with additional feature selection, respectively. RESULTS The most sensitive features in decreasing order were time-to-peak (TTP), cerebral blood flow (CBF) and cerebral vascular reactivity (CVR), all of these inside of iWSAs. Applying iWSAs combined with feature selection yielded significantly higher receiver operating characteristics areas under the curve (AUC) than whole GM/WM VOIs (AUC: 0.84 vs. 0.90, p = 0.039). Correctly predicted patients presented with worse cognitive performances than frequently misclassified patients (Trail-making-test B: 152.5s vs. 94.4s, p = 0.034). CONCLUSION Random forest classifiers trained on multiparametric MRI data allow identification of the most relevant parameters and VOIs to predict ICAS, which may improve personalized treatments.
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Affiliation(s)
- Carina Gleißner
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Stephan Kaczmarz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- Philips GmbH Market DACH, Hamburg, Germany
- TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jan Kufer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Lena Schmitzer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Michael Kallmayer
- Department of Vascular and Endovascular Surgery, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christine Preibisch
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Clinic for Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jens Göttler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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