The evolving contribution of MRI measures towards the prediction of secondary progressive multiple sclerosis.

BACKGROUND: In multiple sclerosis (MS), both lesion accrual and brain atrophy predict clinical outcomes. However, it is unclear whether these prognostic features are equally relevant throughout the course of MS. Among 103 participants recruited following a clinically isolated syndrome (CIS) and followed up over 30 years, we explored (1) whether white matter lesions were prognostically more relevant earlier and brain atrophy later in the disease course towards development of secondary progressive (SP) disease; (2) if so, when the balance in prognostic contribution shifts and (3) whether optimised prognostic models predicting SP disease should include different features dependent on disease duration. METHODS: Binary logistic regression models were built using age, gender, brain lesion counts and locations, and linear atrophy measures (third ventricular width and medullary width) at each time point up to 20 years, using either single time point data alone or adjusted for baseline measures. RESULTS: By 30 years, 27 participants remained CIS while 60 had MS (26 SPMS and 16 MS-related death). Lesions counts were prognostically significant from baseline and at all later time points while linear atrophy measure models reached significance from 5 years. When adjusted for baseline, in combined MRI models including lesion count and linear atrophy measures, only lesion counts were significant predictors. In combined models including relapse measures, Expanded Disability Status Scale scores and MRI measures, only infratentorial lesions were significant predictors throughout. CONCLUSIONS: While SPMS progression is associated with brain atrophy, in predictive models only infratentorial lesions were consistently prognostically significant.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection.

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Networks of microstructural damage predict disability in multiple sclerosis.

BACKGROUND: Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. METHODS: We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. RESULTS: We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). CONCLUSIONS: GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials.

Surface-in pathology in multiple sclerosis: a new view on pathogenesis?

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.

Cortical involvement determines impairment 30 years after a clinically isolated syndrome.

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.

A 30-Year Clinical and Magnetic Resonance Imaging Observational Study of Multiple Sclerosis and Clinically Isolated Syndromes.

OBJECTIVE: Clinical outcomes in multiple sclerosis (MS) are highly variable. We aim to determine the long-term clinical outcomes in MS, and to identify early prognostic features of these outcomes. METHODS: One hundred thirty-two people presenting with a clinically isolated syndrome were prospectively recruited between 1984 and 1987, and followed up clinically and radiologically 1, 5, 10, 14, 20, and now 30 years later. All available notes and magnetic resonance imaging scans were reviewed, and MS was defined according to the 2010 McDonald criteria. RESULTS: Clinical outcome data were obtained in 120 participants at 30 years. Eighty were known to have developed MS by 30 years. Expanded Disability Status Scale (EDSS) scores were available in 107 participants, of whom 77 had MS; 32 (42%) remained fully ambulatory (EDSS scores ≤3.5), all of whom had relapsing-remitting MS (RRMS), 3 (4%) had RRMS and EDSS scores >3.5, 26 (34%) had secondary progressive MS (all had EDSS scores >3.5), and MS contributed to death in 16 (20%). Of those with MS, 11 received disease-modifying therapy. The strongest early predictors (within 5 years of presentation) of secondary progressive MS at 30 years were presence of baseline infratentorial lesions and deep white matter lesions at 1 year. INTERPRETATION: Thirty years after onset, in a largely untreated cohort, there was a divergence of MS outcomes; some people accrued substantial disability early on, whereas others ran a more favorable long-term course. These outcomes could, in part, be predicted by radiological findings from within 1 year of first presentation. ANN NEUROL 2020;87:63-74.

Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes.

OBJECTIVE: In multiple sclerosis (MS), MRI measures at the whole brain or regional level are only modestly associated with disability, while network-based measures are emerging as promising prognostic markers. We sought to demonstrate whether data-driven patterns of covarying regional grey matter (GM) volumes predict future disability in secondary progressive MS (SPMS). METHODS: We used cross-sectional structural MRI, and baseline and longitudinal data of Expanded Disability Status Scale, Nine-Hole Peg Test (9HPT) and Symbol Digit Modalities Test (SDMT), from a clinical trial in 988 people with SPMS. We processed T1-weighted scans to obtain GM probability maps and applied spatial independent component analysis (ICA). We repeated ICA on 400 healthy controls. We used survival models to determine whether baseline patterns of covarying GM volume measures predict cognitive and motor worsening. RESULTS: We identified 15 patterns of regionally covarying GM features. Compared with whole brain GM, deep GM and lesion volumes, some ICA components correlated more closely with clinical outcomes. A mainly basal ganglia component had the highest correlations at baseline with the SDMT and was associated with cognitive worsening (HR=1.29, 95% CI 1.09 to 1.52, p<0.005). Two ICA components were associated with 9HPT worsening (HR=1.30, 95% CI 1.06 to 1.60, p<0.01 and HR=1.21, 95% CI 1.01 to 1.45, p<0.05). ICA measures could better predict SDMT and 9HPT worsening (C-index=0.69-0.71) compared with models including only whole and regional MRI measures (C-index=0.65-0.69, p value for all comparison <0.05). CONCLUSIONS: The disability progression was better predicted by some of the covarying GM regions patterns, than by single regional or whole-brain measures. ICA, which may represent structural brain networks, can be applied to clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect.

Increased functional sensorimotor network efficiency relates to disability in multiple sclerosis.

BACKGROUND: Network abnormalities could help explain physical disability in multiple sclerosis (MS), which remains poorly understood. OBJECTIVE: This study investigates functional network efficiency changes in the sensorimotor system. METHODS: We included 222 MS patients, divided into low disability (LD, Expanded Disability Status Scale (EDSS) ⩽3.5, n = 185) and high disability (HD, EDSS ⩾6, n = 37), and 82 healthy controls (HC). Functional connectivity was assessed between 23 sensorimotor regions. Measures of efficiency were computed and compared between groups using general linear models corrected for age and sex. Binary logistic regression models related disability status to local functional network efficiency (LE), brain volumes and demographics. Functional connectivity patterns of regions important for disability were explored. RESULTS: HD patients demonstrated significantly higher LE of the left primary somatosensory cortex (S1) and right pallidum compared to LD and HC, and left premotor cortex compared to HC only. The logistic regression model for disability (R2 = 0.38) included age, deep grey matter volume and left S1 LE. S1 functional connectivity was increased with prefrontal and secondary sensory areas in HD patients, compared to LD and HC. CONCLUSION: Clinical disability in MS associates with functional sensorimotor increases in efficiency and connectivity, centred around S1, independent of structural damage.

Distinct influence of different vascular risk factors on white matter brain lesions in multiple sclerosis.

OBJECTIVE: To determine if vascular risk factor (VRF), that is, smoking, arterial hypertension (HT), dyslipidaemia and diabetes, have an effect on multiple sclerosis (MS) pathology as measured by MS typical brain lesions, we have compared brain MRIs from patients with MS with and without VRF age-matched and sex-matched. METHODS: Brain MRIs from five centres were scored for the presence of Dawson's fingers (DF) and juxtacortical lesions (JCL). A regression model was built to predict the effect of each individual VRF on DF and JCL, considering age and disease duration. RESULTS: 92 MS cases without VRF and 106 MS with one or more VRF (80 ever-smokers, 43 hypertensives, 25 dyslipidaemics and 10 diabetics) were included. Ever-smoking associated with a higher burden of DF (Exp(B)=1.29, 95% CI 1.10 to 1.51, p<0.01) and JCL (Exp(B)=1.38, 95% CI 1.21 to 1.57, p<0.01). No other VRF had an impact on DF. Dyslipidaemia associated with increased JCL (Exp(B)=1.30, 95% CI 1.10 to 1.56, p<0.01) but HT did not associate with any of the outcomes. CONCLUSIONS: Individual VRF appear to affect MS-specific lesions differently. An increase in MS lesions was mainly seen in smokers; however, this VRF is most likely to be present from onset of MS, and other VRF effects may be partly mitigated by treatment. Our findings support that treating VRF and cessation of smoking may be important in the management of MS.

Periventricular magnetisation transfer ratio abnormalities in multiple sclerosis improve after alemtuzumab.

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.

Magnetisation transfer ratio abnormalities in primary and secondary progressive multiple sclerosis.

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.

Structural network disruption markers explain disability in multiple sclerosis.

OBJECTIVE: To evaluate whether structural brain network metrics correlate better with clinical impairment and information processing speed in multiple sclerosis (MS) beyond atrophy measures and white matter lesions. METHODS: This cross-sectional study included 51 healthy controls and 122 patients comprising 58 relapsing-remitting, 28 primary progressive and 36 secondary progressive. Structural brain networks were reconstructed from diffusion-weighted MRIs and standard metrics reflecting network density, efficiency and clustering coefficient were derived and compared between subjects' groups. Stepwise linear regression analyses were used to investigate the contribution of network measures that explain clinical disability (Expanded Disability Status Scale (EDSS)) and information processing speed (Symbol Digit Modalities Test (SDMT)) compared with conventional MRI metrics alone and to determine the best statistical model that explains better EDSS and SDMT. RESULTS: Compared with controls, network efficiency and clustering coefficient were reduced in MS while these measures were also reduced in secondary progressive relative to relapsing-remitting patients. Structural network metrics increase the variance explained by the statistical models for clinical and information processing dysfunction. The best model for EDSS showed that reduced network density and global efficiency and increased age were associated with increased clinical disability. The best model for SDMT showed that lower deep grey matter volume, reduced efficiency and male gender were associated with worse information processing speed. CONCLUSIONS: Structural topological changes exist between subjects' groups. Network density and global efficiency explained disability above non-network measures, highlighting that network metrics can provide clinically relevant information about MS pathology.

Commentary on Al Hussona et al. 'New-onset seizures as a sole clinical presentation of multiple sclerosis'.

Despite the now significant contribution of magnetic resonance imaging, the accurate and timely diagnosis of multiple sclerosis (MS) is still clinically challenging. Al Hussona et al., with their case series, highlight the complexities of attributing paroxysmal, and in particular cortical, symptoms such as epileptic seizures to inflammatory demyelinating lesions, and establishing a diagnosis of MS based on them. In such circumstances an MS diagnosis is likely to be more tentative than for more typical MS presentations, and treatment choices should be weighed accordingly.

Volumetric reconstruction from printed films: Enabling 30 year longitudinal analysis in MR neuroimaging.

Hospitals often hold historical MR image data printed on films without being able to make it accessible to modern image processing techniques. Having the possibility to recover geometrically consistent, volumetric images from scans acquired decades ago will enable more comprehensive, longitudinal studies to understand disease progressions. In this paper, we propose a consistent framework to reconstruct a volumetric representation from printed films holding thick single-slice brain MR image acquisitions dating back to the 1980's. We introduce a flexible framework based on semi-automatic slice extraction, followed by automated slice-to-volume registration with inter-slice transformation regularisation and slice intensity correction. Our algorithm is robust against numerous detrimental effects being present in archaic films. A subsequent, isotropic total variation deconvolution technique revitalises the visual appearance of the obtained volumes. We assess the accuracy and perform the validation of our reconstruction framework on a uniquely long-term MRI dataset where a ground-truth is available. This method will be used to facilitate a robust longitudinal analysis spanning 30 years of MRI scans.

An abnormal periventricular magnetization transfer ratio gradient occurs early in multiple sclerosis.

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.

A longitudinal study of cortical grey matter lesion subtypes in relapse-onset multiple sclerosis.

BACKGROUND: Cortical grey matter (GM) lesions are common in multiple sclerosis (MS), but little is known about their temporal evolution. We investigated this in people with relapsing-remitting (RR) and secondary progressive (SP) MS. METHODS: 27 people with RRMS, and 22 with SPMS were included in this study. Phase-sensitive inversion recovery scans were acquired on 2 occasions. Cortical GM lesions were classified as intracortical (IC, only involving GM) and leucocortical (LC, mixed GM-white matter (WM)); WM lesions touching the cortex as juxtacortical (JC). On follow-up scans, new IC, LC and JC lesions were identified, and any change in classification of lesions previously observed was noted. WM lesion counts in the whole brain were assessed on PD/T2-weighted scans. RESULTS: Over a mean (SD) of 21.0 (5.8) months, the number of new IC lesions per person per year was greater in SPMS (1.6 (1.9)) than RRMS (0.8 (1.9)) (Mann-Whitney p=0.039). All new LC lesions arose from previously seen IC lesions (SPMS 1.4 (1.8) per person per year, and RRMS 1.1 (1.0)), and none arose de novo, or from previously seen JC lesions. Changes in cortical GM (either new IC or IC converting to LC) lesion counts did not correlate with the changes in WM lesion counts. CONCLUSIONS: New cortical GM lesions rarely arise from the WM and the rate of new IC lesion formation is not closely linked with WM lesion accrual. IC lesion formation appears to be more common in SPMS than RRMS.

DIR-visible grey matter lesions and atrophy in multiple sclerosis: partners in crime?

BACKGROUND: The extent and clinical relevance of grey matter (GM) pathology in multiple sclerosis (MS) are increasingly recognised. GM pathology may present as focal lesions, which can be visualised using double inversion recovery (DIR) MRI, or as diffuse pathology, which can manifest as atrophy. It is, however, unclear whether the diffuse atrophy centres on focal lesions. This study aimed to determine if GM lesions and GM atrophy colocalise, and to assess their independent relationship with motor and cognitive deficits in MS. METHODS: Eighty people with MS and 30 healthy controls underwent brain volumetric T1-weighted and DIR MRI at 3 T, and had a comprehensive neurological and cognitive assessment. Probability mapping of GM lesions marked on the DIR scans and voxel- based morphometry (assessing GM atrophy) were carried out. The associations of GM lesion load and GM volume with clinical scores were tested. RESULTS: DIR-visible GM lesions were most commonly found in the right cerebellum and most apparent in patients with primary progressive MS. Deep GM structures appeared largely free from lesions, but showed considerable atrophy, particularly in the thalamus, caudate, pallidum and putamen, and this was most apparent in secondary progressive patients with MS. Very little co-localisation of GM atrophy and lesions was seen, and this was generally confined to the cerebellum and postcentral gyrus. In both regions, GM lesions and volume independently correlated with physical disability and cognitive performance. CONCLUSIONS: DIR-detectable GM lesions and GM atrophy do not significantly overlap in the brain but, when they do, they independently contribute to clinical disability.

Relationship of grey and white matter abnormalities with distance from the surface of the brain in multiple sclerosis.

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.