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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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Rubin M, Pagani E, Preziosa P, Meani A, Storelli L, Margoni M, Filippi M, Rocca MA. Cerebrospinal Fluid-In Gradient of Cortical and Deep Gray Matter Damage in Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200271. [PMID: 38896808 PMCID: PMC11197989 DOI: 10.1212/nxi.0000000000200271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 04/19/2024] [Indexed: 06/21/2024]
Abstract
BACKGROUND AND OBJECTIVES A CSF-in gradient in cortical and thalamic gray matter (GM) damage has been found in multiple sclerosis (MS). We concomitantly explored the patterns of cortical, thalamic, and caudate microstructural abnormalities at progressive distances from CSF using a multiparametric MRI approach. METHODS For this cross-sectional study, from 3T 3D T1-weighted scans, we sampled cortical layers at 25%-50%-75% depths from pial surface and thalamic and caudate bands at 2-3-4 voxels from the ventricular-GM interface. Using linear mixed models, we tested between-group comparisons of magnetization transfer ratio (MTR) and R2* layer-specific z-scores, CSF-in across-layer z-score changes, and their correlations with clinical (disease duration and disability) and structural (focal lesions, brain, and choroid plexus volume) MRI measures. RESULTS We enrolled 52 patients with MS (33 relapsing-remitting [RRMS], 19 progressive [PMS], mean age: 46.4 years, median disease duration: 15.1 years, median: EDSS 2.0) and 70 controls (mean age 41.5 ± 12.8). Compared with controls, RRMS showed lower MTR values in the outer and middle cortical layers (false-discovery rate [FDR]-p ≤ 0.025) and lower R2* values in all 3 cortical layers (FDR-p ≤ 0.016). PMS had lower MTR values in the outer and middle cortical (FDR-p ≤ 0.016) and thalamic (FDR-p ≤ 0.048) layers, and in the outer caudate layer (FDR-p = 0.024). They showed lower R2* values in the outer cortical layer (FDR-p = 0.003) and in the outer thalamic layer (FDR-p = 0.046) and higher R2* values in all 3 caudate layers (FDR-p ≤ 0.031). Both RRMS and PMS had a gradient of damage, with lower values closer to the CSF, for cortical (FDR-p ≤ 0.002) and thalamic (FDR-p ≤ 0.042) MTR. PMS showed a gradient of damage for cortical R2* (FDR-p = 0.005), thalamic R2* (FDR-p = 0.004), and caudate MTR (FDR-p ≤ 0.013). Lower MTR and R2* of outer cortical, thalamic, and caudate layers and steeper gradient of damage toward the CSF were significantly associated with older age, higher T2-hyperintense white matter lesion volume, higher thalamic lesion volume, and lower brain volume (β ≥ 0.08, all FDR-p ≤ 0.040). Lower MTR of outer caudate layer was associated with more severe disability (β = -0.26, FDR-p = 0.040). No correlations with choroid plexus volume were found. DISCUSSION CSF-in damage gradients are heterogeneous among different GM regions and through MS course, possibly reflecting different dynamics of demyelination and iron loss/accumulation.
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Affiliation(s)
- Martina Rubin
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Loredana Storelli
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Monica Margoni
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- From the Neuroimaging Research Unit (M.R., E.P., P.P., A.M., L.S., M.M., M.F., M.A.R.), Division of Neuroscience; Neurology Unit (M.R., P.P., M.M., M.F., M.A.R.), IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.R., P.P., M.F., M.A.R.); Neurorehabilitation Unit (M.M., M.F.); and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Milan, Italy
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Ananthavarathan P, Sahi N, Chard DT. An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression. Expert Rev Neurother 2024; 24:201-216. [PMID: 38235594 DOI: 10.1080/14737175.2024.2304116] [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: 11/01/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024]
Abstract
INTRODUCTION While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear. AREAS COVERED The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning. EXPERT OPINION Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.
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Affiliation(s)
- Piriyankan Ananthavarathan
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Nitin Sahi
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Declan T Chard
- Clinical Research Associate & Consultant Neurologist, Institute of Neurology - Queen Square Multiple Sclerosis Centre, London, UK
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Tonietto M, Poirion E, Lazzarotto A, Ricigliano V, Papeix C, Bottlaender M, Bodini B, Stankoff B. Periventricular remyelination failure in multiple sclerosis: a substrate for neurodegeneration. Brain 2023; 146:182-194. [PMID: 36097347 DOI: 10.1093/brain/awac334] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 07/26/2022] [Accepted: 08/18/2022] [Indexed: 01/11/2023] Open
Abstract
In multiple sclerosis, spontaneous remyelination is generally incomplete and heterogeneous across patients. A high heterogeneity in remyelination may also exist across lesions within the same individual, suggesting the presence of local factors interfering with myelin regeneration. In this study we explored in vivo the regional distribution of myelin repair and investigated its relationship with neurodegeneration. We first took advantage of the myelin binding property of the amyloid radiotracer 11C-PiB to conduct a longitudinal 11C-PiB PET study in an original cohort of 19 participants with a relapsing-remitting form of multiple sclerosis, followed-up over a period of 1-4 months. We then replicated our results on an independent cohort of 40 people with multiple sclerosis followed-up over 1 year with magnetization transfer imaging, an MRI metrics sensitive to myelin content. For each imaging method, voxel-wise maps of myelin content changes were generated according to modality-specific thresholds. We demonstrated a selective failure of remyelination in periventricular white matter lesions of people with multiple sclerosis in both cohorts. In both the original and the replication cohort, we estimated that the probability of demyelinated voxels to remyelinate over the follow-up increased significantly as a function of the distance from ventricular CSF. Enlarged choroid plexus, a recently discovered biomarker linked to neuroinflammation, was found to be associated with the periventricular failure of remyelination in the two cohorts (r = -0.79, P = 0.0018; r = -0.40, P = 0.045, respectively), suggesting a role of the brain-CSF barrier in affecting myelin repair in surrounding tissues. In both cohorts, the failure of remyelination in periventricular white matter lesions was associated with lower thalamic volume (r = 0.86, P < 0.0001; r = 0.33; P = 0.069, respectively), an imaging marker of neurodegeneration. Interestingly, we also showed an association between the periventricular failure of remyelination and regional cortical atrophy that was mediated by the number of cortex-derived tracts passing through periventricular white matter lesions, especially in patients at the relapsing-remitting stage. Our findings demonstrate that lesion proximity to ventricles is associated with a failure of myelin repair and support the hypothesis that a selective periventricular remyelination failure in combination with the large number of tracts connecting periventricular lesions with cortical areas is a key mechanism contributing to cortical damage in multiple sclerosis.
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Affiliation(s)
- Matteo Tonietto
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Service Hospitalier Frédéric Joliot, Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, France
| | - Emilie Poirion
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France
| | - Andrea Lazzarotto
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Vito Ricigliano
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Caroline Papeix
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, Pitié-Salpêtrière Hospital, APHP, Paris, France
| | - Michel Bottlaender
- Service Hospitalier Frédéric Joliot, Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, France
| | - Benedetta Bodini
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
| | - Bruno Stankoff
- Paris Brain Institute, Sorbonne Université, ICM, CNRS, Inserm, Paris, France.,Neurology Department, St Antoine Hospital, APHP, Paris, France
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Periventricular magnetisation transfer abnormalities in early multiple sclerosis. Neuroimage Clin 2022; 34:103012. [PMID: 35487133 PMCID: PMC9125781 DOI: 10.1016/j.nicl.2022.103012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 11/30/2022]
Abstract
Periventricular-MTR gradients are present from the earliest stage of MS and become steeper in advanced disease. Lower MTR in periventricular-NAWM was positively associated with reduced cortical-mean-thickness. MTR in periventricular-lesions scaled with cortical-mean-thickness, while non-periventricular lesions were unrelated. These findings suggest a common pathophysiologic mechanism between CSF-adjacent cortical and periventricular areas.
Objective Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. Methods We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. Results Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. Conclusion PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.
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Vaneckova M, Piredda GF, Andelova M, Krasensky J, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Hilbert T, Maréchal B, Fartaria MJ, Ravano V, Kober T. Periventricular gradient of T 1 tissue alterations in multiple sclerosis. Neuroimage Clin 2022; 34:103009. [PMID: 35561554 PMCID: PMC9112026 DOI: 10.1016/j.nicl.2022.103009] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/24/2022] [Accepted: 04/12/2022] [Indexed: 01/12/2023]
Abstract
T1 relaxation times alterations were assessed based on a study-specific atlas. T1 alterations depend on distance from lateral ventricles (“periventricular gradient”). Gradient parameters correlate better with disability compared to conventional MRI.
Objective Pathology in multiple sclerosis is not homogenously distributed. Recently, it has been shown that structures adjacent to CSF are more severely affected. A gradient of brain tissue involvement was shown with more severe pathology in periventricular areas and in proximity to brain surfaces such as the subarachnoid spaces and ependyma, and hence termed the “surface–in” gradient. Here, we study whether (i) the surface-in gradient of periventricular tissue alteration measured by T1 relaxometry is already present in early multiple sclerosis patients, (ii) how it differs between early and progressive multiple sclerosis patients, and (iii) whether the gradient-derived metrics in normal-appearing white matter and lesions correlate better with physical disability than conventional MRI-based metrics. Methods Forty-seven patients with early multiple sclerosis, 52 with progressive multiple sclerosis, and 92 healthy controls were included in the study. Isotropic 3D T1 relaxometry maps were obtained using the Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes sequence at 3 T. After spatially normalizing the T1 maps into a study-specific common space, T1 inter-subject variability within the healthy cohort was modelled voxel-wise, yielding a normative T1 atlas. Individual comparisons of each multiple sclerosis patient against the atlas were performed by computing z-scores. Equidistant bands of voxels were defined around the ventricles in the supratentorial white matter; the z-scores in these bands were analysed and compared between the early and progressive multiple sclerosis cohorts. Correlations between both conventional and z-score-gradient-derived MRI metrics and the Expanded Disability Status Scale were assessed. Results Patients with early and progressive multiple sclerosis demonstrated a periventricular gradient of T1 relaxation time z-scores. In progressive multiple sclerosis, z-score-derived metrics reflecting the gradient of tissue abnormality in normal-appearing white matter were more strongly correlated with disability (maximal rho = 0.374) than the conventional lesion volume and count (maximal rho = 0.189 and 0.21 respectively). In early multiple sclerosis, the gradient of normal-appearing white matter volume with z-scores > 2 at baseline correlated with clinical disability assessed at two years follow-up. Conclusion Our results suggest that the surface-in white matter gradient of tissue alteration is detectable with T1 relaxometry and is already present at clinical disease onset. The periventricular gradients correlate with clinical disability. The periventricular gradient in normal-appearing white matter may thus qualify as a promising biomarker for monitoring of disease activity from an early stage in all phenotypes of multiple sclerosis.
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Affiliation(s)
- Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Calvi A, Carrasco FP, Tur C, Chard DT, Stutters J, De Angelis F, John N, Williams T, Doshi A, Samson RS, MacManus D, Gandini Wheeler-Kingshott CA, Ciccarelli O, Chataway J, Barkhof F. Association of Slowly Expanding Lesions on MRI With Disability in People With Secondary Progressive Multiple Sclerosis. Neurology 2022; 98:e1783-e1793. [PMID: 35277438 DOI: 10.1212/wnl.0000000000200144] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 01/18/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE To explore the relationship between slowly expanding lesions (SELs) on MRI and disability in secondary progressive multiple sclerosis (SPMS). METHODS We retrospectively studied 345 patients with SPMS enrolled in the MS-SMART trial. They underwent brain MRI at baseline and at 24 and 96 weeks. Definite SELs were defined as concentrically expanding T2 lesions, as assessed by nonlinear deformation of volumetric T1-weighted images. Associations of SEL volumes with other MRI metrics and disability were assessed through Pearson correlations and regression analyses. RESULTS Averaged across patients, 29% of T2 lesions were classified as being definite SELs. A greater volume of definite SELs correlated with a higher total baseline T2 lesion volume (r = 0.55, p < 0.001) and percentage brain volume reduction (r = -0.26, p < 0.001), a higher number of new persisting T1 black holes (r = 0.19, p < 0.001), and, in a subset of 106 patients, with a greater reduction in magnetization transfer ratio (adjusted difference 0.52, p < 0.001). In regression analyses, a higher definite SEL volume was associated with increasing disability, as assessed by the Expanded Disability Status Scale (β = 0.23, p = 0.020), z scores of the Multiple Sclerosis Functional Composite (β = -0.47, p = 0.048), Timed 25-Foot Walk Test (β = -2.10, p = 0.001), and Paced Auditory Serial Addition Task (β = -0.27, p = 0.006), and increased risk of disability progression (odds ratio 1.92, p = 0.025). DISCUSSION Definite SELs represent almost one-third of T2 lesions in SPMS. They are associated with neurodegenerative MRI markers and related to clinical worsening, suggesting that they may contribute to disease progression and be a new target for therapeutic interventions.
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Affiliation(s)
- Alberto Calvi
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Ferran Prados Carrasco
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Carmen Tur
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Declan T Chard
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Jonathan Stutters
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Floriana De Angelis
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Nevin John
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Thomas Williams
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Anisha Doshi
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Rebecca S Samson
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - David MacManus
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Claudia A Gandini Wheeler-Kingshott
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Olga Ciccarelli
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Jeremy Chataway
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
| | - Frederik Barkhof
- From Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, Faculty of Brain Sciences (A.C., F.P.C., C.T., D.T.C., J.S., F.D.A., N.J., T.W., A.D., R.S.S., D.M., C.A.G.W.-K., O.C., J.C., F.B.), and Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering (F.P.C., F.B.), University College London, UK; IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (A.C.), University of Milan, Italy; e-Health Centre (F.P.C.), Universitat Oberta de Catalunya, Barcelona, Spain; Neurology Department (C.T., F.D.A.), Luton and Dunstable University Hospital; National Institute for Health Research (D.T.C., O.C., J.C., F.B.), Biomedical Research Centre, University College London Hospitals, UK; Department of Brain and Behavioural Sciences (C.A.G.W.-K.), University of Pavia; Brain Connectivity Centre (C.A.G.W.-K.), IRCCS Mondino Foundation, Pavia, Italy; and Radiology & Nuclear Medicine (F.B.), VU University Medical Centre, Amsterdam, the Netherlands
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8
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York EN, Thrippleton MJ, Meijboom R, Hunt DPJ, Waldman AD. Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis. Brain Commun 2022; 4:fcac088. [PMID: 35652121 PMCID: PMC9149789 DOI: 10.1093/braincomms/fcac088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/17/2021] [Accepted: 03/31/2022] [Indexed: 11/28/2022] Open
Abstract
Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.
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Affiliation(s)
- Elizabeth N. York
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | | | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
| | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic,
University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of
Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of
Edinburgh, Edinburgh, UK
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9
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Cohan SL, Benedict RHB, Cree BAC, DeLuca J, Hua LH, Chun J. The Two Sides of Siponimod: Evidence for Brain and Immune Mechanisms in Multiple Sclerosis. CNS Drugs 2022; 36:703-719. [PMID: 35725892 PMCID: PMC9259525 DOI: 10.1007/s40263-022-00927-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/12/2022] [Indexed: 12/13/2022]
Abstract
Siponimod is a selective sphingosine 1-phosphate receptor subtype 1 (S1P1) and 5 (S1P5) modulator approved in the United States and the European Union as an oral treatment for adults with relapsing forms of multiple sclerosis (RMS), including active secondary progressive multiple sclerosis (SPMS). Preclinical and clinical studies provide support for a dual mechanism of action of siponimod, targeting peripherally mediated inflammation and exerting direct central effects. As an S1P1 receptor modulator, siponimod reduces lymphocyte egress from lymph nodes, thus inhibiting their migration from the periphery to the central nervous system. As a result of its peripheral immunomodulatory effects, siponimod reduces both magnetic resonance imaging (MRI) lesion (gadolinium-enhancing and new/enlarging T2 hyperintense) and relapse activity compared with placebo. Independent of these effects, siponimod can penetrate the blood-brain barrier and, by binding to S1P1 and S1P5 receptors on a variety of brain cells, including astrocytes, oligodendrocytes, neurons, and microglia, exert effects to modulate neural inflammation and neurodegeneration. Clinical data in patients with SPMS have shown that, compared with placebo, siponimod treatment is associated with reductions in levels of neurofilament light chain (a marker of neuroaxonal damage) and thalamic and cortical gray matter atrophy, with smaller reductions in MRI magnetization transfer ratio and reduced confirmed disability progression. This review examines the preclinical and clinical data supporting the dual mechanism of action of siponimod in RMS.
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Affiliation(s)
- Stanley L Cohan
- Providence Multiple Sclerosis Center, Providence Brain Institute, 9135 SW Barnes Rd Suite 461, Portland, OR, 97225, USA.
| | | | - Bruce A C Cree
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | | | - Le H Hua
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Jerold Chun
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
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10
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Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
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Affiliation(s)
- Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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11
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Haider L, Prados F, Chung K, Goodkin O, Kanber B, Sudre C, Yiannakas M, Samson RS, Mangesius S, Thompson AJ, Gandini Wheeler-Kingshott CAM, Ciccarelli O, Chard DT, Barkhof F. Cortical involvement determines impairment 30 years after a clinically isolated syndrome. Brain 2021; 144:1384-1395. [PMID: 33880511 PMCID: PMC8219364 DOI: 10.1093/brain/awab033] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/24/2020] [Accepted: 12/03/2020] [Indexed: 01/01/2023] Open
Abstract
Many studies report an overlap of MRI and clinical findings between patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), which in part is reflective of inclusion of subjects with variable disease duration and short periods of follow-up. To overcome these limitations, we examined the differences between RRMS and SPMS and the relationship between MRI measures and clinical outcomes 30 years after first presentation with clinically isolated syndrome suggestive of multiple sclerosis. Sixty-three patients were studied 30 years after their initial presentation with a clinically isolated syndrome; only 14% received a disease modifying treatment at any time point. Twenty-seven patients developed RRMS, 15 SPMS and 21 experienced no further neurological events; these groups were comparable in terms of age and disease duration. Clinical assessment included the Expanded Disability Status Scale, 9-Hole Peg Test and Timed 25-Foot Walk and the Brief International Cognitive Assessment For Multiple Sclerosis. All subjects underwent a comprehensive MRI protocol at 3 T measuring brain white and grey matter (lesions, volumes and magnetization transfer ratio) and cervical cord involvement. Linear regression models were used to estimate age- and gender-adjusted group differences between clinical phenotypes after 30 years, and stepwise selection to determine associations between a large sets of MRI predictor variables and physical and cognitive outcome measures. At the 30-year follow-up, the greatest differences in MRI measures between SPMS and RRMS were the number of cortical lesions, which were higher in SPMS (the presence of cortical lesions had 100% sensitivity and 88% specificity), and grey matter volume, which was lower in SPMS. Across all subjects, cortical lesions, grey matter volume and cervical cord volume explained 60% of the variance of the Expanded Disability Status Scale; cortical lesions alone explained 43%. Grey matter volume, cortical lesions and gender explained 43% of the variance of Timed 25-Foot Walk. Reduced cortical magnetization transfer ratios emerged as the only significant explanatory variable for the symbol digit modality test and explained 52% of its variance. Cortical involvement, both in terms of lesions and atrophy, appears to be the main correlate of progressive disease and disability in a cohort of individuals with very long follow-up and homogeneous disease duration, indicating that this should be the target of therapeutic interventions.
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Affiliation(s)
- Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Department of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Austria
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Karen Chung
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Olivia Goodkin
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Carole Sudre
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Marios Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Alan J Thompson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.,Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
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12
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Pardini M, Brown JWL, Magliozzi R, Reynolds R, Chard DT. Surface-in pathology in multiple sclerosis: a new view on pathogenesis? Brain 2021; 144:1646-1654. [PMID: 33876200 DOI: 10.1093/brain/awab025] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 11/03/2020] [Accepted: 11/17/2020] [Indexed: 11/12/2022] Open
Abstract
While multiple sclerosis can affect any part of the CNS, it does not do so evenly. In white matter it has long been recognized that lesions tend to occur around the ventricles, and grey matter lesions mainly accrue in the outermost (subpial) cortex. In cortical grey matter, neuronal loss is greater in the outermost layers. This cortical gradient has been replicated in vivo with magnetization transfer ratio and similar gradients in grey and white matter magnetization transfer ratio are seen around the ventricles, with the most severe abnormalities abutting the ventricular surface. The cause of these gradients remains uncertain, though soluble factors released from meningeal inflammation into the CSF has the most supporting evidence. In this Update, we review this 'surface-in' spatial distribution of multiple sclerosis abnormalities and consider the implications for understanding pathogenic mechanisms and treatments designed to slow or stop them.
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Affiliation(s)
- Matteo Pardini
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, and IRCCS AOU San Martino-IST, Genoa, Italy
| | - J William L Brown
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Department of Clinical Neurosciences, University of Cambridge, Box 165, Cambridge Biomedical Campus, Cambridge, UK.,Clinical Outcomes Research Unit (CORe), University of Melbourne, Melbourne, Australia
| | - Roberta Magliozzi
- Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy.,Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Richard Reynolds
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK.,Centre for Molecular Neuropathology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
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13
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Rahmanzadeh R, Lu PJ, Barakovic M, Weigel M, Maggi P, Nguyen TD, Schiavi S, Daducci A, La Rosa F, Schaedelin S, Absinta M, Reich DS, Sati P, Wang Y, Bach Cuadra M, Radue EW, Kuhle J, Kappos L, Granziera C. Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging. Brain 2021; 144:1684-1696. [PMID: 33693571 PMCID: PMC8374972 DOI: 10.1093/brain/awab088] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 12/29/2020] [Accepted: 01/03/2021] [Indexed: 12/25/2022] Open
Abstract
Damage to the myelin sheath and the neuroaxonal unit is a cardinal feature of multiple sclerosis; however, a detailed characterization of the interaction between myelin and axon damage in vivo remains challenging. We applied myelin water and multi-shell diffusion imaging to quantify the relative damage to myelin and axons (i) among different lesion types; (ii) in normal-appearing tissue; and (iii) across multiple sclerosis clinical subtypes and healthy controls. We also assessed the relation of focal myelin/axon damage with disability and serum neurofilament light chain as a global biological measure of neuroaxonal damage. Ninety-one multiple sclerosis patients (62 relapsing-remitting, 29 progressive) and 72 healthy controls were enrolled in the study. Differences in myelin water fraction and neurite density index were substantial when lesions were compared to healthy control subjects and normal-appearing multiple sclerosis tissue: both white matter and cortical lesions exhibited a decreased myelin water fraction and neurite density index compared with healthy (P < 0.0001) and peri-plaque white matter (P < 0.0001). Periventricular lesions showed decreased myelin water fraction and neurite density index compared with lesions in the juxtacortical region (P < 0.0001 and P < 0.05). Similarly, lesions with paramagnetic rims showed decreased myelin water fraction and neurite density index relative to lesions without a rim (P < 0.0001). Also, in 75% of white matter lesions, the reduction in neurite density index was higher than the reduction in the myelin water fraction. Besides, normal-appearing white and grey matter revealed diffuse reduction of myelin water fraction and neurite density index in multiple sclerosis compared to healthy controls (P < 0.01). Further, a more extensive reduction in myelin water fraction and neurite density index in normal-appearing cortex was observed in progressive versus relapsing-remitting participants. Neurite density index in white matter lesions correlated with disability in patients with clinical deficits (P < 0.01, beta = -10.00); and neurite density index and myelin water fraction in white matter lesions were associated to serum neurofilament light chain in the entire patient cohort (P < 0.01, beta = -3.60 and P < 0.01, beta = 0.13, respectively). These findings suggest that (i) myelin and axon pathology in multiple sclerosis is extensive in both lesions and normal-appearing tissue; (ii) particular types of lesions exhibit more damage to myelin and axons than others; (iii) progressive patients differ from relapsing-remitting patients because of more extensive axon/myelin damage in the cortex; and (iv) myelin and axon pathology in lesions is related to disability in patients with clinical deficits and global measures of neuroaxonal damage.
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Affiliation(s)
- Reza Rahmanzadeh
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Pietro Maggi
- Department of Neurology, Lausanne University Hospital, Lausanne, Switzerland.,Cliniques universitaires Saint Luc, Université catholique de Louvain, Brussel, Belgium
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Radiology Department, Center for Biomedical Imaging (CIBM), Lausanne University and University Hospital, Lausanne, Switzerland
| | - Sabine Schaedelin
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Radiology Department, Center for Biomedical Imaging (CIBM), Lausanne University and University Hospital, Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Department of Medicine and Biomedical Engineering, Translational Imaging in Neurology Basel, University Hospital Basel and University of Basel, Basel, Switzerland.,Departments of Medicine, Clinical Research and Biomedical Engineering Neurologic Clinic and Policlinic, Switzerland, University Hospital Basel and University of Basel, Basel, Switzerland
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14
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Filippi M, Preziosa P, Barkhof F, Chard DT, De Stefano N, Fox RJ, Gasperini C, Kappos L, Montalban X, Moraal B, Reich DS, Rovira À, Toosy AT, Traboulsee A, Weinshenker BG, Zeydan B, Banwell BL, Rocca MA. Diagnosis of Progressive Multiple Sclerosis From the Imaging Perspective: A Review. JAMA Neurol 2021; 78:351-364. [PMID: 33315071 DOI: 10.1001/jamaneurol.2020.4689] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance Although magnetic resonance imaging (MRI) is useful for monitoring disease dissemination in space and over time and excluding multiple sclerosis (MS) mimics, there has been less application of MRI to progressive MS, including diagnosing primary progressive (PP) MS and identifying patients with relapsing-remitting (RR) MS who are at risk of developing secondary progressive (SP) MS. This review addresses clinical application of MRI for both diagnosis and prognosis of progressive MS. Observations Although nonspecific, some spinal cord imaging features (diffuse abnormalities and lesions involving gray matter [GM] and ≥2 white matter columns) are typical of PPMS. In patients with PPMS and those with relapse-onset MS, location of lesions in critical central nervous system regions (spinal cord, infratentorial regions, and GM) and MRI-detected high inflammatory activity in the first years after diagnosis are risk factors for long-term disability and future progressive disease course. These measures are evaluable in clinical practice. In patients with established MS, GM involvement and neurodegeneration are associated with accelerated clinical worsening. Subpial demyelination and slowly expanding lesions are novel indicators of progressive MS. Conclusions and Relevance Diagnosis of PPMS is more challenging than diagnosis of RRMS. No qualitative clinical, immunological, histopathological, or neuroimaging features differentiate PPMS and SPMS; both are characterized by imaging findings reflecting neurodegeneration and are also impacted by aging and comorbidities. Unmet diagnostic needs include identification of MRI markers capable of distinguishing PPMS from RRMS and predicting the evolution of RRMS to SPMS. Integration of multiple parameters will likely be essential to achieve these aims.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Istituto di Ricovero e di Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Istituto di Ricovero e di Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VU University Medical Center (VUmc), Multiple Sclerosis Center Amsterdam, Amsterdam, the Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, United Kingdom
| | - Declan T Chard
- Nuclear Magnetic Resonance (NMR) Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, London, United Kingdom
- National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, United Kingdom
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, Ohio
| | - Claudio Gasperini
- Department of Neurology, San Camillo-Forlanini Hospital, Rome, Italy
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital and University of Basel, Basel, Switzerland
| | - Xavier Montalban
- Department of Neurology, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Hospital Vall d'Hebron, Autonomous University of Barcelona, Barcelona, Spain
- Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VU University Medical Center (VUmc), Multiple Sclerosis Center Amsterdam, Amsterdam, the Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
| | - Àlex Rovira
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital and Research Institute (VHIR), Autonomous University of Barcelona, Barcelona, Spain
| | - Ahmed T Toosy
- Nuclear Magnetic Resonance (NMR) Research Unit, Queen Square Multiple Sclerosis Centre, University College London Institute of Neurology, London, United Kingdom
| | - Anthony Traboulsee
- MS/Magnetic Resonance Imaging (MRI) Research Group, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Burcu Zeydan
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Brenda L Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Neurology and Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Istituto di Ricovero e di Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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15
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Monaco S, Nicholas R, Reynolds R, Magliozzi R. Intrathecal Inflammation in Progressive Multiple Sclerosis. Int J Mol Sci 2020; 21:ijms21218217. [PMID: 33153042 PMCID: PMC7663229 DOI: 10.3390/ijms21218217] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 10/29/2020] [Accepted: 10/31/2020] [Indexed: 01/05/2023] Open
Abstract
Progressive forms of multiple sclerosis (MS) are associated with chronic demyelination, axonal loss, neurodegeneration, cortical and deep gray matter damage, and atrophy. These changes are strictly associated with compartmentalized sustained inflammation within the brain parenchyma, the leptomeninges, and the cerebrospinal fluid. In progressive MS, molecular mechanisms underlying active demyelination differ from processes that drive neurodegeneration at cortical and subcortical locations. The widespread pattern of neurodegeneration is consistent with mechanisms associated with the inflammatory molecular load of the cerebrospinal fluid. This is at variance with gray matter demyelination that typically occurs at focal subpial sites, in the proximity of ectopic meningeal lymphoid follicles. Accordingly, it is possible that variations in the extent and location of neurodegeneration may be accounted for by individual differences in CSF flow, and by the composition of soluble inflammatory factors and their clearance. In addition, “double hit” damage may occur at sites allowing a bidirectional exchange between interstitial fluid and CSF, such as the Virchow–Robin spaces and the periventricular ependymal barrier. An important aspect of CSF inflammation and deep gray matter damage in MS involves dysfunction of the blood–cerebrospinal fluid barrier and inflammation in the choroid plexus. Here, we provide a comprehensive review on the role of intrathecal inflammation compartmentalized to CNS and non-neural tissues in progressive MS.
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Affiliation(s)
- Salvatore Monaco
- Department of Neurosciences, Biomedicine and Movements Sciences, University of Verona, 37134 Verona, Italy
- Correspondence: (S.M.); (R.M.)
| | - Richard Nicholas
- Department of Brain Sciences, Imperial College, Faculty of Medicine, London W12 ONN, UK; (R.N.); (R.R.)
| | - Richard Reynolds
- Department of Brain Sciences, Imperial College, Faculty of Medicine, London W12 ONN, UK; (R.N.); (R.R.)
| | - Roberta Magliozzi
- Department of Neurosciences, Biomedicine and Movements Sciences, University of Verona, 37134 Verona, Italy
- Department of Brain Sciences, Imperial College, Faculty of Medicine, London W12 ONN, UK; (R.N.); (R.R.)
- Correspondence: (S.M.); (R.M.)
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16
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Romero-Garcia R, Seidlitz J, Whitaker KJ, Morgan SE, Fonagy P, Dolan RJ, Jones PB, Goodyer IM, Suckling J, Vértes PE, Bullmore ET. Schizotypy-Related Magnetization of Cortex in Healthy Adolescence Is Colocated With Expression of Schizophrenia-Related Genes. Biol Psychiatry 2020; 88:248-259. [PMID: 32029217 PMCID: PMC7369635 DOI: 10.1016/j.biopsych.2019.12.005] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 11/21/2019] [Accepted: 12/03/2019] [Indexed: 12/03/2022]
Abstract
BACKGROUND Genetic risk is thought to drive clinical variation on a spectrum of schizophrenia-like traits, but the underlying changes in brain structure that mechanistically link genomic variation to schizotypal experience and behavior are unclear. METHODS We assessed schizotypy using a self-reported questionnaire and measured magnetization transfer as a putative microstructural magnetic resonance imaging marker of intracortical myelination in 68 brain regions in 248 healthy young people (14-25 years of age). We used normative adult brain gene expression data and partial least squares analysis to find the weighted gene expression pattern that was most colocated with the cortical map of schizotypy-related magnetization. RESULTS Magnetization was significantly correlated with schizotypy in the bilateral posterior cingulate cortex and precuneus (and for disorganized schizotypy, also in medial prefrontal cortex; all false discovery rate-corrected ps < .05), which are regions of the default mode network specialized for social and memory functions. The genes most positively weighted on the whole-genome expression map colocated with schizotypy-related magnetization were enriched for genes that were significantly downregulated in two prior case-control histological studies of brain gene expression in schizophrenia. Conversely, the most negatively weighted genes were enriched for genes that were transcriptionally upregulated in schizophrenia. Positively weighted (downregulated) genes were enriched for neuronal, specifically interneuronal, affiliations and coded a network of proteins comprising a few highly interactive "hubs" such as parvalbumin and calmodulin. CONCLUSIONS Microstructural magnetic resonance imaging maps of intracortical magnetization can be linked to both the behavioral traits of schizotypy and prior histological data on dysregulated gene expression in schizophrenia.
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Affiliation(s)
| | - Jakob Seidlitz
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kirstie J Whitaker
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Alan Turing Institute, London, United Kingdom
| | - Sarah E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, London, United Kingdom
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
| | - Ian M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Alan Turing Institute, London, United Kingdom; School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom
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17
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Reali C, Magliozzi R, Roncaroli F, Nicholas R, Howell OW, Reynolds R. B cell rich meningeal inflammation associates with increased spinal cord pathology in multiple sclerosis. Brain Pathol 2020; 30:779-793. [PMID: 32243032 PMCID: PMC8018043 DOI: 10.1111/bpa.12841] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/18/2019] [Accepted: 12/20/2019] [Indexed: 12/15/2022] Open
Abstract
Increased inflammation in the cerebral meninges is associated with extensive subpial cortical grey matter pathology in the forebrain and a more severe disease course in a substantial proportion of secondary progressive multiple sclerosis (SPMS) cases. It is not known whether this relationship extends to spinal cord pathology. We assessed the contribution of meningeal and parenchymal immune infiltrates to spinal cord pathology in SPMS cases characterized in the presence (F+) or absence (F-) of lymphoid-like structures in the forebrain meninges. Transverse cryosections of cervical, thoracic and lumbar cord of 22 SPMS and five control cases were analyzed for CD20+ B cells, CD4+ and CD8+ T cells, microglia/macrophages (IBA-1+), demyelination (myelin oligodendrocyte glycoprotein+) and axon density (neurofilament-H+). Lymphoid-like structures containing follicular dendritic cell networks and dividing B cells were seen in the spinal meninges of 3 out of 11 F+ SPMS cases. CD4+ and CD20+ cell counts were increased in F+ SPMS compared to F- SPMS and controls, whilst axon loss was greatest in motor and sensory tracts of the F+ SPMS cases (P < 0.01). The density of CD20+ B cells of the spinal leptomeninges correlated with CD4+ T cells and total B and T cells of the meninges; with the density of white matter perivascular CD20+ and CD4+ lymphocytes (P < 0.05); with white matter lesion area (P < 0.05); and the extent of axon loss (P < 0.05) in F+ SPMS cases only. We show that the presence of lymphoid-like structures in the forebrain is associated with a profound spinal cord pathology and local B cell rich meningeal inflammation associates with the extent of cord pathology. Our work supports a principal role for B cells in sustaining inflammation and tissue injury throughout the CNS in the progressive disease stage.
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Affiliation(s)
- Camilla Reali
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
- Merck Healthcare KGaADarmstadtGermany
| | - Roberta Magliozzi
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
- Department of Neuroscience, Biomedicine and MovementUniversity of VeronaVeronaItaly
| | - Federico Roncaroli
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
- Division of Neuroscience and Experimental PsychologyFaculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
- Manchester Academic Health Science CentreManchesterUK
| | - Richard Nicholas
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
| | - Owain W. Howell
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
- Institute for Life SciencesSwansea University Medical SchoolSwanseaUK
| | - Richard Reynolds
- Department of Brain SciencesFaculty of MedicineImperial CollegeLondonUK
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18
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Cassiano MT, Lanzillo R, Alfano B, Costabile T, Comerci M, Prinster A, Moccia M, Megna R, Morra VB, Quarantelli M, Brunetti A. Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis. NEUROIMAGE-CLINICAL 2020; 26:102201. [PMID: 32062567 PMCID: PMC7025083 DOI: 10.1016/j.nicl.2020.102201] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/13/2020] [Accepted: 01/28/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Regional analyses of markers of microstructural gray matter (GM) changes, including relaxation rates, have shown inconsistent correlations with physical and cognitive impairment in MS. OBJECTIVE To assess voxelwise the correlation of the R1 and R2 relaxation rates with the physical and cognitive impairment in MS. METHODS GM R1 and R2 relaxation rate maps were obtained in 241 relapsing-remitting MS patients by relaxometric segmentation of MRI studies. Correlations with the Expanded Disability Status Scale (EDSS) and the percentage of impaired cognitive test (Brief Repeatable Battery and Stroop Test, available in 186 patients) were assessed voxelwise, including voxel GM content as nuisance covariate to remove the effect of atrophy on the correlations. RESULTS Extensive clusters of inverse correlation between EDSS and R2 were detected throughout the brain, while inverse correlations with R1 were mostly limited to perirolandic and supramarginal cortices. Cognitive impairment correlated negatively with R1, and to a lesser extent with R2, in the middle frontal, mesial temporal, midcingulate and medial parieto-occipital cortices. CONCLUSION In relapsing-remitting MS patients, GM microstructural changes correlate diffusely with physical disability, independent of atrophy, with a preferential role of the sensorimotor cortices. Neuronal damage in the limbic system and dorsolateral prefrontal cortices correlates with cognitive dysfunction.
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Affiliation(s)
- Maria Teresa Cassiano
- Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini, 5, 80131 Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Bruno Alfano
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Teresa Costabile
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marco Comerci
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Anna Prinster
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Rosario Megna
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145 Naples, Italy.
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Via Pansini, 5, 80131 Naples, Italy
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19
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Rahmanzadeh R, Brück W, Minagar A, Sahraian MA. Multiple sclerosis pathogenesis: missing pieces of an old puzzle. Rev Neurosci 2019; 30:67-83. [PMID: 29883325 DOI: 10.1515/revneuro-2018-0002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Accepted: 03/30/2018] [Indexed: 11/15/2022]
Abstract
Traditionally, multiple sclerosis (MS) was considered to be a CD4 T cell-mediated CNS autoimmunity, compatible with experimental autoimmune encephalitis model, which can be characterized by focal lesions in the white matter. However, studies of recent decades revealed several missing pieces of MS puzzle and showed that MS pathogenesis is more complex than the traditional view and may include the following: a primary degenerative process (e.g. oligodendroglial pathology), generalized abnormality of normal-appearing brain tissue, pronounced gray matter pathology, involvement of innate immunity, and CD8 T cells and B cells. Here, we review these findings and discuss their implications in MS pathogenesis.
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Affiliation(s)
- Reza Rahmanzadeh
- MS Research Center, Neuroscience Institute, Tehran University of Medical Science, Department of Neurology, Sina Hospital, 1136746911 Tehran, Iran
| | - Wolfgang Brück
- Institute of Neuropathology, University Medical Center, D-37075 Göttingen, Germany
| | - Alireza Minagar
- Department of Neurology, LSU Health Sciences Center, Shreveport, LA 71130, USA
| | - Mohammad Ali Sahraian
- MS Research Center, Neuroscience Institute, Tehran University of Medical Science, Department of Neurology, Sina Hospital, 1136746911 Tehran, Iran.,Iranian Center for Neurological Research, Neuroscience Institute, Tehran University of Medical Science, 1136746890 Tehran, Iran
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20
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Brown JWL, Prados Carrasco F, Eshaghi A, Sudre CH, Button T, Pardini M, Samson RS, Ourselin S, Wheeler-Kingshott CAG, Jones JL, Coles AJ, Chard DT. Periventricular magnetisation transfer ratio abnormalities in multiple sclerosis improve after alemtuzumab. Mult Scler 2019; 26:1093-1101. [PMID: 31169059 DOI: 10.1177/1352458519852093] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND In multiple sclerosis (MS), disease effects on magnetisation transfer ratio (MTR) increase towards the ventricles. This periventricular gradient is evident shortly after first symptoms and is independent of white matter lesions. OBJECTIVE To explore if alemtuzumab, a peripherally acting disease-modifying treatment, modifies the gradient's evolution, and whether baseline gradients predict on-treatment relapses. METHODS Thirty-four people with relapsing-remitting MS underwent annual magnetic resonance imaging (MRI) scanning (19 receiving alemtuzumab (four scans each), 15 untreated (three scans each)). The normal-appearing white matter was segmented into concentric bands. Gradients were measured over the three bands nearest the ventricles. Mixed-effects models adjusted for age, gender, relapse rate, lesion number and brain parenchymal fraction compared the groups' baseline gradients and evolution. RESULTS Untreated, the mean MTR gradient increased (+0.030 pu/band/year) but decreased following alemtuzumab (-0.045 pu/band/year, p = 0.037). Within the alemtuzumab group, there were no significant differences in baseline lesion number (p = 0.568) nor brain parenchymal fraction (p = 0.187) between those who relapsed within 4 years (n = 4) and those who did not (n = 15). However, the baseline gradient was significantly different (p = 0.020). CONCLUSION Untreated, abnormal periventricular gradients worsen with time, but appear reversible with peripheral immunotherapy. Baseline gradients - but not lesion loads or brain volumes - may predict on-treatment relapses. Larger confirmatory studies are required.
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Affiliation(s)
- J William L Brown
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK; eHealth Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Arman Eshaghi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Tom Button
- Department of Neurology, York Hospital, York, UK
| | - Matteo Pardini
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Claudia Am Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Joanne L Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alasdair J Coles
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; National Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
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21
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Brown JWL, Chowdhury A, Kanber B, Prados Carrasco F, Eshaghi A, Sudre CH, Pardini M, Samson RS, van de Pavert SHP, Wheeler-Kingshott CG, Chard DT. Magnetisation transfer ratio abnormalities in primary and secondary progressive multiple sclerosis. Mult Scler 2019; 26:679-687. [DOI: 10.1177/1352458519841810] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: In relapse-onset multiple sclerosis (MS), tissue abnormality – as assessed with magnetisation transfer ratio (MTR) imaging – is greater in the outer cortical and inner periventricular layers. The cause of this remains unknown but meningeal inflammation has been implicated, particularly lymphoid follicles, which are seen in secondary progressive (SP) but not primary progressive (PP) MS. Cortical and periventricular MTR gradients might, therefore, differ in PPMS and SPMS if these follicles are responsible. Objective: We assessed cortical and periventricular MTR gradients in PPMS, and compared gradients between people with PPMS and SPMS. Methods: Using an optimised processing pipeline, periventricular normal-appearing white matter and cortical grey-matter MTR gradients were compared between 51 healthy controls and 63 people with progressive MS (28 PPMS, 35 SPMS). Results: The periventricular gradient was significantly shallower in healthy controls (0.122 percentage units (pu)/band) compared to PPMS (0.952 pu/band, p < 0.0001) and SPMS (1.360 pu/band, p < 0.0001). The cortical gradient was also significantly shallower in healthy controls (−2.860 pu/band) compared to PPMS (−3.214 pu/band, p = 0.038) and SPMS (−3.328 pu/band, p = 0.016). Conclusion: Abnormal periventricular and cortical MTR gradients occur in both PPMS and SPMS, suggesting comparable underlying pathological processes.
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Affiliation(s)
- James William L Brown
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Azmain Chowdhury
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/National Institute for Health Research (NIHR) Biomedical Research Centre, University College London Hospitals (UCLH), London, UK/Department of Clinical and Experimental Epilepsy, UCL Queen Square
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/eHealth Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Arman Eshaghi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Carole H Sudre
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, UK/Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK/School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Matteo Pardini
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Steven HP van de Pavert
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK
| | - Claudia Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy/Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, UK/National Institute for Health Research (NIHR) Biomedical Research Centre, University College London Hospitals (UCLH), London, UK
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22
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Filippi M, Brück W, Chard D, Fazekas F, Geurts JJG, Enzinger C, Hametner S, Kuhlmann T, Preziosa P, Rovira À, Schmierer K, Stadelmann C, Rocca MA. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 2019; 18:198-210. [DOI: 10.1016/s1474-4422(18)30451-4] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 10/22/2018] [Accepted: 11/12/2018] [Indexed: 12/12/2022]
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23
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Barritt AW, Gabel MC, Cercignani M, Leigh PN. Emerging Magnetic Resonance Imaging Techniques and Analysis Methods in Amyotrophic Lateral Sclerosis. Front Neurol 2018; 9:1065. [PMID: 30564192 PMCID: PMC6288229 DOI: 10.3389/fneur.2018.01065] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 11/22/2018] [Indexed: 12/17/2022] Open
Abstract
Objective markers of disease sensitive to the clinical activity, symptomatic progression, and underlying substrates of neurodegeneration are highly coveted in amyotrophic lateral sclerosis in order to more eloquently stratify the highly heterogeneous phenotype and facilitate the discovery of effective disease modifying treatments for patients. Magnetic resonance imaging (MRI) is a promising, non-invasive biomarker candidate whose acquisition techniques and analysis methods are undergoing constant evolution in the pursuit of parameters which more closely represent biologically-applicable tissue changes. Neurite Orientation Dispersion and Density Imaging (NODDI; a form of diffusion imaging), and quantitative Magnetization Transfer Imaging (qMTi) are two such emerging modalities which have each broadened the understanding of other neurological disorders and have the potential to provide new insights into structural alterations initiated by the disease process in ALS. Furthermore, novel neuroimaging data analysis approaches such as Event-Based Modeling (EBM) may be able to circumvent the requirement for longitudinal scanning as a means to comprehend the dynamic stages of neurodegeneration in vivo. Combining these and other innovative imaging protocols with more sophisticated techniques to analyse ever-increasing datasets holds the exciting prospect of transforming understanding of the biological processes and temporal evolution of the ALS syndrome, and can only benefit from multicentre collaboration across the entire ALS research community.
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Affiliation(s)
- Andrew W Barritt
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, United Kingdom.,Hurstwood Park Neurological Centre Haywards Heath, West Sussex, United Kingdom
| | - Matt C Gabel
- Department of Neuroscience, Trafford Centre for Biomedical Research Brighton and Sussex Medical School, Falmer, United Kingdom
| | - Mara Cercignani
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, United Kingdom
| | - P Nigel Leigh
- Hurstwood Park Neurological Centre Haywards Heath, West Sussex, United Kingdom.,Department of Neuroscience, Trafford Centre for Biomedical Research Brighton and Sussex Medical School, Falmer, United Kingdom
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24
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Tur C, Eshaghi A, Altmann DR, Jenkins TM, Prados F, Grussu F, Charalambous T, Schmidt A, Ourselin S, Clayden JD, Wheeler-Kingshott CAMG, Thompson AJ, Ciccarelli O, Toosy AT. Structural cortical network reorganization associated with early conversion to multiple sclerosis. Sci Rep 2018; 8:10715. [PMID: 30013173 PMCID: PMC6048099 DOI: 10.1038/s41598-018-29017-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 07/02/2018] [Indexed: 11/09/2022] Open
Abstract
Brain structural covariance networks (SCNs) based on pairwise statistical associations of cortical thickness data across brain areas reflect underlying physical and functional connections between them. SCNs capture the complexity of human brain cortex structure and are disrupted in neurodegenerative conditions. However, the longitudinal assessment of SCN dynamics has not yet been explored, despite its potential to unveil mechanisms underlying neurodegeneration. Here, we evaluated the changes of SCNs over 12 months in patients with a first inflammatory-demyelinating attack of the Central Nervous System and assessed their clinical relevance by comparing SCN dynamics of patients with and without conversion to multiple sclerosis (MS) over one year. All subjects underwent clinical and brain MRI assessments over one year. Brain cortical thicknesses for each subject and time point were used to obtain group-level between-area correlation matrices from which nodal connectivity metrics were obtained. Robust bootstrap-based statistical approaches (allowing sampling with replacement) assessed the significance of longitudinal changes. Patients who converted to MS exhibited significantly greater network connectivity at baseline than non-converters (p = 0.02) and a subsequent connectivity loss over time (p = 0.001-0.02), not observed in non-converters' network. These findings suggest SCN analysis is sensitive to brain tissue changes in early MS, reflecting clinically relevant aspects of the condition. However, this is preliminary work, indicated by the low sample sizes, and its results and conclusions should be treated with caution and confirmed with larger cohorts.
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Affiliation(s)
- C Tur
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.
| | - A Eshaghi
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London (UCL), London, WC1E 7JE, UK
| | - D R Altmann
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,Medical Statistics Department, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - T M Jenkins
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK
| | - F Prados
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, WC1E 7JE, UK
| | - F Grussu
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London (UCL), London, WC1E 7JE, UK
| | - T Charalambous
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK
| | - A Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - S Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, WC1E 7JE, UK
| | - J D Clayden
- UCL Great Ormond Street Institute of Child Health, UCL, London, WC1N 1EH, UK
| | - C A M G Wheeler-Kingshott
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,Brain MRI 3T Research Center, C. Mondino National Neurological Institute, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - A J Thompson
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - O Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK.,National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - A T Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College of London (UCL), London, WC1B 5EH, UK
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25
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Sled JG. Modelling and interpretation of magnetization transfer imaging in the brain. Neuroimage 2017; 182:128-135. [PMID: 29208570 DOI: 10.1016/j.neuroimage.2017.11.065] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 11/19/2017] [Accepted: 11/29/2017] [Indexed: 01/09/2023] Open
Abstract
Magnetization transfer contrast has yielded insight into brain tissue microstructure changes across the lifespan and in a range of disorders. This progress has been aided by the development of quantitative magnetization transfer imaging techniques able to extract intrinsic properties of the tissue that are independent of the specifics of the data acquisition. While the tissue properties extracted by these techniques do not map directly onto specific cellular structures or pathological processes, a growing body of work from animal models and histopathological correlations aids the in vivo interpretation of magnetization transfer properties of tissue. This review examines the biophysical models that have been developed to describe magnetization transfer contrast in tissue as well as the experimental evidence for the biological interpretation of magnetization transfer data in health and disease.
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Affiliation(s)
- John G Sled
- Hospital for Sick Children, Mouse Imaging Centre, Toronto, Ontario, Canada; Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
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26
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Mainero C, Louapre C. Unraveling cortical pathology in multiple sclerosis using the T1-/T2-weighted ratio? Ann Neurol 2017; 82:516-518. [PMID: 28976603 DOI: 10.1002/ana.25063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 09/29/2017] [Accepted: 10/02/2017] [Indexed: 11/09/2022]
Affiliation(s)
- Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA.,Harvard Medical School, Cambridge, MA
| | - Céline Louapre
- UPMC University Paris 06, UMR S 1127, and CNRS UMR 7225, and ICM, Paris, France.,APHP, Hôpital Pitié-Salpêtriere, Neurology Department, Paris, France
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27
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Kühn S, Düzel S, Eibich P, Krekel C, Wüstemann H, Kolbe J, Martensson J, Goebel J, Gallinat J, Wagner GG, Lindenberger U. In search of features that constitute an "enriched environment" in humans: Associations between geographical properties and brain structure. Sci Rep 2017; 7:11920. [PMID: 28931835 PMCID: PMC5607225 DOI: 10.1038/s41598-017-12046-7] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 08/22/2017] [Indexed: 12/30/2022] Open
Abstract
Enriched environments elicit brain plasticity in animals. In humans it is unclear which environment is enriching. Living in a city has been associated with increased amygdala activity in a stress paradigm, and being brought up in a city with increased pregenual anterior cingulate cortex (pACC) activity. We set out to identify geographical characteristics that constitute an enriched environment affecting the human brain. We used structural equation modelling on 341 older adults to establish three latent brain factors (amygdala, pACC and dorsolateral prefrontal cortex (DLPFC)) to test the effects of forest, urban green, water and wasteland around the home address. Our results reveal a significant positive association between the coverage of forest and amygdala integrity. We conclude that forests may have salutogenic effects on the integrity of the amygdala. Since cross-sectional data does not allow causal inference it could also be that individuals with high structural integrity choose to live closer to forest.
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Affiliation(s)
- Simone Kühn
- Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany. .,University Clinic Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany.
| | - Sandra Düzel
- Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany
| | - Peter Eibich
- German Institute for Economic Research, Mohrenstrasse 58, 10117, Berlin, Germany.,University of Oxfor The Health Economics Research Centre (HERC) Old Road Campus, Headington, Oxford, OX3 7LF, UK
| | - Christian Krekel
- German Institute for Economic Research, Mohrenstrasse 58, 10117, Berlin, Germany.,Paris School of Ecoß 48 Boulevard Jourdan, 75014, Paris, France.,Centre for Economic Performance, London School of Economics, Houghton Street, London, WC2A 2AE, UK
| | - Henry Wüstemann
- Technical University Berlin, Institute for Landscape Architecture and Environmental Planning Landscape Economics, Straße des 17. Juni 145, 10623, Berlin, Germany
| | - Jens Kolbe
- Technical University Berlin, Institute for Economics and Business Law, Econometrics and Business Statistics, Straße des 17. Juni 135, 10623, Berlin, Germany
| | - Johan Martensson
- Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany
| | - Jan Goebel
- German Institute for Economic Research, Mohrenstrasse 58, 10117, Berlin, Germany
| | - Jürgen Gallinat
- University Clinic Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany
| | - Gert G Wagner
- Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany.,University of Oxfor The Health Economics Research Centre (HERC) Old Road Campus, Headington, Oxford, OX3 7LF, UK.,Technical University Berlin, Institute for Economics and Business Law, Econometrics and Business Statistics, Straße des 17. Juni 135, 10623, Berlin, Germany
| | - Ulman Lindenberger
- Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195, Berlin, Germany.,European University Institute San Domenico, Fiesole, Italy
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28
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Louapre C, Govindarajan ST, Giannì C, Madigan N, Sloane JA, Treaba CA, Herranz E, Kinkel RP, Mainero C. Heterogeneous pathological processes account for thalamic degeneration in multiple sclerosis: Insights from 7 T imaging. Mult Scler 2017; 24:1433-1444. [PMID: 28803512 DOI: 10.1177/1352458517726382] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Thalamic degeneration impacts multiple sclerosis (MS) prognosis. OBJECTIVE To investigate heterogeneous thalamic pathology, its correlation with white matter (WM), cortical lesions and thickness, and as function of distance from cerebrospinal fluid (CSF). METHODS In 41 MS subjects and 17 controls, using 3 and 7 T imaging, we tested for (1) differences in thalamic volume and quantitative T2* (q-T2*) (2) globally and (3) within concentric bands originating from the CSF/thalamus interface; (4) the relation between thalamic, cortical, and WM metrics; and (5) the contribution of magnetic resonance imaging (MRI) metrics to clinical scores. We also assessed MS thalamic lesion distribution as a function of distance from CSF. RESULTS Thalamic lesions were mainly located next to the ventricles. Thalamic volume was decreased in MS versus controls ( p < 10-2); global q-T2* was longer in secondary progressive multiple sclerosis (SPMS) only ( p < 10-2), indicating myelin and/or iron loss. Thalamic atrophy and longer q-T2* correlated with WM lesion volume ( p < 0.01). In relapsing-remitting MS, q-T2* thalamic abnormalities were located next to the WM ( p < 0.01 (uncorrected), p = 0.09 (corrected)), while they were homogeneously distributed in SPMS. Cortical MRI metrics were the strongest predictors of clinical outcome. CONCLUSION Heterogeneous pathological processes affect the thalamus in MS. While focal lesions are likely mainly driven by CSF-mediated factors, overall thalamic degeneration develops in association with WM lesions.
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Affiliation(s)
- Céline Louapre
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Sindhuja T Govindarajan
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Costanza Giannì
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Nancy Madigan
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jacob A Sloane
- Harvard Medical School, Boston, MA, USA; Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Elena Herranz
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Revere P Kinkel
- Department of Neuroscience, University of California San Diego, San Diego, CA, USA
| | - Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
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29
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30
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Abstract
Several neuropathologic and imaging studies have consistently confirmed that multiple sclerosis affects both white (WM) and gray matter (GM) and that GM damage plays a key role in disability progression. However, differently from WM damage, the less inflammatory cell infiltration, the absence of significant blood-brain barrier damage, the low myelin density in upper cortical layers, as well as technical constraints, make the GM damage almost undetectable by means of conventional MR imaging.
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Affiliation(s)
- Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Policlinico GB Rossi, Piazzale LA Scuro 10, Verona 37134, Italy.
| | - Marco Castellaro
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/a, Padova 35135, Italy
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31
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Brown JWL, Pardini M, Brownlee WJ, Fernando K, Samson RS, Prados Carrasco F, Ourselin S, Gandini Wheeler-Kingshott CAM, Miller DH, Chard DT. An abnormal periventricular magnetization transfer ratio gradient occurs early in multiple sclerosis. Brain 2017; 140:387-398. [PMID: 28043954 DOI: 10.1093/brain/aww296] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Revised: 08/16/2016] [Accepted: 09/28/2016] [Indexed: 11/13/2022] Open
Abstract
In established multiple sclerosis, tissue abnormality-as assessed using magnetization transfer ratio-increases close to the lateral ventricles. We aimed to determine whether or not (i) these changes are present from the earliest clinical stages of multiple sclerosis; (ii) they occur independent of white matter lesions; and (iii) they are associated with subsequent conversion to clinically definite multiple sclerosis and disability. Seventy-one subjects had MRI scanning a median of 4.6 months after a clinically isolated optic neuritis (49 females, mean age 33.5 years) and were followed up clinically 2 and 5 years later. Thirty-seven healthy controls (25 females, mean age 34.4 years) were also scanned. In normal-appearing white matter, magnetization transfer ratio gradients were measured 1-5 mm and 6-10 mm from the lateral ventricles. In control subjects, magnetization transfer ratio was highest adjacent to the ventricles and decreased with distance from them; in optic neuritis, normal-appearing white matter magnetization transfer ratio was lowest adjacent to the ventricles, increased over the first 5 mm, and then paralleled control values. The magnetization transfer ratio gradient over 1-5 mm differed significantly between the optic neuritis and control groups [+0.059 percentage units/mm (pu/mm) versus -0.033 pu/mm, P = 0.010], and was significantly steeper in those developing clinically definite multiple sclerosis within 2 years compared to those who did not (0.132 pu/mm versus 0.016 pu/mm, P = 0.020). In multivariate binary logistic regression the magnetization transfer ratio gradient was independently associated with the development of clinically definite multiple sclerosis within 2 years (magnetization transfer ratio gradient odds ratio 61.708, P = 0.023; presence of T2 lesions odds ratio 8.500, P = 0.071). At 5 years, lesional measures overtook magnetization transfer ratio gradients as significant predictors of conversion to multiple sclerosis. The magnetization transfer ratio gradient was not significantly affected by the presence of brain lesions [T2 lesions (P = 0.918), periventricular T2 lesions (P = 0.580) or gadolinium-enhancing T1 lesions (P = 0.724)]. The magnetization transfer ratio gradient also correlated with Expanded Disability Status Scale score 5 years later (Spearman r = 0.313, P = 0.027). An abnormal periventricular magnetization transfer ratio gradient occurs early in multiple sclerosis, is clinically relevant, and may arise from one or more mechanisms that are at least partly independent of lesion formation.
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Affiliation(s)
- J William L Brown
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Department of Clinical Neurosciences, University of Cambridge, Box 165, Cambridge Biomedical Campus, Cambridge, UK
| | - Matteo Pardini
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Wallace J Brownlee
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK
| | - Kryshani Fernando
- Department of Neurology, Royal Free Hospital, Pond Street, London, UK
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK.,Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,Brain MRI 3T Center, C. Mondino National Neurological Institute, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - David H Miller
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London (UCL) Institute of Neurology, London, UK .,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
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32
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Rudko DA, Derakhshan M, Maranzano J, Nakamura K, Arnold DL, Narayanan S. Delineation of cortical pathology in multiple sclerosis using multi-surface magnetization transfer ratio imaging. NEUROIMAGE-CLINICAL 2016; 12:858-868. [PMID: 27872808 PMCID: PMC5107650 DOI: 10.1016/j.nicl.2016.10.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Revised: 09/23/2016] [Accepted: 10/11/2016] [Indexed: 01/06/2023]
Abstract
The purpose of our study was to evaluate the utility of measurements of cortical surface magnetization transfer ratio (csMTR) on the inner, mid and outer cortical boundaries as clinically accessible biomarkers of cortical gray matter pathology in multiple sclerosis (MS). Twenty-five MS patients and 12 matched controls were recruited from the MS Clinic of the Montreal Neurological Institute. Anatomical and magnetization transfer ratio (MTR) images were acquired using 3 Tesla MRI at baseline and two-year time-points. MTR maps were smoothed along meshes representing the inner, mid and outer neocortical boundaries. To evaluate csMTR reductions suggestive of sub-pial demyelination in MS patients, a mixed model analysis was carried out at both the individual vertex level and in anatomically parcellated brain regions. Our results demonstrate that focal areas of csMTR reduction are most prevalent along the outer cortical surface in the superior temporal and posterior cingulate cortices, as well as in the cuneus and precentral gyrus. Additionally, age regression analysis identified that reductions of csMTR in MS patients increase with age but appear to hit a plateau in the outer caudal anterior cingulate, as well as in the precentral and postcentral cortex. After correction for the naturally occurring gradient in cortical MTR, the difference in csMTR between the inner and outer cortex in focal areas in the brains of MS patients correlated with clinical disability. Overall, our findings support multi-surface analysis of csMTR as a sensitive marker of cortical sub-pial abnormality indicative of demyelination in MS patients. Novel cortical MTR analysis identifies areas of sub-pial abnormality in MS patients. A greater area of sub-pial abnormality in MS exists on the outer cortical layer. Cortical regions most affected were involved in executive function and processing speed. Normalized differences between outer and inner cortex MTR correlate with EDSS in MS. This technique can be applied for clinical trials at the MRI field strength of 3 T.
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Affiliation(s)
- David A Rudko
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Mishkin Derakhshan
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Josefina Maranzano
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue Cleveland, OH 44195, United States
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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33
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Pardini M, Sudre CH, Prados F, Yaldizli Ö, Sethi V, Muhlert N, Samson RS, van de Pavert SH, Cardoso MJ, Ourselin S, Gandini Wheeler-Kingshott CAM, Miller DH, Chard DT. Relationship of grey and white matter abnormalities with distance from the surface of the brain in multiple sclerosis. J Neurol Neurosurg Psychiatry 2016; 87:1212-1217. [PMID: 27601434 DOI: 10.1136/jnnp-2016-313979] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 08/14/2016] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To assess the association between proximity to the inner (ventricular and aqueductal) and outer (pial) surfaces of the brain and the distribution of normal appearing white matter (NAWM) and grey matter (GM) abnormalities, and white matter (WM) lesions, in multiple sclerosis (MS). METHODS 67 people with relapse-onset MS and 30 healthy controls were included in the study. Volumetric T1 images and high-resolution (1 mm3) magnetisation transfer ratio (MTR) images were acquired and segmented into 12 bands between the inner and outer surfaces of the brain. The first and last bands were discarded to limit partial volume effects with cerebrospinal fluid. MTR values were computed for all bands in supratentorial NAWM, cerebellar NAWM and brainstem NA tissue, and deep and cortical GM. Band WM lesion volumes were also measured. RESULTS Proximity to the ventricular surfaces was associated with progressively lower MTR values in the MS group but not in controls in supratentorial and cerebellar NAWM, brainstem NA and in deep and cortical GM. The density of WM lesions was associated with proximity to the ventricles only in the supratentorial compartment, and no link was found with distance from the pial surfaces. CONCLUSIONS In MS, MTR abnormalities in NAWM and GM are related to distance from the inner and outer surfaces of the brain, and this suggests that there is a common factor underlying their spatial distribution. A similar pattern was not found for WM lesions, raising the possibility that different factors promote their formation.
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Affiliation(s)
- Matteo Pardini
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Carole H Sudre
- Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Ferran Prados
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Özgür Yaldizli
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Varun Sethi
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK
| | - Nils Muhlert
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK School of Psychology and Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK School of Psychological Sciences, University of Manchester, Manchester UK
| | - Rebecca S Samson
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK
| | - Steven H van de Pavert
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK
| | - M Jorge Cardoso
- Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Sebastien Ourselin
- Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Brain MRI 3T Center, C. Mondino National Neurological Institute, Pavia, Italy Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - David H Miller
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Declan T Chard
- Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
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34
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Leocani L, Rocca MA, Comi G. MRI and neurophysiological measures to predict course, disability and treatment response in multiple sclerosis. Curr Opin Neurol 2016; 29:243-53. [DOI: 10.1097/wco.0000000000000333] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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35
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Gracien RM, Jurcoane A, Wagner M, Reitz SC, Mayer C, Volz S, Hof SM, Fleischer V, Droby A, Steinmetz H, Groppa S, Hattingen E, Deichmann R, Klein JC. Multimodal quantitative MRI assessment of cortical damage in relapsing-remitting multiple sclerosis. J Magn Reson Imaging 2016; 44:1600-1607. [DOI: 10.1002/jmri.25297] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 04/19/2016] [Indexed: 11/05/2022] Open
Affiliation(s)
- René-Maxime Gracien
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Alina Jurcoane
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Marlies Wagner
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Sarah C. Reitz
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Christoph Mayer
- Department of Neurology; Goethe University; Frankfurt/Main Germany
| | - Steffen Volz
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Stephanie-Michelle Hof
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Vinzenz Fleischer
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | - Amgad Droby
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | | | - Sergiu Groppa
- Department of Neurology; Johannes Gutenberg University; Mainz Germany
- Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN); Johannes Gutenberg-University; Mainz Germany
| | - Elke Hattingen
- Department of Neuroradiology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Ralf Deichmann
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
| | - Johannes C. Klein
- Department of Neurology; Goethe University; Frankfurt/Main Germany
- Brain Imaging Center; Goethe University; Frankfurt/Main Germany
- Nuffield Department of Clinical Neurosciences; University of Oxford; UK
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36
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Rimkus CDM, Steenwijk MD, Barkhof F. Causes, effects and connectivity changes in MS-related cognitive decline. Dement Neuropsychol 2016; 10:2-11. [PMID: 29213424 PMCID: PMC5674907 DOI: 10.1590/s1980-57642016dn10100002] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency.
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Affiliation(s)
- Carolina de Medeiros Rimkus
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands and Department of Physics and Medical technology, Neuroscience campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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37
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Brown JWL, Chard DT. The role of MRI in the evaluation of secondary progressive multiple sclerosis. Expert Rev Neurother 2016; 16:157-71. [PMID: 26692498 DOI: 10.1586/14737175.2016.1134323] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Magnetic resonance imaging already has an established role in the diagnosis of multiple sclerosis, but it also has the potential to provide prognostic information, and to monitor [corrected] disease progression in clinical trials and practice. Magnetic resonance imaging measures are increasingly being used as the primary outcome in early phase clinical trials of immunomodulatory therapies (for example brain white matter lesion counts or volumes, and gadolinium contrast enhancing lesions) and putatively neuroprotective agents (for example measures of whole brain atrophy), and trials of agents that promote remyelination are also likely to follow suit. In this review we consider the use of magnetic resonance imaging measures as predictors and markers of disease progression in multiple sclerosis, and explore possible future directions in this rapidly developing field.
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Affiliation(s)
- J William L Brown
- a Department of Clinical Neurosciences , University of Cambridge , Cambridge , UK.,b NMR Research Unit, Queen Square Multiple Sclerosis Centre, Institute of Neurology , University College London (UCL) , London , UK
| | - Declan T Chard
- b NMR Research Unit, Queen Square Multiple Sclerosis Centre, Institute of Neurology , University College London (UCL) , London , UK.,c Biomedical Research Centre, National Institute for Health Research (NIHR) , University College London Hospitals (UCLH) , London , UK
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38
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Jonkman LE, Fleysher L, Steenwijk MD, Koeleman JA, de Snoo TP, Barkhof F, Inglese M, Geurts JJ. Ultra-high field MTR and qR2* differentiates subpial cortical lesions from normal-appearing gray matter in multiple sclerosis. Mult Scler 2015; 22:1306-14. [PMID: 26672996 DOI: 10.1177/1352458515620499] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Accepted: 11/11/2015] [Indexed: 01/14/2023]
Abstract
BACKGROUND Cortical gray matter (GM) demyelination is frequent and clinically relevant in multiple sclerosis (MS). Quantitative magnetic resonance imaging (qMRI) sequences such as magnetization transfer ratio (MTR) and quantitative R2* (qR2*) can capture pathological subtleties missed by conventional magnetic resonance imaging (MRI) sequences. Although differences in MTR and qR2* have been reported between lesional and non-lesional tissue, differences between lesion types or lesion types and myelin density matched normal-appearing gray matter (NAGM) have not been found or investigated. OBJECTIVE Identify quantitative differences in histopathologically verified GM lesion types and matched NAGM at ultra-high field strength. METHODS Using 7T post-mortem MRI, MRI lesions were marked on T2 images and co-registered to the calculated MTR and qR2* maps for further evaluation. In all, 15 brain slices were collected, containing a total of 74 cortical GM lesions and 45 areas of NAGM. RESULTS Intracortical lesions had lower MTR and qR2* values compared to NAGM. Type I lesions showed lower MTR than type III lesions. Type III lesions showed lower MTR than matched NAGM, and type I and IV lesions showed lower qR2* than matched NAGM. CONCLUSION qMRI at 7T can provide additional information on extent of cortical pathology, especially concerning subpial lesions. This may be relevant for monitoring disease progression and potential treatment effects.
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Affiliation(s)
- Laura E Jonkman
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Lazar Fleysher
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Martijn D Steenwijk
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands/Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Jan A Koeleman
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Teun-Pieter de Snoo
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA/Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA/Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Jeroen Jg Geurts
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
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39
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Enzinger C, Barkhof F, Ciccarelli O, Filippi M, Kappos L, Rocca MA, Ropele S, Rovira À, Schneider T, de Stefano N, Vrenken H, Wheeler-Kingshott C, Wuerfel J, Fazekas F. Nonconventional MRI and microstructural cerebral changes in multiple sclerosis. Nat Rev Neurol 2015; 11:676-86. [PMID: 26526531 DOI: 10.1038/nrneurol.2015.194] [Citation(s) in RCA: 85] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
MRI has become the most important paraclinical tool for diagnosing and monitoring patients with multiple sclerosis (MS). However, conventional MRI sequences are largely nonspecific in the pathology they reveal, and only provide a limited view of the complex morphological changes associated with MS. Nonconventional MRI techniques, such as magnetization transfer imaging (MTI), diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI) promise to complement existing techniques by revealing more-specific information on microstructural tissue changes. Past years have witnessed dramatic advances in the acquisition and analysis of such imaging data, and numerous studies have used these tools to probe tissue alterations associated with MS. Other MRI-based techniques-such as myelin-water imaging, (23)Na imaging, magnetic resonance elastography and magnetic resonance perfusion imaging-might also shed new light on disease-associated changes. This Review summarizes the rapid technical progress in the use of MRI in patients with MS, with a focus on nonconventional structural MRI. We critically discuss the present utility of nonconventional MRI in MS, and provide an outlook on future applications, including clinical practice. This information should allow appropriate selection of advanced MRI techniques, and facilitate their use in future studies of this disease.
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Affiliation(s)
- Christian Enzinger
- Division of Neuroradiology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria.,Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Frederik Barkhof
- VU University MS Center Amsterdam, Department of Radiology and Nuclear Medicine and Department of Physics &Medical Technology, VU University Medical Center, Netherlands
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, University College London Institute of Neurology, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Italy
| | - Ludwig Kappos
- Department of Neurology, University of Basel, Switzerland
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Italy
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Àlex Rovira
- Magnetic Resonance Unit, Cemcat, Hospital Vall d'Hebron, Autonomous University of Barcelona, Spain
| | - Torben Schneider
- NMR Research Unit, Queen Square MS Centre, University College London Institute of Neurology, UK
| | - Nicola de Stefano
- Department of Neurological and Behavioural Sciences, University of Siena, Italy
| | - Hugo Vrenken
- VU University MS Center Amsterdam, Department of Radiology and Nuclear Medicine and Department of Physics &Medical Technology, VU University Medical Center, Netherlands
| | | | - Jens Wuerfel
- Medical Image Analysis Center, University Hospital Basel, Switzerland
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria
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40
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Jonkman LE, Klaver R, Fleysher L, Inglese M, Geurts JJG. Ultra-High-Field MRI Visualization of Cortical Multiple Sclerosis Lesions with T2 and T2*: A Postmortem MRI and Histopathology Study. AJNR Am J Neuroradiol 2015; 36:2062-7. [PMID: 26228878 DOI: 10.3174/ajnr.a4418] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2015] [Accepted: 04/02/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE At 7T MR imaging, T2*-weighted gradient echo has been shown to provide high-resolution anatomic images of gray matter lesions. However, few studies have verified T2*WI lesions histopathologically or compared them with more standard techniques at ultra-high-field strength. This study aimed to determine the sensitivity of T2WI and T2*WI sequences for detecting cortical GM lesions in MS. MATERIALS AND METHODS At 7T, 2D multiecho spin-echo T2WI and 3D gradient-echo T2*WI were acquired from 27 formalin-fixed coronal hemispheric brain sections of 15 patients and 4 healthy controls. Proteolipid-stained tissue sections (8 μm) were matched to the corresponding MR images, and lesions were manually scored on both MR imaging sequences (blinded to histopathology) and tissue sections (blinded to MR imaging). The sensitivity of MR imaging sequences for GM lesion types and white matter lesions was calculated. An unblinded retrospective scoring was also performed. RESULTS If all cortical GM lesions were taken into account, the T2WI sequence detected slightly more lesions than the T2*WI sequence: 28% and 16%, respectively (P = .054). This difference disappeared when only intracortical lesions were considered. When histopathologic information (type, location) was revealed to the reader, the sensitivity went up to 84% (T2WI) and 85% (T2*WI) (not significant). Furthermore, the false-positive rate was 8.6% for the T2WI and 10.5% for the T2*WI sequence. CONCLUSIONS There is no strong advantage of the T2*WI sequence compared with a conventional T2WI sequence in the detection of cortical lesions at 7T. Retrospectively, a high percentage of lesions could be detected with both sequences. However, many lesions are still missed prospectively. This could possibly be minimized with better a priori observer training.
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Affiliation(s)
- L E Jonkman
- From the Department of Anatomy and Neurosciences (L.E.J., R.K., J.J.G.G.), VU University Medical Center, Amsterdam, the Netherlands
| | - R Klaver
- From the Department of Anatomy and Neurosciences (L.E.J., R.K., J.J.G.G.), VU University Medical Center, Amsterdam, the Netherlands
| | | | - M Inglese
- Departments of Radiology (L.F., M.I.) Neurology (M.I.) Neurosciences (M.I.), Mount Sinai School of Medicine, New York, New York Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.I.), University of Genoa, Genoa, Italy
| | - J J G Geurts
- From the Department of Anatomy and Neurosciences (L.E.J., R.K., J.J.G.G.), VU University Medical Center, Amsterdam, the Netherlands
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41
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Amann M, Papadopoulou A, Andelova M, Magon S, Mueller-Lenke N, Naegelin Y, Stippich C, Radue EW, Bieri O, Kappos L, Sprenger T. Magnetization transfer ratio in lesions rather than normal-appearing brain relates to disability in patients with multiple sclerosis. J Neurol 2015; 262:1909-17. [PMID: 26041614 DOI: 10.1007/s00415-015-7793-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Revised: 05/20/2015] [Accepted: 05/21/2015] [Indexed: 11/24/2022]
Abstract
Magnetization transfer ratio (MTR) is a semi-quantitative measure that seems to correlate with the degree of myelin loss and generally tissue destruction in multiple sclerosis (MS). Our objective was to comprehensively assess the MTR of lesions and normal appearing (NA) tissue separately in the white matter (WM), the cortex, the thalamus and the basal ganglia (BG) and determine their relative contribution to disability. In this cross-sectional study 71 patients were included (59 with relapsing-remitting MS, 12 with secondary progressive MS). We used a three-dimensional MTR sequence with high spatial resolution, based on balanced steady-state free precession. Mean MTR was calculated for lesions and NA tissue separately for each tissue type. Lesional MTR was lower than normal-appearing MTR in WM, cortex and thalamus. In the regression analysis, MTR of cortical lesions (β = -0.23, p = 0.05) and MTR of WML (β = -0.21, p = 0.08) were related by trend to the expanded disability status scale. MTR of WML significantly predicted the paced auditory serial-addition test (β = 0.35, p = 0.004). MTR of normal-appearing tissue did not relate to any outcome. Our results suggest that MTR of lesions in the white matter and cortex rather than of normal-appearing tissue relates to disability in patients with MS.
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Affiliation(s)
- Michael Amann
- Department of Neurology, University Hospital Basel, Basel, Switzerland
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42
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Muhlert N, Sethi V, Cipolotti L, Haroon H, Parker GJM, Yousry T, Wheeler-Kingshott C, Miller D, Ron M, Chard D. The grey matter correlates of impaired decision-making in multiple sclerosis. J Neurol Neurosurg Psychiatry 2015; 86:530-6. [PMID: 25006208 PMCID: PMC4413680 DOI: 10.1136/jnnp-2014-308169] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 06/15/2014] [Indexed: 11/04/2022]
Abstract
OBJECTIVE People with multiple sclerosis (MS) have difficulties with decision-making but it is unclear if this is due to changes in impulsivity, risk taking, deliberation or risk adjustment, and how this relates to brain pathology. METHODS We assessed these aspects of decision-making in 105 people with MS and 43 healthy controls. We used a novel diffusion MRI method, diffusion orientational complexity (DOC), as an index of grey matter pathology in regions associated with decision-making and also measured grey matter tissue volumes and white matter lesion volumes. RESULTS People with MS showed less adjustment to risk and slower decision-making than controls. Moreover, impaired decision-making correlated with reduced executive function, memory and processing speed. Decision-making impairments were most prevalent in people with secondary progressive MS. They were seen in patients with cognitive impairment and those without cognitive impairment. On diffusion MRI, people with MS showed DOC changes in all regions except the occipital cortex, relative to controls. Risk adjustment correlated with DOC in the hippocampi and deliberation time with DOC in the medial prefrontal, middle frontal gyrus, anterior cingulate and caudate parcellations and with white matter lesion volumes. CONCLUSIONS These data clarify the features of decision-making deficits in MS, and provide the first evidence that they relate to grey and white matter abnormalities seen using MRI.
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Affiliation(s)
- Nils Muhlert
- NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK School of Psychology and Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Varun Sethi
- NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Lisa Cipolotti
- Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Hamied Haroon
- Faculty of Medical & Human Sciences, Centre for Imaging Sciences, Biomedical Imaging Institute, The University of Manchester, Manchester, UK
| | - Geoff J M Parker
- Faculty of Medical & Human Sciences, Centre for Imaging Sciences, Biomedical Imaging Institute, The University of Manchester, Manchester, UK
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - David Miller
- NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Maria Ron
- NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Declan Chard
- NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
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43
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Advanced imaging tools to investigate multiple sclerosis pathology. Presse Med 2015; 44:e159-67. [DOI: 10.1016/j.lpm.2015.02.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 02/23/2015] [Indexed: 12/26/2022] Open
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Liu Z, Pardini M, Yaldizli Ö, Sethi V, Muhlert N, Wheeler-Kingshott CAM, Samson RS, Miller DH, Chard DT. Magnetization transfer ratio measures in normal-appearing white matter show periventricular gradient abnormalities in multiple sclerosis. Brain 2015; 138:1239-46. [PMID: 25823475 DOI: 10.1093/brain/awv065] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2014] [Accepted: 01/17/2015] [Indexed: 01/27/2023] Open
Abstract
In multiple sclerosis, there is increasing evidence that demyelination, and neuronal damage occurs preferentially in cortical grey matter next to the outer surface of the brain. It has been suggested that this may be due to the effects of pathology outside the brain parenchyma, in particular meningeal inflammation or through cerebrospinal fluid mediated factors. White matter lesions are often located adjacent to the ventricles of the brain, suggesting the possibility of a similar outside-in pathogenesis, but an investigation of the relationship of periventricular normal-appearing white matter abnormalities with distance from the ventricles has not previously been undertaken. The present study investigates this relationship in vivo using quantitative magnetic resonance imaging and compares the abnormalities between secondary progressive and relapsing remitting multiple sclerosis. Forty-three patients with relapsing remitting and 28 with secondary progressive multiple sclerosis, and 38 healthy control subjects were included in this study. T1-weighted volumetric, magnetization transfer and proton density/T2-weighted scans were acquired for all subjects. From the magnetization transfer data, magnetization transfer ratio maps were prepared. White matter tissue masks were derived from SPM8 segmentations of the T1-weighted images. Normal-appearing white matter masks were generated by subtracting white matter lesions identified on the proton density/T2 scan, and a two-voxel perilesional ring, from the SPM8 derived white matter masks. White matter was divided in concentric bands, each ∼1-mm thick, radiating from the ventricles toward the cortex. The first periventricular band was excluded from analysis to mitigate partial volume effects, and normal-appearing white matter and lesion magnetization transfer ratio values were then computed for the 10 bands nearest to the ventricles. Compared with controls, magnetization transfer ratio in the normal-appearing white matter bands was significantly lower in patients with multiple sclerosis. In controls, magnetization transfer ratio was highest in the band adjacent to the ventricles and declined with increasing distance from the ventricles. In the multiple sclerosis groups, relative to controls, reductions in magnetization transfer ratio were greater in the secondary progressive multiple sclerosis compared with relapsing remitting multiple sclerosis group, and these reductions were greatest next to the ventricles and became smaller with distance from them. White matter lesion magnetization transfer ratio reductions were also more apparent adjacent to the ventricle and decreased with distance from the ventricles in both the relapsing remitting and secondary progressive multiple sclerosis groups. These findings suggest that in people with multiple sclerosis, and more so in secondary progressive than relapsing remitting multiple sclerosis, tissue structural abnormalities in normal-appearing white matter and white matter lesions are greatest near the ventricles. This would be consistent with a cerebrospinal fluid or ependymal mediated pathogenesis.
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Affiliation(s)
- Zheng Liu
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 2 Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Matteo Pardini
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 3 Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Özgür Yaldizli
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 4 Multiple Sclerosis Centre, Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Varun Sethi
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Nils Muhlert
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 5 School of Psychology and Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Claudia A M Wheeler-Kingshott
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Rebecca S Samson
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - David H Miller
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 6 National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
| | - Declan T Chard
- 1 Queen Square Multiple Sclerosis Centre, NMR Research Unit, Department of Neuroinflammation, UCL Institute of Neurology, London, UK 6 National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, UK
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Enzinger C, Fazekas F. Measuring Gray Matter and White Matter Damage in MS: Why This is Not Enough. Front Neurol 2015; 6:56. [PMID: 25852635 PMCID: PMC4362212 DOI: 10.3389/fneur.2015.00056] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 02/27/2015] [Indexed: 01/06/2023] Open
Affiliation(s)
- Christian Enzinger
- Department of Neurology, Medical University of Graz , Graz , Austria ; Division of Neuroradiology, Department of Radiology, Medical University of Graz , Graz , Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz , Graz , Austria
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47
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Freedman MS, Abdoli M. Evaluating response to disease-modifying therapy in relapsing multiple sclerosis. Expert Rev Neurother 2015; 15:407-23. [DOI: 10.1586/14737175.2015.1023711] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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48
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Mainero C, Louapre C, Govindarajan ST, Giannì C, Nielsen AS, Cohen-Adad J, Sloane J, Kinkel RP. A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging. ACTA ACUST UNITED AC 2015; 138:932-45. [PMID: 25681411 DOI: 10.1093/brain/awv011] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
We used a surface-based analysis of T2* relaxation rates at 7 T magnetic resonance imaging, which allows sampling quantitative T2* throughout the cortical width, to map in vivo the spatial distribution of intracortical pathology in multiple sclerosis. Ultra-high resolution quantitative T2* maps were obtained in 10 subjects with clinically isolated syndrome/early multiple sclerosis (≤ 3 years disease duration), 18 subjects with relapsing-remitting multiple sclerosis (≥ 4 years disease duration), 13 subjects with secondary progressive multiple sclerosis, and in 17 age-matched healthy controls. Quantitative T2* maps were registered to anatomical cortical surfaces for sampling T2* at 25%, 50% and 75% depth from the pial surface. Differences in laminar quantitative T2* between each patient group and controls were assessed using general linear model (P < 0.05 corrected for multiple comparisons). In all 41 multiple sclerosis cases, we tested for associations between laminar quantitative T2*, neurological disability, Multiple Sclerosis Severity Score, cortical thickness, and white matter lesions. In patients, we measured, T2* in intracortical lesions and in the intracortical portion of leukocortical lesions visually detected on 7 T scans. Cortical lesional T2* was compared with patients' normal-appearing cortical grey matter T2* (paired t-test) and with mean cortical T2* in controls (linear regression using age as nuisance factor). Subjects with multiple sclerosis exhibited relative to controls, independent from cortical thickness, significantly increased T2*, consistent with cortical myelin and iron loss. In early disease, T2* changes were focal and mainly confined at 25% depth, and in cortical sulci. In later disease stages T2* changes involved deeper cortical laminae, multiple cortical areas and gyri. In patients, T2* in intracortical and leukocortical lesions was increased compared with normal-appearing cortical grey matter (P < 10(-10) and P < 10(-7)), and mean cortical T2* in controls (P < 10(-5) and P < 10(-6)). In secondary progressive multiple sclerosis, T2* in normal-appearing cortical grey matter was significantly increased relative to controls (P < 0.001). Laminar T2* changes may, thus, result from cortical pathology within and outside focal cortical lesions. Neurological disability and Multiple Sclerosis Severity Score correlated each with the degree of laminar quantitative T2* changes, independently from white matter lesions, the greatest association being at 25% depth, while they did not correlate with cortical thickness and volume. These findings demonstrate a gradient in the expression of cortical pathology throughout stages of multiple sclerosis, which was associated with worse disability and provides in vivo evidence for the existence of a cortical pathological process driven from the pial surface.
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Affiliation(s)
- Caterina Mainero
- 1 A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA
| | - Céline Louapre
- 1 A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA
| | - Sindhuja T Govindarajan
- 1 A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Costanza Giannì
- 1 A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA
| | - A Scott Nielsen
- 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA 3 Beth Israel Deaconess Medical Center, Boston, MA, USA 4 Virginia Mason Medical Center, Seattle, WA, USA
| | - Julien Cohen-Adad
- 1 A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA 5 Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Jacob Sloane
- 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA 3 Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Revere P Kinkel
- 2 Harvard Medical School, 25 Shattuck Street, Boston, MA 02115,USA 3 Beth Israel Deaconess Medical Center, Boston, MA, USA 6 University of California San Diego, USA
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Kearney H, Yiannakas MC, Samson RS, Wheeler-Kingshott CAM, Ciccarelli O, Miller DH. Investigation of magnetization transfer ratio-derived pial and subpial abnormalities in the multiple sclerosis spinal cord. Brain 2014; 137:2456-68. [DOI: 10.1093/brain/awu171] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
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