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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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Moors S, Nakhostin D, Ilchenko D, Kulcsar Z, Starkey J, Winklhofer S, Ineichen BV. Cytotoxic lesions of the corpus callosum: a systematic review. Eur Radiol 2024; 34:4628-4637. [PMID: 38147170 PMCID: PMC11213749 DOI: 10.1007/s00330-023-10524-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/07/2023] [Accepted: 11/25/2023] [Indexed: 12/27/2023]
Abstract
OBJECTIVES Cytotoxic lesions of the corpus callosum (CLOCC) are a common magnetic resonance imaging (MRI) finding associated with various systemic diseases including COVID-19. Although an increasing number of such cases is reported in the literature, there is a lack of systematic evidence summarizing the etiology and neuroimaging findings of these lesions. Thus, the aim of this systematic review was to synthesize the applied nomenclature, neuroimaging and clinical features, and differential diagnoses as well as associated disease entities of CLOCC. MATERIALS AND METHODS A comprehensive literature search in three biomedical databases identified 441 references, out of which 324 were eligible for a narrative summary including a total of 1353 patients. RESULTS Our PRISMA-conform systematic review identifies a broad panel of disease entities which are associated with CLOCC, among them toxic/drug-treatment-associated, infectious (viral, bacterial), vascular, metabolic, traumatic, and neoplastic entities in both adult and pediatric individuals. On MRI, CLOCC show typical high T2 signal, low T1 signal, restricted diffusion, and lack of contrast enhancement. The majority of the lesions were reversible within the follow-up period (median follow-up 3 weeks). Interestingly, even though CLOCC were mostly associated with symptoms of the underlying disease, in exceptional cases, CLOCC were associated with callosal neurological symptoms. Of note, employed nomenclature for CLOCC was highly inconsistent. CONCLUSIONS Our study provides high-level evidence for clinical and imaging features of CLOCC as well as associated disease entities. CLINICAL RELEVANCE STATEMENT Our study provides high-level evidence on MRI features of CLOCC as well as a comprehensive list of disease entities potentially associated with CLOCC. Together, this will facilitate rigorous diagnostic workup of suspected CLOCC cases. KEY POINTS • Cytotoxic lesions of the corpus callosum (CLOCC) are a frequent MRI feature associated with various systemic diseases. • Cytotoxic lesions of the corpus callosum show a highly homogenous MRI presentation and temporal dynamics. • This comprehensive overview will benefit (neuro)radiologists during diagnostic workup.
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Affiliation(s)
- Selina Moors
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland
| | - Dominik Nakhostin
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland
| | - Dariya Ilchenko
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland
| | - Jay Starkey
- Department of Radiology, Oregon Health & Science University, Portland, OR, USA
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland
| | - Benjamin V Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital of Zurich, Zurich, Switzerland.
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland.
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Moura J, Granziera C, Marta M, Silva AM. Emerging imaging markers in radiologically isolated syndrome: implications for earlier treatment initiation. Neurol Sci 2024; 45:3061-3068. [PMID: 38374458 DOI: 10.1007/s10072-024-07402-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/13/2024] [Indexed: 02/21/2024]
Abstract
The presence of central nervous system lesions fulfilling the criteria of dissemination in space and time on MRI leads to the diagnosis of a radiologically isolated syndrome (RIS), which may be an early sign of multiple sclerosis (MS). However, some patients who do not fulfill the necessary criteria for RIS still evolve to MS, and some T2 hyperintensities that resemble demyelinating lesions may originate from mimics. In light of the recent recognition of the efficacy of disease-modifying therapy (DMT) in RIS, it is relevant to consider additional imaging features that are more specific of MS. We performed a narrative review on cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL) in patients with RIS. In previous RIS studies, the reported prevalence of CLs ranges between 20.0 and 40.0%, CVS + white matter lesions (WMLs) between 87.0 and 93.0% and PRLs between 26.7 and 63.0%. Overall, these imaging findings appear to be frequent in RIS cohorts, although not consistently taken into account in previous studies. The search for CLs, CVS + WML and PRLs in RIS patients could lead to earlier identification of patients who will evolve to MS and benefit from DMTs.
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Affiliation(s)
- João Moura
- Department of Neurology, Centro Hospitalar Universitário de Santo António, Largo Professor Abel Salazar, 4099-001, Porto, Portugal.
- ICBAS School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Monica Marta
- Department of Neurology, Royal London Hospital, Barts Health NHS Trust, London, UK
- Neuroscience and Trauma, Blizard Institute of Cell and Molecular Science, London, UK
| | - Ana Martins Silva
- Department of Neurology, Centro Hospitalar Universitário de Santo António, Largo Professor Abel Salazar, 4099-001, Porto, Portugal
- ICBAS School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
- Unit of Multidisciplinary Research in Biomedicine, Instituto de Ciências Biomédicas Abel Salazar, University of Porto, Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), Porto, Portugal
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4
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Nistri R, Ianniello A, Pozzilli V, Giannì C, Pozzilli C. Advanced MRI Techniques: Diagnosis and Follow-Up of Multiple Sclerosis. Diagnostics (Basel) 2024; 14:1120. [PMID: 38893646 PMCID: PMC11171945 DOI: 10.3390/diagnostics14111120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/08/2024] [Accepted: 05/13/2024] [Indexed: 06/21/2024] Open
Abstract
Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing-remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.
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Affiliation(s)
- Riccardo Nistri
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
| | - Antonio Ianniello
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
| | - Valeria Pozzilli
- Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Costanza Giannì
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
- IRCCS Neuromed, 86077 Pozzilli, Italy
| | - Carlo Pozzilli
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
- MS Center Sant’Andrea Hospital, 00189 Rome, Italy
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Durozard P, Maarouf A, Zaaraoui W, Stellmann JP, Boutière C, Rico A, Demortière S, Guye M, Le Troter A, Dary H, Ranjeva JP, Audoin B, Pelletier J. Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI. Invest Radiol 2024:00004424-990000000-00214. [PMID: 38889240 DOI: 10.1097/rli.0000000000001082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
OBJECTIVES Compelling evidence indicates a significant involvement of cortical lesions in the progressive phase of multiple sclerosis (MS), significantly contributing to late-stage disability. Despite the promise of ultra-high-field magnetic resonance imaging (MRI) in detecting cortical lesions, current evidence falls short in providing insights into the existence of such lesions during the early stages of MS or their underlying cause. This study delineated, at the early stage of MS, (1) the prevalence and spatial distribution of cortical lesions identified by 7 T MRI, (2) their relationship with white matter lesions, and (3) their clinical implications. MATERIALS AND METHODS Twenty individuals with early-stage relapsing-remitting MS (disease duration <1 year) underwent a 7 T MRI session involving T1-weighted MP2RAGE, T2*-weighted multiGRE, and T2-weighted FLAIR sequences for cortical and white matter segmentation. Disability assessments included the Expanded Disability Status Scale, the Multiple Sclerosis Functional Composite, and an extensive evaluation of cognitive function. RESULTS Cortical lesions were detected in 15 of 20 patients (75%). MP2RAGE revealed a total of 190 intracortical lesions (median, 4 lesions/case [range, 0-44]) and 216 leukocortical lesions (median, 2 lesions/case [range, 0-75]). Although the number of white matter lesions correlated with the total number of leukocortical lesions (r = 0.91, P < 0.001), no correlation was observed between the number of white matter or leukocortical lesions and the number of intracortical lesions. Furthermore, the number of leukocortical lesions but not intracortical or white-matter lesions was significantly correlated with cognitive impairment (r = 0.63, P = 0.04, corrected for multiple comparisons). CONCLUSIONS This study highlights the notable prevalence of cortical lesions at the early stage of MS identified by 7 T MRI. There may be a potential divergence in the underlying pathophysiological mechanisms driving distinct lesion types, notably between intracortical lesions and white matter/leukocortical lesions. Moreover, during the early disease phase, leukocortical lesions more effectively accounted for cognitive deficits.
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Affiliation(s)
- Pierre Durozard
- From the Aix Marseille Univ, CNRS, CRMBM, Marseille, France (P.D., A.M., W.Z., J.-P.S., A.R., M.G., A.T., H.D., J.-P.R., B.A., J.P.); Aix Marseille Univ, APHM, Pôle de Neurosciences Cliniques, MICeME, Marseille, France (A.M., C.B., A.R., S.D., B.A., J.P.); Aix Marseille Univ, APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, Marseille, France (J.-P.S., M.G.); and CRC-SEP Corse, Centre Hospitalier d'Ajaccio, Ajaccio, France (P.D.)
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6
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Faigle W, Piccirelli M, Hortobágyi T, Frontzek K, Cannon AE, Zürrer WE, Granberg T, Kulcsar Z, Ludersdorfer T, Frauenknecht KBM, Reimann R, Ineichen BV. The Brainbox -a tool to facilitate correlation of brain magnetic resonance imaging features to histopathology. Brain Commun 2023; 5:fcad307. [PMID: 38025281 PMCID: PMC10664401 DOI: 10.1093/braincomms/fcad307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 07/20/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
Magnetic resonance imaging (MRI) has limitations in identifying underlying tissue pathology, which is relevant for neurological diseases such as multiple sclerosis, stroke or brain tumours. However, there are no standardized methods for correlating MRI features with histopathology. Thus, here we aimed to develop and validate a tool that can facilitate the correlation of brain MRI features to corresponding histopathology. For this, we designed the Brainbox, a waterproof and MRI-compatible 3D printed container with an integrated 3D coordinate system. We used the Brainbox to acquire post-mortem ex vivo MRI of eight human brains, fresh and formalin-fixed, and correlated focal imaging features to histopathology using the built-in 3D coordinate system. With its built-in 3D coordinate system, the Brainbox allowed correlation of MRI features to corresponding tissue substrates. The Brainbox was used to correlate different MR image features of interest to the respective tissue substrate, including normal anatomical structures such as the hippocampus or perivascular spaces, as well as a lacunar stroke. Brain volume decreased upon fixation by 7% (P = 0.01). The Brainbox enabled degassing of specimens before scanning, reducing susceptibility artefacts and minimizing bulk motion during scanning. In conclusion, our proof-of-principle experiments demonstrate the usability of the Brainbox, which can contribute to improving the specificity of MRI and the standardization of the correlation between post-mortem ex vivo human brain MRI and histopathology. Brainboxes are available upon request from our institution.
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Affiliation(s)
- Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University Zurich, University Hospital Zurich, CH-8091 Zurich, Switzerland
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Tibor Hortobágyi
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
| | - Karl Frontzek
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, WC1N 1PJ London, United Kingdom
| | - Amelia Elaine Cannon
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Wolfgang Emanuel Zürrer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, S-141 86 Stockholm, Sweden
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Thomas Ludersdorfer
- Neuroimmunology and MS Research Section, Neurology Clinic, University Zurich, University Hospital Zurich, CH-8091 Zurich, Switzerland
| | - Katrin B M Frauenknecht
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
- Luxembourg Center of Neuropathology (LCNP), Laboratoire National de Santé, 3555 Dudelange, Luxembourg
- National Center of Pathology (NCP), Laboratoire National de Santé, 3555 Dudelange, Luxembourg
| | - Regina Reimann
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, CH-8001 Zurich, Switzerland
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Baadsvik EL, Weiger M, Froidevaux R, Faigle W, Ineichen BV, Pruessmann KP. Quantitative magnetic resonance mapping of the myelin bilayer reflects pathology in multiple sclerosis brain tissue. SCIENCE ADVANCES 2023; 9:eadi0611. [PMID: 37566661 PMCID: PMC10421026 DOI: 10.1126/sciadv.adi0611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 07/07/2023] [Indexed: 08/13/2023]
Abstract
Multiple sclerosis (MS) is a neuroinflammatory disease characterized by loss of myelin (demyelination) and, to a certain extent, subsequent myelin repair (remyelination). To better understand the pathomechanisms underlying de- and remyelination and to monitor the efficacy of treatments aimed at regenerating myelin, techniques offering noninvasive visualizations of myelin are warranted. Magnetic resonance (MR) imaging has long been at the forefront of efforts to visualize myelin, but it has only recently become feasible to access the rapidly decaying resonance signals stemming from the myelin lipid-protein bilayer itself. Here, we show that direct MR mapping of the bilayer yields highly specific myelin maps in brain tissue from patients with MS. Furthermore, examination of the bilayer signal behavior is found to reveal pathological alterations in normal-appearing white and gray matter. These results indicate promise for in vivo implementations of the myelin bilayer mapping technique, with prospective applications in basic research, diagnostics, disease monitoring, and drug development.
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Affiliation(s)
- Emily Louise Baadsvik
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Romain Froidevaux
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University of Zurich, University Hospital Zurich, Zurich, Switzerland
- Institut Curie, Immunity and Cancer Unit 932, Paris, France
| | - Benjamin V. Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Schmidt R, Keban E, Bollmann S, Wiggins CJ, Niendorf T. Scaling the mountains: what lies above 7 Tesla magnetic resonance? MAGMA (NEW YORK, N.Y.) 2023; 36:151-157. [PMID: 37072540 PMCID: PMC10140119 DOI: 10.1007/s10334-023-01087-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 04/20/2023]
Affiliation(s)
- Rita Schmidt
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Elena Keban
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University of Bern, Bern, Switzerland
| | - Saskia Bollmann
- School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture and Information Technology, The University of Queensland, Brisbane, Australia
| | - Christopher J Wiggins
- Imaging Core Facility, Institute for Neurology and Medicine, Forschungszentrum Julich, Julich, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility, Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.
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Lesion-Specific Metabolic Alterations in Relapsing-Remitting Multiple Sclerosis Via 7 T Magnetic Resonance Spectroscopic Imaging. Invest Radiol 2023; 58:156-165. [PMID: 36094811 PMCID: PMC9835681 DOI: 10.1097/rli.0000000000000913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND Magnetic resonance spectroscopic imaging (MRSI) of the brain enables in vivo assessment of metabolic alterations in multiple sclerosis (MS). This provides complementary insights into lesion pathology that cannot be obtained via T1- and T2-weighted conventional magnetic resonance imaging (cMRI). PURPOSE The aims of this study were to assess focal metabolic alterations inside and at the periphery of lesions that are visible or invisible on cMRI, and to correlate their metabolic changes with T1 hypointensity and the distance of lesions to cortical gray matter (GM). METHODS A 7 T MRSI was performed on 51 patients with relapsing-remitting MS (30 female/21 male; mean age, 35.4 ± 9.9 years). Mean metabolic ratios were calculated for segmented regions of interest (ROIs) of normal-appearing white matter, white matter lesions, and focal regions of increased mIns/tNAA invisible on cMRI. A subgroup analysis was performed after subdividing based on T1 relaxation and distance to cortical GM. Metabolite ratios were correlated with T1 and compared between different layers around cMRI-visible lesions. RESULTS Focal regions of, on average, 2.8-fold higher mIns/tNAA than surrounding normal-appearing white matter and with an appearance similar to that of MS lesions were found, which were not visible on cMRI (ie, ~4% of metabolic hotspots). T1 relaxation was positively correlated with mIns/tNAA ( P ≤ 0.01), and negatively with tNAA/tCr ( P ≤ 0.01) and tCho/tCr ( P ≤ 0.01). mIns/tCr was increased outside lesions, whereas tNAA/tCr distributions resembled macroscopic tissue damage inside the lesions. mIns/tCr was -21% lower for lesions closer to cortical GM ( P ≤ 0.05). CONCLUSIONS 7 T MRSI allows in vivo visualization of focal MS pathology not visible on cMRI and the assessment of metabolite levels in the lesion center, in the active lesion periphery and in cortical lesions. This demonstrated the potential of MRSI to image mIns as an early biomarker in lesion development.
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10
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Glutathione in the Pons Is Associated With Clinical Status Improvements in Subacute Spinal Cord Injury. Invest Radiol 2023; 58:131-138. [PMID: 35926077 DOI: 10.1097/rli.0000000000000905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
OBJECTIVES In spinal cord injury (SCI), the primary mechanical injury is followed by secondary sequelae that develop over the subsequent months and manifests in biochemical, functional, and microstructural alterations, at the site of direct injury but also in the spinal cord tissue above and below the actual lesion site. Noninvasive magnetic resonance spectroscopy (MRS) can be used to assess biochemical modulation occurring in the secondary injury phase, in addition to and supporting conventional MRI, and might help predict and improve patient outcome. In this article, we aimed to examine the metabolic levels in the pons of subacute SCI by means of in vivo proton MRS at 3 T and explore the association to clinical scores. MATERIALS AND METHODS In this prospective study, between November 2015 and February 2018, single-voxel short-echo MRS data were acquired in healthy controls and in SCI subjects in the pons once during rehabilitation. Besides the single-point MRS examination, in addition, in participants with SCI, the clinical status (ie, motor, light touch, and pinprick scores) was assessed twice: (1) around the MRS session (approximately 10 weeks postinjury) and (2) before discharge (at approximately 9 months postinjury). The group differences were assessed with Kruskal-Wallis test, the post hoc comparison was assessed with Wilcoxon rank sum test, and the clinical correlations were conducted with Spearman rank correlation test. Bayes factor calculations completed the statistical part providing relevant evidence values. RESULTS Twenty healthy controls (median age, 50 years; interquartile range, 41-55 years; 18 men) and 18 subjects with traumatic SCI (median age, 50 years; interquartile range, 32-58 years; 16 men) are included. Group comparison showed an increase of total N -acetylaspartate and combined glutamate and glutamine levels in complete SCI and a reduction of total creatine in incomplete paraplegic SCI. The proton MRS-based glutathione levels at baseline correlate to the motor score improvement during rehabilitation in incomplete subacute SCI. CONCLUSIONS This exploratory study showed an association of the metabolite concentration of glutathione in the pons assessed at approximately 10 weeks after injury with the improvements of the motor score during the rehabilitation. Pontine glutathione levels in subjects with traumatic subacute incomplete SCI acquired remote from the injury site correlate to clinical score and might therefore be beneficial in the rehabilitation assessments.
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11
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Ineichen BV, Okar SV, Proulx ST, Engelhardt B, Lassmann H, Reich DS. Perivascular spaces and their role in neuroinflammation. Neuron 2022; 110:3566-3581. [PMID: 36327898 PMCID: PMC9905791 DOI: 10.1016/j.neuron.2022.10.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/17/2022] [Accepted: 10/13/2022] [Indexed: 11/19/2022]
Abstract
It is uncontested that perivascular spaces play critical roles in maintaining homeostasis and priming neuroinflammation. However, despite more than a century of intense research on perivascular spaces, many open questions remain about the anatomical compartment surrounding blood vessels within the CNS. The goal of this comprehensive review is to summarize the literature on perivascular spaces in human neuroinflammation and associated animal disease models. We describe the cell types taking part in the morphological and functional aspects of perivascular spaces and how those spaces can be visualized. Based on this, we propose a model of the cascade of events occurring during neuroinflammatory pathology. We also discuss current knowledge gaps and limitations of the available evidence. An improved understanding of perivascular spaces could advance our comprehension of the pathophysiology of neuroinflammation and open a new therapeutic window for neuroinflammatory diseases such as multiple sclerosis.
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Affiliation(s)
- Benjamin V Ineichen
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA; Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Center for Reproducible Science, University of Zurich, Zurich, Switzerland.
| | - Serhat V Okar
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven T Proulx
- Theodor Kocher Institute, University of Bern, Bern, Switzerland
| | | | - Hans Lassmann
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Spitalgasse 4, 1090 Vienna, Austria
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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12
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Combes AJ, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J.E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Corresponding author at: 1161 21st Ave S, MCN AA1105, Nashville, TN 37232, USA.
| | - Margareta A. Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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13
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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14
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Seginer A, Schmidt R. Phase-based fast 3D high-resolution quantitative T 2 MRI in 7 T human brain imaging. Sci Rep 2022; 12:14088. [PMID: 35982143 PMCID: PMC9388657 DOI: 10.1038/s41598-022-17607-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/28/2022] [Indexed: 12/04/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a powerful and versatile technique that offers a range of physiological, diagnostic, structural, and functional measurements. One of the most widely used basic contrasts in MRI diagnostics is transverse relaxation time (T2)-weighted imaging, but it provides only qualitative information. Realizing quantitative high-resolution T2 mapping is imperative for the development of personalized medicine, as it can enable the characterization of diseases progression. While ultra-high-field (≥ 7 T) MRI offers the means to gain new insights by increasing the spatial resolution, implementing fast quantitative T2 mapping cannot be achieved without overcoming the increased power deposition and radio frequency (RF) field inhomogeneity at ultra-high-fields. A recent study has demonstrated a new phase-based T2 mapping approach based on fast steady-state acquisitions. We extend this new approach to ultra-high field MRI, achieving quantitative high-resolution 3D T2 mapping at 7 T while addressing RF field inhomogeneity and utilizing low flip angle pulses; overcoming two main ultra-high field challenges. The method is based on controlling the coherent transverse magnetization in a steady-state gradient echo acquisition; achieved by utilizing low flip angles, a specific phase increment for the RF pulses, and short repetition times. This approach simultaneously extracts both T2 and RF field maps from the phase of the signal. Prior to in vivo experiments, the method was assessed using a 3D head-shaped phantom that was designed to model the RF field distribution in the brain. Our approach delivers fast 3D whole brain images with submillimeter resolution without requiring special hardware, such as multi-channel transmit coil, thus promoting high usability of the ultra-high field MRI in clinical practice.
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Affiliation(s)
| | - Rita Schmidt
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel. .,The Azrieli National Institute for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel.
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15
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La Rosa F, Beck ES, Maranzano J, Todea R, van Gelderen P, de Zwart JA, Luciano NJ, Duyn JH, Thiran J, Granziera C, Reich DS, Sati P, Bach Cuadra M. Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI. NMR IN BIOMEDICINE 2022; 35:e4730. [PMID: 35297114 PMCID: PMC9539569 DOI: 10.1002/nbm.4730] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/23/2022] [Accepted: 03/14/2022] [Indexed: 05/16/2023]
Abstract
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical Lesion AI-Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5 mm isotropic MP2RAGE acquired four times (MP2RAGE×4), 0.7 mm MP2RAGE, 0.5 mm T2 *-weighted GRE, and 0.5 mm T2 *-weighted EPI. The second dataset consisted of 20 scans including only 0.75 × 0.75 × 0.9 mm3 MP2RAGE. CLAIMS was first evaluated using sixfold cross-validation with single and multi-contrast 0.5 mm MRI input. Second, the performance of the model was tested on 0.7 mm MP2RAGE images after training with either 0.5 mm MP2RAGE×4, 0.7 mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state-of-the-art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGE×4 achieved results comparable to those of the multi-contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain-scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6 μL (lesion-wise detection rate of 71% versus 48%). The proposed framework outperforms previous state-of-the-art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7 T MRI, especially in the field of diagnosis and differential diagnosis of MS patients.
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Erin S. Beck
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Josefina Maranzano
- Department of AnatomyUniversity of Quebec in Trois‐RivièresTrois‐RivièresQuebecCanada
- McConnell Brain Imaging Center, Department of Neurology and NeurosurgeryMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
| | - Ramona‐Alexandra Todea
- Department of Neuroradiology, Clinic of Radiology and Nuclear MedicineUniversity Hospital of BaselBaselSwitzerland
| | - Peter van Gelderen
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jacco A. de Zwart
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Nicholas J. Luciano
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Jeff H. Duyn
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jean‐Philippe Thiran
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Pascal Sati
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCAUSA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
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16
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Multiple sclerosis: two decades of progress. Lancet Neurol 2022; 21:211-214. [DOI: 10.1016/s1474-4422(22)00040-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 01/25/2022] [Indexed: 12/16/2022]
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17
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A Deep Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging. Invest Radiol 2022; 57:423-432. [DOI: 10.1097/rli.0000000000000854] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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18
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Barker PB. Brain Pathology in Multiple Sclerosis with High-Field-Strength MR Spectroscopic Imaging. Radiology 2022; 303:151-152. [PMID: 34981980 DOI: 10.1148/radiol.212026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Peter B Barker
- From the Russell H. Morgan Department of Radiology and Radiological Sciences, the Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 367B, Baltimore, MD 21287
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19
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Runge VM, Heverhagen JT. The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T. Invest Radiol 2022; 57:1-12. [PMID: 34510100 DOI: 10.1097/rli.0000000000000824] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
ABSTRACT This review provides a balanced perspective regarding the clinical utility of magnetic resonance systems across the range of field strengths for which current state-of-the-art units exist (0.55 T, 1.5 T, 3 T, and 7 T). Guidance regarding this issue is critical to appropriate purchasing, usage, and further dissemination of this important imaging modality, both in the industrial world and in developing nations. The review serves to provide an important update, although to a large extent this information has never previously been openly presented. In that sense, it serves also as a position paper, with statements and recommendations as appropriate.
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Affiliation(s)
- Val M Runge
- From the Department of Diagnostic, Interventional, and Pediatric Radiology, University Hospital of Bern, Inselspital, University of Bern, Bern, Switzerland
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Kreiter DJ, van den Hurk J, Wiggins CJ, Hupperts RMM, Gerlach OHH. Ultra-high field spinal cord MRI in multiple sclerosis: Where are we standing? A literature review. Mult Scler Relat Disord 2021; 57:103436. [PMID: 34871855 DOI: 10.1016/j.msard.2021.103436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 11/18/2021] [Accepted: 11/27/2021] [Indexed: 12/24/2022]
Abstract
Magnetic resonance imaging (MRI) is a cornerstone in multiple sclerosis (MS) diagnostics and monitoring. Ultra-high field (UHF) MRI is being increasingly used and becoming more accessible. Due to the small diameter and mobility of the spinal cord, imaging this structure at ultra-high fields poses additional challenges compared to brain imaging. Here we review the potential benefits for the MS field by providing a literature overview of the use UHF spinal cord MRI in MS research and we elaborate on the challenges that are faced. Benefits include increased signal- and contrast-to-noise, enabling for higher spatial resolutions, which can improve MS lesion sensitivity in both the spinal white matter as well as grey matter. Additionally, these benefits can aid imaging of microstructural abnormalities in the spinal cord in MS using advanced MRI techniques like functional imaging, MR spectroscopy and diffusion-based techniques. Technical challenges include increased magnetic field inhomogeneities, distortions from physiological motion and optimalisation of sequences. Approaches including parallel imaging techniques, real time shimming and retrospective compensation of physiological motion are making it increasingly possible to unravel the potential of spinal cord UHF MRI in the context of MS research.
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Affiliation(s)
- Daniël J Kreiter
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.
| | - Job van den Hurk
- Scannexus, Maastricht, The Netherlands; Maastricht University, Faculty of Health, Medicine & Life Sciences, Maastricht, The Netherlands
| | | | - Raymond M M Hupperts
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Oliver H H Gerlach
- Academic MS center Zuyderland, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands; School for Mental Health and Neuroscience, Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.
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