Corpus callosum atrophy correlates with gray matter atrophy in patients with multiple sclerosis

Associations between corpus callosum damage, clinical disability, and surface-based homologous inter-hemispheric connectivity in multiple sclerosis

Axonal damage in the corpus callosum is prevalent in multiple sclerosis (MS). Although callosal damage is associated with disrupted functional connectivity between hemispheres, it is unclear how this relates to cognitive and physical disability. We investigated this phenomenon using advanced measures of microstructural integrity in the corpus callosum and surface-based homologous inter-hemispheric connectivity (sHIC) in the cortex. We found that sHIC was significantly decreased in primary motor, somatosensory, visual, and temporal cortical areas in a group of 36 participants with MS (29 relapsing-remitting, 4 secondary progressive MS, and 3 primary-progressive MS) compared with 42 healthy controls (cluster level, p < 0.05). In participants with MS, global sHIC correlated with fractional anisotropy and restricted volume fraction in the posterior segment of the corpus callosum (r = 0.426, p = 0.013; r = 0.399, p = 0.020, respectively). Lower sHIC, particularly in somatomotor and posterior cortical areas, was associated with cognitive impairment and higher disability scores on the Expanded Disability Status Scale (EDSS). We demonstrated that higher levels of sHIC attenuated the effects of posterior callosal damage on physical disability and cognitive dysfunction, as measured by the EDSS and Brief Visuospatial Memory Test-Revised (interaction effect, p < 0.05). We also observed a positive association between global sHIC and years of education (r = 0.402, p = 0.018), supporting the phenomenon of "brain reserve" in MS. Our data suggest that preserved sHIC helps prevent cognitive and physical decline in MS.

Grey matter atrophy in patients with benign multiple sclerosis

BACKGROUND

Brain atrophy appears during the progression of multiple sclerosis (MS) and is associated with the disability caused by the disease.

METHODS

We investigated global and regional grey matter (GM) and white matter (WM) volumes, WM lesion load, and corpus callosum index (CCI), in benign relapsing-remitting MS (BRRMS, n = 35) with and without any treatment and compared those to aggressive relapsing-remitting MS (ARRMS, n = 46). Structures were analyzed by using an automated MRI quantification tool (cNeuro®).

RESULTS

The total brain and cerebral WM volumes were larger in BRRMS than in ARRMS (p = .014, p = .017 respectively). In BRRMS, total brain volumes, regional GM volumes, and CCI were found similar whether or not disease-modifying treatment (DMT) was used. The total (p = .033), as well as subcortical (p = .046) and deep WM (p = .041) lesion load volumes were larger in BRRMS patients without DMT. Cortical GM volumes did not differ between BRRMS and ARRMS, but the volumes of total brain tissue (p = .014) and thalami (p = .003) were larger in patients with BRRMS compared to ARRMS. A positive correlation was found between CCI and whole-brain volume in both BRRMS (r = .73, p < .001) and ARRMS (r = .80, p < .01).

CONCLUSIONS

Thalamic volume is the most prominent measure to differentiate BRRMS and ARRMS. Validation of automated quantification of CCI provides an additional applicable MRI biomarker to detect brain atrophy in MS.

Perivascular space is associated with brain atrophy in patients with multiple sclerosis

BACKGROUND

Perivascular space (PVS) is associated with neurodegenerative and neuroimmune diseases. Multiple sclerosis (MS) is traditionally a neuroimmune disease. However, studies show neurodegeneration also plays a vital role in MS. At present, most studies conclude severer PVS in MS is an imaging marker of neuroinflammation, while a 7T MRI study suggests that PVS in MS is associated with neurodegeneration.

METHODS

In this study, 82 MS patients (n=82) and 32 healthy controls (n=32) were enrolled. The following indexes were measured: the number, size and distribution of PVS, the PVS score, corpus callosum index (CCI), corpus callosum area (CCA), the ratio of the corpus callosum to the cranium (CCR), aligned third ventricle width (a3VW), and unaligned third ventricle width (u3VW).

RESULTS

The PVS score (4 vs. 3, P=0.041), PVSs number (103.280±45.107 vs. 87.625±30.139, P=0.035), and enlarged perivascular spaces (EPVSs) number (9 vs. 1, P<0.001) of MS patients were significantly higher than in the healthy controls. PVSs number (23.5 vs. 13) and EPVSs number (1 vs. 0) in the basal ganglia (BG), and EPVSs number (3 vs. 0) in centrum semiovale (CSO) of MS patients were significantly higher than in the healthy controls, P<0.001. In MS patients, PVS was correlated with age and hypertension but not to the extended disability status scale (EDSS) score and other clinical data. In MS patients, PVS score was correlated with CCA (rs=0.272; P=0.013) and the CCR (rs=0.219; P=0.048), and PVSs number was correlated with CCA (rs=0.255; P=0.021), the correlation disappeared after adjusting hypertension and age. In MS patients in remission, PVSs number was correlated with CCA (rs=0.487; P=0.019), CCR (rs=0.479; P=0.021), and PVS score was correlated with CCA (rs=0.453; P=0.03). After adjustment of hypertension and age, the total number of PVSs was correlated with CCA (rs=0.419; P=0.049).

CONCLUSIONS

The PVS load in MS patients was heavier than healthy people, especially in BG and CSO. PVS was not correlated with EDSS in MS patients. The PVS of MS patients was associated with CCA and CCR, and PVSs number was independently related with CCA in MS patients in remission.

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

BACKGROUND AND PURPOSE

Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learning-based CC segmentation tool and hypothesized that its output would correlate with disability.

METHODS

A cohort of 631 MS patients (449 females, baseline age 41 ± 11 years) with both 3-dimensional T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI was used for the development. Data from 204 patients were manually segmented to train convolutional neural networks in extracting the midsagittal intracranial and CC areas. Remaining data were used to compare segmentations with FreeSurfer and benchmark the outputs with regard to clinical correlations. A 1.5 and 3 Tesla reproducibility cohort of 9 MS patients evaluated the segmentation robustness.

RESULTS

The deep learning-based tool was accurate in selecting the appropriate slice for segmentation (98% accuracy within 3 mm of the manual ground truth) and segmenting the CC (Dice coefficient .88-.91) and intracranial areas (.97-.98). The accuracy was lower with higher atrophy. Reproducibility was excellent (intraclass correlation coefficient > .90) for T1-weighted scans and moderate-good for FLAIR (.74-.75). Segmentations were associated with baseline and future (average follow-up time 6-7 years) Expanded Disability Status Scale (ρ = -.13 to -.24) and Symbol Digit Modalities Test (r = .18-.29) scores.

CONCLUSIONS

We present a fully automatic deep learning-based CC segmentation tool optimized to modern imaging in MS with clinical correlations on par with computationally expensive alternatives.

Rhythmic interlimb coordination of the lower limbs in multiple sclerosis during auditory pacing to three different frequencies

BACKGROUND

Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system with heterogeneous symptoms. Persons with MS (PwMS) show reduced walking capacity with changes in their gait pattern. It is unknown to which extent coordination deficits are present in PwMS, which can be measured by seated lower leg interlimb coordination tasks, and to which extent they are related to motor and cognitive function.

RESEARCH QUESTION

How is the control of interlimb coordination of the lower limbs characterized in PwMS compared to healthy controls (HC) during a seated rhythmical coordination task and what is the relationship between interlimb coordination, motor or cognitive function?

METHODS

Rhythmical interlimb coordination was assessed during a single session in 38 PwMS and 13 HC, using a seated rhythmical coordination task, comprising of antiphase flexion-extension of the lower limbs, to metronomes at 0.75 Hz, 1.00 Hz, 1.50 Hz. Outcomes were phase coordination index (PCI), movement amplitude and movement frequency. Correlations between interlimb coordination, motor, and cognitive function were examined.

RESULTS

PwMS showed impaired walking capacity but preserved cognitive function. Mixed model analysis revealed a significant effect of group and metronome frequency for PCI, attenuated by the variability in generating knee (antiphase flexion-extension) movements. Movement amplitude was highest at metronome frequency 1.00 Hz. In PwMS significant correlations were found between PCI and cognitive function when performing the task at metronome frequencies 0.75 Hz and 1.50 Hz, as well as motor function at 1.50 Hz.

SIGNIFICANCE

PwMS had a higher variability in interlimb coordination compared to HC. The most stable interlimb antiphase coordination mode was performed at 1.00 Hz. Significant correlations support the existence of a relationship between information processing speed, as well as walking impairment, with interlimb coordination. While cognitive and motor control are always needed for interlimb coordination movements, associations are strongest in the deviant higher and lower metronome rhythms.

Shape and Volumetric Differences in the Corpus Callosum between Patients with Major Depressive Disorder and Healthy Controls

OBJECTIVE

This study aimed to investigate the morphometric differences in the corpus callosum between patients with major depressive disorder (MDD) and healthy controls and analyze their relationship to gray matter changes.

METHODS

Twenty female MDD patients and 21 healthy controls (HCs) were included in the study. To identify the difference in the regional gray matter concentration (GMC), VBM was performed with T1 magnetic resonance imaging. The shape analysis of the corpus callosum was processed. Diffusion tensor imaging (DTI) fiber-tracking was performed to identify the regional tract pathways in the damaged corpus callosal areas.

RESULTS

In the shape analysis, regional shape contractions in the rostrum and splenium were found in the MDD patients. VBM analysis showed a significantly lower white matter concentration in the genu and splenium, and a significantly lower GMC in the frontal, limbic, insular, and temporal regions of the MDD patients compared to the HCs. In DTI fiber-tracking, the fibers crossing the damaged areas of the genu, rostrum, and splenium were anatomically connected to the areas of lower GMC in MDD patients.

CONCLUSION

These findings support that major depressive disorder may be due to disturbances in multiple neuronal circuits, especially those associated with the corpus callosum.

A validation study of manual atrophy measures in patients with Multiple Sclerosis

PURPOSE

Manual measures such as corpus callosum index, normalized corpus callosum area, and width of the third ventricle are potential biomarkers for brain atrophy. In this work, we investigate their suitability to assess the neurodegenerative component of multiple sclerosis (MS) by comparing them to volumetric measures and expanded disability status scale (EDSS).

METHODS

Fifty-eight patients with a clinically isolated syndrome, 48 MS patients treated with interferon β, and 26 treated with natalizumab underwent a brain MRI at baseline and after 1 year. Manual measures were evaluated by two observers using Jim v.6.0 at both time points. Volumetric tools (SIENA/x and Freesurfer) were used to calculate normalized brain volume, brain parenchymal fraction, annualized percentage of brain volume change, corpus callosum volume, ventricle volume, and volume of the third ventricle. Statistical analyses were performed with SPSS v.13.

RESULTS

Usage of corpus callosum volume and third ventricle volume to validate normalized corpus callosum area and width of the third ventricle, respectively, showed very good correlations (r = 0.85, r = 0.83; p < 0.01). Width of the third ventricle, corpus callosum index, and normalized corpus callosum area correlations were significant with EDSS in all patients and moderate to strong with normalized brain volume and brain parenchymal fraction in natalizumab-treated patients (respectively r = - 0.54, r = - 0.61; r = 0.55, r = 0.67; and r = 0.58, r = 0.67; with p < 0.05).

CONCLUSION

Width of the third ventricle and normalized corpus callosum area seem the more robust manual measures regarding correlation with volumetric measures and EDSS, especially in patients with more advanced disease.

Brain MRI Predicts Worsening Multiple Sclerosis Disability over 5 Years in the SUMMIT Study

BACKGROUND AND PURPOSE

Brain MRI-derived lesions and atrophy are related to multiple sclerosis (MS) disability. In the Serially Unified Multicenter MS Investigation (SUMMIT), from Brigham and Women's Hospital (BWH) and University of California, San Francisco (UCSF), we assessed whether MRI methodologic heterogeneity may limit the ability to pool multisite data sets to assess 5-year clinical-MRI associations.

METHODS

Patients with relapsing-remitting (RR) MS (n = 100 from each site) underwent baseline brain MRI and baseline and 5-year clinical evaluations. Patients were matched on sex (74 women each), age, disease duration, and Expanded Disability Status Scale (EDSS) score. MRI was performed with differences between sites in both acquisition (field strength, voxel size, pulse sequences), and postprocessing pipeline to assess brain parenchymal fraction (BPF) and T2 lesion volume (T2LV).

RESULTS

The UCSF cohort showed higher correlation than the BWH cohort between T2LV and disease duration. UCSF showed a higher inverse correlation between BPF and age than BWH. UCSF showed a higher inverse correlation than BWH between BPF and 5-year EDSS score. Both cohorts showed inverse correlations between BPF and T2LV, with no between-site difference. The pooled but not individual cohort data showed a link between a lower baseline BPF and the subsequent 5-year worsening in disability in addition to other stronger relationships in the data.

CONCLUSIONS

MRI acquisition and processing differences may result in some degree of heterogeneity in assessing brain lesion and atrophy measures in patients with MS. Pooling of data across sites is beneficial to correct for potential biases in individual data sets.

MRI-Based Manual versus Automated Corpus Callosum Volumetric Measurements in Multiple Sclerosis

BACKGROUND AND PURPOSE

Corpus callosum atrophy is a neurodegenerative biomarker in multiple sclerosis (MS). Manual delineations are gold standard but subjective and labor intensive. Novel automated methods are promising but require validation. We aimed to compare the robustness of manual versus automatic corpus callosum segmentations based on FreeSurfer.

METHODS

Nine MS patients (6 females, age 38 ± 13 years, disease duration 7.3 ± 5.2 years) were scanned twice with repositioning using 3-dimensional T₁ -weighted magnetic resonance imaging on three scanners (two 1.5 T and one 3.0 T), that is, six scans/patient, on the same day. Normalized corpus callosum areas were measured independently by a junior doctor and neuroradiologist. The cross-sectional and longitudinal streams of FreeSurfer were used to segment the corpus callosum volume.

RESULTS

Manual measurements had high intrarater (junior doctor .96 and neuroradiologist .96) and interrater agreement (.94), by intraclass correlation coefficient (P < .001). The coefficient of variation was lowest for longitudinal FreeSurfer (.96% within scanners; 2.0% between scanners) compared to cross-sectional FreeSurfer (3.7%, P = .001; 3.8%, P = .058) and the neuroradiologist (2.3%, P = .005; 2.4%, P = .33). Longitudinal FreeSurfer was also more accurate than cross-sectional (Dice scores 83.9 ± 7.5% vs. 78.9 ± 8.4%, P < .01 relative to manual segmentations). The corpus callosum measures correlated with physical disability (longitudinal FreeSurfer r = -.36, P < .01; neuroradiologist r = -.32, P < .01) and cognitive disability (longitudinal FreeSurfer r = .68, P < .001; neuroradiologist r = .64, P < .001).

CONCLUSIONS

FreeSurfer's longitudinal stream provides corpus callosum measures with better repeatability than current manual methods and with similar clinical correlations. However, due to some limitations in accuracy, caution is warranted when using FreeSurfer with clinical data.

Central nervous system targeted autoimmunity causes regional atrophy: a 9.4T MRI study of the EAE mouse model of Multiple Sclerosis

Atrophy has become a clinically relevant marker of progressive neurodegeneration in multiple sclerosis (MS). To better understand atrophy, mouse models that feature atrophy along with other aspects of MS are needed. The experimental autoimmune encephalomyelitis (EAE) mouse model of MS was used to determine the extent of atrophy in a model of inflammation-associated central nervous system pathology. High-resolution magnetic resonance imaging (MRI) and atlas-based volumetric analysis were performed to measure brain regional volumes in EAE mice. EAE brains were larger at peak clinical disease (days 14–16) compared to controls, with affected regions including the cerebellum, hippocampus, and corpus callosum. Following peak clinical disease, EAE mice exhibited significant loss of volume at chronic long-term disease duration (day 66+). Atrophy was identified in both white and grey matter regions including the cerebral cortex, cerebellum, hippocampus, corpus callosum, basal forebrain, midbrain, optic tract, and colliculus. Histological analysis of the atrophied cortex, cerebellum, and hippocampus showed demyelination, and axonal/neuronal loss. We hypothesize this atrophy could be a result of inflammatory associated neurodegenerative processes, which may also be involved in MS. Using MRI and atlas-based volumetrics, EAE has the potential to be a test bed for treatments aimed at reducing progressive neurological deterioration in MS.

Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis

Objective

To evaluate alterations in apparent axon diameter and axon density obtained by high‐gradient diffusion MRI in the corpus callosum of MS patients and the relationship of these advanced diffusion MRI metrics to neurologic disability and cognitive impairment in MS.

Methods

Thirty people with MS (23 relapsing‐remitting MS [RRMS], 7 progressive MS [PMS]) and 23 healthy controls were scanned on a human 3‐tesla (3T) MRI scanner equipped with 300 mT/m maximum gradient strength using a comprehensive multishell diffusion MRI protocol. Data were fitted to a three‐compartment geometric model of white matter to estimate apparent axon diameter and axon density in the midline corpus callosum. Neurologic disability and cognitive function were measured using the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Minimal Assessment of Cognitive Function in MS battery.

Results

Apparent axon diameter was significantly larger and axon density reduced in the normal‐appearing corpus callosum (NACC) of MS patients compared to healthy controls, with similar trends seen in PMS compared to RRMS. Larger apparent axon diameter in the NACC of MS patients correlated with greater disability as measured by the EDSS (r = 0.555, P = 0.007) and poorer performance on the Symbol Digits Modalities Test (r = ‐0.593, P = 0.008) and Brief Visuospatial Memory Test–Revised (r = −0.632, P < 0.01), tests of interhemispheric processing speed and new learning and memory, respectively.

Interpretation

Apparent axon diameter in the corpus callosum obtained from high‐gradient diffusion MRI is a potential imaging biomarker that may be used to understand the development and progression of cognitive impairment in MS.

Pathological cut-offs of global and regional brain volume loss in multiple sclerosis

BACKGROUND

Volumetric MRI surrogate markers of disease progression are lacking.

OBJECTIVE

To establish cut-off values of brain volume loss able to discriminate between healthy controls and MS patients.

METHODS

In total, 386 patients after first demyelinating event suggestive of MS (CIS), 964 relapsing-remitting MS (RRMS) patients, 63 secondary-progressive MS (SPMS) patients and 58 healthy controls were included in this longitudinal study. A total of 11,438 MRI scans performed on the same MRI scanner with the same protocol were analysed. Annualised percentage changes of whole brain, grey matter, thalamus and corpus callosum volumes were estimated. We investigated cut-offs able to discriminate between healthy controls and MS patients.

RESULTS

At a predefined specificity of 90%, the annualised percentage change cut-off of corpus callosum volume (-0.57%) was able to distinguish between healthy controls and patients with the highest sensitivity (51% in CIS, 48% in RRMS and 42% in SPMS patients). Lower sensitivities (22%-49%) were found for cut-offs of whole brain, grey matter and thalamic volume loss. Among CIS and RRMS patients, cut-offs were associated with greater accumulation of disability.

CONCLUSION

We identified cut-offs of annualised global and regional brain volume loss rates able to discriminate between healthy controls and MS patients.

Automated segmentation of cerebral deep gray matter from MRI scans: effect of field strength on sensitivity and reliability

Background

The cerebral subcortical deep gray matter nuclei (DGM) are a common, early, and clinically-relevant site of atrophy in multiple sclerosis (MS). Robust and reliable DGM segmentation could prove useful to evaluate putative neuroprotective MS therapies. The objective of the study was to compare the sensitivity and reliability of DGM volumes obtained from 1.5T vs. 3T MRI.

Methods

Fourteen patients with MS [age (mean, range) 50.2 (32.0–60.8) years, disease duration 18.4 (8.2–35.5) years, Expanded Disability Status Scale score 3.1 (0–6), median 3.0] and 15 normal controls (NC) underwent brain 3D T1-weighted paired scan-rescans at 1.5T and 3T. DGM (caudate, thalamus, globus pallidus, and putamen) segmentation was obtained by the fully automated FSL-FIRST pipeline. Both raw and normalized volumes were derived.

Results

DGM volumes were generally higher at 3T vs. 1.5T in both groups. For raw volumes, 3T showed slightly better sensitivity (thalamus: p = 0.02; caudate: p = 0.10; putamen: p = 0.02; globus pallidus: p = 0.0004; total DGM: p = 0.01) than 1.5T (thalamus: p = 0.05; caudate: p = 0.09; putamen: p = 0.03; globus pallidus: p = 0.0006; total DGM: p = 0.02) for detecting DGM atrophy in MS vs. NC. For normalized volumes, 3T but not 1.5T detected atrophy in the globus pallidus in the MS group. Across all subjects, scan-rescan reliability was generally very high for both platforms, showing slightly higher reliability for some DGM volumes at 3T. Raw volumes showed higher reliability than normalized volumes. Raw DGM volume showed higher reliability than the individual structures.

Conclusions

These results suggest somewhat higher sensitivity and reliability of DGM volumes obtained from 3T vs. 1.5T MRI. Further studies should assess the role of this 3T pipeline in tracking potential MS neurotherapeutic effects.

Brain Parenchymal Fraction in Healthy Adults-A Systematic Review of the Literature

Brain atrophy is an important feature of many neurodegenerative disorders. It can be described in terms of change in the brain parenchymal fraction (BPF). In order to interpret the BPF in disease, knowledge on the BPF in healthy individuals is required. The aim of this study was to establish a normal range of values for the BPF of healthy individuals via a systematic review of the literature. The databases PubMed and Scopus were searched and 95 articles, including a total of 9269 individuals, were identified including the required data. We present values of BPF from healthy individuals stratified by age and post-processing method. The mean BPF correlated with mean age and there were significant differences in age-adjusted mean BPF between methods. This study contributes to increased knowledge about BPF in healthy individuals, which may assist in the interpretation of BPF in the setting of disease. We highlight the differences between post-processing methods and the need for a consensus gold standard.

A surface-based technique for mapping homotopic interhemispheric connectivity: Development, characterization, and clinical application

The functional organization of the human brain consists of a high degree of connectivity between interhemispheric homologous regions. The degree of homotopic organization is known to vary across the cortex and homotopic connectivity is high in regions that share cross-hemisphere structural connections or are activated by common input streams (e.g., the visual system). Damage to one or both regions, as well as damage to the connections between homotopic regions, could disrupt this functional organization. Here were introduce and test a computationally efficient technique, surface-based homotopic interhermispheric connectivity (sHIC), that leverages surface-based registration and processing techniques in an attempt to improve the spatial specificity and accuracy of cortical interhemispheric connectivity estimated with resting state functional connectivity. This technique is shown to be reliable both within and across subjects. sHIC is also characterized in a dataset of nearly 1000 subjects. We confirm previous results showing increased interhemispheric connectivity in primary sensory regions, and reveal a novel rostro-caudal functionally defined network level pattern of sHIC across the brain. In addition, we demonstrate a structural-functional relationship between sHIC and atrophy of the corpus callosum in multiple sclerosis (r = 0.2979, p = 0.0461). sHIC presents as a sensitive and reliable measure of cortical homotopy that may prove useful as a biomarker in neurologic disease. Hum Brain Mapp 37:2849-2868, 2016. © 2016 Wiley Periodicals, Inc.

Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors

Purpose

We tested the validity of a freely available segmentation pipeline to measure compartmental brain volumes from 3T MRI in patients with multiple sclerosis (MS). Our primary focus was methodological to explore the effect of segmentation corrections on the clinical relevance of the output metrics.

Methods

Three-dimensional T1-weighted images were acquired to compare 61 MS patients to 30 age- and gender-matched normal controls (NC). We also tested the within patient MRI relationship to disability (eg, expanded disability status scale [EDSS] score) and cognition. Statistical parametric mapping v. 8 (SPM8)-derived gray matter (GMF), white matter (WMF), and total brain parenchyma fractions (BPF) were derived before and after correcting errors from T1 hypointense MS lesions and/or ineffective deep GM contouring.

Results

MS patients had lower GMF and BPF as compared to NC (P<.05). Cognitively impaired patients had lower BPF than cognitively preserved patients (P<.05). BPF was related to EDSS; BPF and GMF were related to disease duration (all P<.05). Errors caused bias in GMFs and WMFs but had no discernable influence on BPFs or any MRI-clinical associations.

Conclusions

We report the validity of a segmentation pipeline for the detection of MS-related brain atrophy with 3T MRI. Longitudinal studies are warranted to extend these results.

Corpus callosum atrophy is strongly associated with cognitive impairment in multiple sclerosis: Results of a 17-year longitudinal study

Background:

Cognitive impairment is common in multiple sclerosis (MS) and may be subtle. The corpus callosum is essential for connectivity-demanding cognitive tasks and is significantly affected in MS, therefore it may serve as a marker for cognitive function.

Objective:

The objective of this paper is to longitudinally study the normalized corpus callosum area (nCCA) as a marker of cognitive function and disability in MS.

Methods:

Thirty-seven MS patients were followed from 1996 with follow-ups in 2004 and 2013. A healthy matched control group was recruited. The Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT) were assessed. The nCCA was measured on T2-weighted images. Volumetry was performed with FreeSurfer.

Results:

Disease duration spanned five decades (1.6–46 years). Annual corpus callosal atrophy rate decreased with disease duration. nCCA was strongly correlated with SDMT ( r = 0.793, p < 0.001) and moderately correlated with EDSS ( r = −0.545, p < 0.001) after adjusting for disease duration, age and sex. The correlations of brain parenchymal fraction, white matter fraction, gray matter fraction and normalized lesion volume were less strong.

Conclusions:

The nCCA correlates well with physical and cognitive disability in time perspectives close to two decades, outperforming volumetric measurements. The nCCA is fast and could be feasible for clinical implementation where it may help identify patients in need of neuropsychological evaluation.

MRI phenotypes based on cerebral lesions and atrophy in patients with multiple sclerosis

BACKGROUND

While disease categories (i.e. clinical phenotypes) of multiple sclerosis (MS) are established, there remains MRI heterogeneity among patients within those definitions. MRI-defined lesions and atrophy show only moderate inter-correlations, suggesting that they represent partly different processes in MS. We assessed the ability of MRI-based categorization of cerebral lesions and atrophy in individual patients to identify distinct phenotypes.

METHODS

We studied 175 patients with MS [age (mean ± SD) 42.7 ± 9.1 years, 124 (71%) women, Expanded Disability Status (EDSS) score 2.5 ± 2.3, n = 18 (10%) clinically isolated demyelinating syndrome (CIS), n=115 (66%) relapsing-remitting (RR), and n = 42 (24%) secondary progressive (SP)]. Brain MRI measures included T2 hyperintense lesion volume (T2LV) and brain parenchymal fraction (to assess whole brain atrophy). Medians were used to create bins for each parameter, with patients assigned a low or high severity score.

RESULTS

Four MRI phenotype categories emerged: Type I = low T2LV/mild atrophy [n = 67 (38%); CIS = 14, RR = 47, SP = 6]; Type II = high T2LV/mild atrophy [n = 21 (12%); RR = 19, SP = 2]; Type III = low T2LV/high atrophy [n = 21 (12%); CIS = 4, RR = 16, SP = 1]; and Type IV = high T2LV/high atrophy [n = 66 (38%); RR = 33, S P = 33]. Type IV was the most disabled and was the only group showing a correlation between T2LV vs. BPF and MRI vs. EDSS score (all p < 0.05).

CONCLUSIONS

We described MRI-categorization based on the relationship between lesions and atrophy in individual patients to identify four phenotypes in MS. Most patients have congruent extremes related to the degree of lesions and atrophy. However, many have a dissociation. Longitudinal studies will help define the stability of these patterns and their role in risk stratification.