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Functional brain networks: linking thalamic atrophy to clinical disability in multiple sclerosis, a multimodal fMRI and MEG study.

ABSTRACT: Thalamic atrophy is known to be one of the most important predictors for clinical dysfunction in multiple sclerosis (MS). As the thalamus is highly connected to many cortical areas, this suggests that thalamic atrophy is associated with disruption of cortical functional networks. We investigated this thalamo-cortical system to explain the presence of physical and cognitive problems in MS. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) were performed in 86 MS patients and 21 healthy subjects. We computed cortical functional networks for fMRI and MEG by respectively the Pearson's correlation coefficient and the phase lag index using the same automated anatomical labeling atlas for both modalities. Thalamo-cortical functional connectivity was only estimated using fMRI. We computed conventional network metrics such as clustering coefficient and path length and analyzed the minimum spanning tree (MST), a subnetwork and backbone of the original network. MS patients showed reduced thalamic volumes and increased thalamo-cortical connectivity. MEG cortical functional networks showed a lower level of integration in MS in terms of the MST, whereas fMRI cortical networks did not differ between groups. Lower integration of MEG cortical functional networks was both related to thalamic atrophy as well as to increased thalamo-cortical functional connectivity in fMRI and to worse cognitive and clinical status. This study demonstrated for the first time that thalamic atrophy is associated with global disruption of cortical functional networks in MS and this global disruption of network activity was related to worse cognitive and clinical function in MS. Hum Brain Mapp 36:603-618, 2015. © 2014 Wiley Periodicals, Inc.

SUBMITTER: Tewarie P

PROVIDER: S-EPMC6869443 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Functional brain networks: linking thalamic atrophy to clinical disability in multiple sclerosis, a multimodal fMRI and MEG study.

Tewarie Prejaas P Schoonheim Menno M MM Schouten Daphne I DI Polman Chris H CH Balk Lisanne J LJ Uitdehaag Bernard M J BM Geurts Jeroen J G JJ Hillebrand Arjan A Barkhof Frederik F Stam Cornelis J CJ

Human brain mapping 20141008 2

Thalamic atrophy is known to be one of the most important predictors for clinical dysfunction in multiple sclerosis (MS). As the thalamus is highly connected to many cortical areas, this suggests that thalamic atrophy is associated with disruption of cortical functional networks. We investigated this thalamo-cortical system to explain the presence of physical and cognitive problems in MS. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) were performed in 86 MS patien ...[more]

PMID: 25293505

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Project description:Purpose: To study which brain volume measures best differentiate early relapsing MS (RMS) and secondary progressive MS (SPMS) patients and correlate with disability and cognition. To test whether isolated thalamic atrophy at study baseline correlates with NEDA (no evidence of disease activity) at 2 years. Methods: Total and regional brain volumes were measured from 24 newly diagnosed RMS patients 6 months after initiation of therapy and 2 years thereafter, and in 36 SPMS patients. Volumes were measured by SIENAX and cNeuro. The patients were divided into subgroups based on whole brain parenchyma (BP) and thalamic atrophy at baseline. Standard scores (z-scores) were computed by comparing individual brain volumes against healthy controls. A z-score cut-off of -1.96 was applied to separate atrophic from normal brain volumes. The Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT) were assessed at baseline and at 2 years. Differences in achieving NEDA-3, NEDA-4, EDSS progression, and SDMT change were analyzed between patients with no thalamic or BP atrophy and in patients with isolated thalamic atrophy at baseline. Results: At baseline, 7 SPMS and 12 RMS patients had no brain atrophy, 8 SPMS and 10 RMS patients had isolated thalamic atrophy and 2 RMS and 20 SPMS patients had both BP and thalamic atrophy. NEDA-3 was reached in 11/19 patients with no brain atrophy but only in 2/16 patients with isolated thalamic atrophy (p = 0.012). NEDA-4 was reached in 7/19 patients with no brain atrophy and in 1/16 of the patients with isolated thalamic atrophy (p = 0.047). At 2 years, EDSS was same or better in 16/19 patients with no brain atrophy but only in 5/17 patients with isolated thalamic atrophy (p = 0.002). There was no significant difference in the EDSS, relapses or SDMT between patients with isolated thalamic atrophy and no atrophy at baseline. Conclusion: Patients with isolated thalamic atrophy were at a higher risk for not reaching 2-year NEDA-3 and for EDSS increase than patients with no identified brain atrophy. The groups were clinically indistinguishable. A single measurement of thalamic and whole brain atrophy could help identify patients needing most effective therapies from early on.

Project description:Grey matter atrophy has been shown in primary progressive multiple sclerosis (PPMS), but its association with physical incapacity is unclear. We submitted 19 patients with PPMS to a neurological evaluation and brain magnetic resonance imaging (MRI) with volumetric analysis using FreeSurfer. We found no relation between the Expanded Disability Status Scale or disease duration and the grey matter or white matter structures analysed. Lesion load was negatively correlated with cortical and subcortical grey matter volumes, but not with total white matter volume. We concluded that physical disability in PPMS is not directly related to brain atrophy and that focal inflammatory white matter lesions may contribute to progressive neuronal degeneration.Primary progressive multiple sclerosis (PPMS) is characterized by chronic progression since onset, with predominant involvement of the spinal cord and prominent neurodegeneration. Grey matter atrophy has been shown in patients with PPMS, but its association with clinical incapacity is uncertain. We investigated the relationship between regional brain atrophy and physical disability in patients with PPMS.Patients with an established diagnosis of PPMS underwent a neurological evaluation followed by brain MRI at 1.5 T. Volumetric analysis was performed with FreeSurfer software, and evaluated the neocortex, total white matter, total subcortical grey matter, putamen, caudate, globus pallidus, thalamus, hippocampus, brainstem, corpus callosum and pre-central gyrus volumes. Clinical data obtained included physical disability as measured by the Expanded Disability Status Scale (EDSS).Nineteen patients were included, 14 female (73.7%), mean age of 55.7 (SD 7.6) and mean disease duration of 13.0 years (SD 8.8). Median EDSS score was 6.0 (3.5-8.0). The average T1 lesion load (4.9 cm³, SD 3.4) and T2 load (10.5 cm³, SD 9.9) did not relate to disease duration. There was no significant correlation between EDSS score or disease duration and the cortical grey matter, deep grey matter or white matter structures analysed. Lesion load was negatively correlated with cortical and subcortical grey matter volumes (p < 0.05), but not with total white matter volume.Physical disability in PPMS is not directly related to brain volume loss. Grey matter atrophy correlates with lesion load in patients with PPMS, indicating that focal inflammatory white matter lesions may contribute to progressive neuronal degeneration.

Project description:In multiple sclerosis (MS), upper cervical cord gray matter (GM) atrophy correlates more strongly with disability than does brain or cord white matter (WM) atrophy. The corresponding relationships in the thoracic cord are unknown owing to technical difficulties in assessing GM and WM compartments by conventional magnetic resonance imaging techniques.To investigate the associations between MS disability and disease type with lower thoracic cord GM and WM areas using phase-sensitive inversion recovery magnetic resonance imaging at 3 T, as well as to compare these relationships with those obtained at upper cervical levels.Between July 2013 and March 2014, a total of 142 patients with MS (aged 25-75 years; 86 women) and 20 healthy control individuals were included in this cross-sectional observational study conducted at an academic university hospital.Total cord areas (TCAs), GM areas, and WM areas at the disc levels C2/C3, C3/C4, T8/9, and T9/10. Area differences between groups were assessed, with age and sex as covariates.Patients with relapsing MS (RMS) had smaller thoracic cord GM areas than did age- and sex-matched control individuals (mean differences [coefficient of variation (COV)]: 0.98 mm2 [9.2%]; P?=?.003 at T8/T9 and 0.93 mm2 [8.0%]; P?=?.01 at T9/T10); however, there were no significant differences in either the WM area or TCA. Patients with progressive MS showed smaller GM areas (mean differences [COV]: 1.02 mm2 [10.6%]; P?<?.001 at T8/T9 and 1.37 mm2 [13.2%]; P?<?.001 at T9/T10) and TCAs (mean differences [COV]: 3.66 mm2 [9.0%]; P?<?.001 at T8/T9 and 3.04 mm2 [7.2%]; P?=?.004 at T9/T10) compared with patients with RMS. All measurements (GM, WM, and TCA) were inversely correlated with Expanded Disability Status Scale score. Thoracic cord GM areas were correlated with lower limb function. In multivariable models (which also included cord WM areas and T2 lesion number, brain WM volumes, brain T1 and fluid-attenuated inversion recovery lesion loads, age, sex, and disease duration), cervical cord GM areas had the strongest correlation with Expanded Disability Status Scale score followed by thoracic cord GM area and brain GM volume.Thoracic cord GM atrophy can be detected in vivo in the absence of WM atrophy in RMS. This atrophy is more pronounced in progressive MS than RMS and correlates with disability and lower limb function. Our results indicate that remarkable cord GM atrophy is present at multiple cervical and lower thoracic levels and, therefore, may reflect widespread cord GM degeneration.

Project description:ObjectiveWe sought to characterize spinal cord atrophy along the entire spinal cord in the major multiple sclerosis (MS) phenotypes, and evaluate its correlation with clinical disability.MethodsAxial T1-weighted images were automatically reformatted at each point along the cord. Spinal cord cross-sectional area (SCCSA) were calculated from C1-T10 vertebral body levels and profile plots were compared across phenotypes. Average values from C2-3, C4-5, and T4-9 regions were compared across phenotypes and correlated with clinical scores, and then categorized as atrophic/normal based on z-scores derived from controls, to compare clinical scores between subgroups. In a subset of relapsing-remitting cases with longitudinal scans these regions were compared to change in clinical scores.ResultsThe cross-sectional study consisted of 149 adults diagnosed with relapsing-remitting MS (RRMS), 49 with secondary-progressive MS (SPMS), 58 with primary-progressive MS (PPMS) and 48 controls. The longitudinal study included 78 RRMS cases. Compared to controls, all MS groups had smaller average regions except RRMS in T4-9 region. In all MS groups, SCCSA from all regions, particularly the cervical cord, correlated with most clinical measures. In the RRMS cohort, 22% of cases had at least one atrophic region, whereas in progressive MS the rate was almost 70%. Longitudinal analysis showed correlation between clinical disability and cervical cord thinning.ConclusionsSpinal cord atrophy was prevalent across MS phenotypes, with regional measures from the RRMS cohort and the progressive cohort, including SPMS and PPMS, being correlated with disability. Longitudinal changes in the spinal cord were documented in RRMS cases, making it a potential marker for disease progression. While cervical SCCSA correlated with most disability and progression measures, inclusion of thoracic measurements improved this correlation and allowed for better subgrouping of spinal cord phenotypes. Cord atrophy is an important and easily obtainable imaging marker of clinical and sub-clinical progression in all MS phenotypes, and such measures can play a key role in patient selection for clinical trials.

Project description:BackgroundMultiple Sclerosis (MS), a neurodegenerative and neuroinflammatory disease, causing lesions that disrupt the brain's anatomical and physiological connectivity networks, resulting in cognitive, visual and/or motor disabilities. Advanced imaging techniques like diffusion and functional MRI allow measurement of the brain's structural connectivity (SC) and functional connectivity (FC) networks, and can enable a better understanding of how their disruptions cause disability in people with MS (pwMS). However, advanced MRI techniques are used mainly for research purposes as they are expensive, time-consuming and require high-level expertise to acquire and process. As an alternative, the Network Modification (NeMo) Tool can be used to estimate SC and FC using lesion masks derived from pwMS and a reference set of controls' connectivity networks.ObjectiveHere, we test the hypothesis that estimated SC and FC (eSC and eFC) from the NeMo Tool, based only on an individual's lesion masks, can be used to classify pwMS into disability categories just as well as SC and FC extracted from advanced MRI directly in pwMS. We also aim to find the connections most important for differentiating between no disability vs evidence of disability groups.Materials and methodsOne hundred pwMS (age:45.5 ± 11.4 years, 66% female, disease duration: 12.97 ± 8.07 years) were included in this study. Expanded Disability Status Scale (EDSS) was used to assess disability, 67 pwMS had no disability (EDSS < 2). Observed SC and FC were extracted from diffusion and functional MRI directly in pwMS, respectively. The NeMo Tool was used to estimate the remaining structural connectome (eSC), by removing streamlines in a reference set of tractograms that intersected the lesion mask. The NeMo Tool's eSC was used then as input to a deep neural network to estimate the corresponding FC (eFC). Logistic regression with ridge regularization was used to classify pwMS into disability categories (no disability vs evidence of disability), based on demographics/clinical information (sex, age, race, disease duration, clinical phenotype, and spinal lesion burden) and either pairwise entries or regional summaries from one of the following matrices: SC, FC, eSC, and eFC. The area under the ROC curve (AUC) was used to assess the classification performance. Both univariate statistics and parameter coefficients from the classification models were used to identify features important to differentiating between the groups.ResultsThe regional eSC and eFC models outperformed their observed FC and SC counterparts (p-value < 0.05), while the pairwise eSC and SC performed similarly (p = 0.10). Regional eSC and eFC models had higher AUC (0.66-0.68) than the pairwise models (0.60-0.65), with regional eFC having highest classification accuracy across all models. Ridge regression coefficients for the regional eFC and regional observed FC models were significantly correlated (Pearson's r = 0.52, p-value < 10e-7). Decreased estimated SC node strength in default mode and ventral attention networks and increased eFC node strength in visual networks was associated with evidence of disability.DiscussionHere, for the first time, we use clinically acquired lesion masks to estimate both structural and functional connectomes in patient populations to better understand brain lesion-dysfunction mapping in pwMS. Models based on the NeMo Tool's estimates of SC and FC better classified pwMS by disability level than SC and FC observed directly in the individual using advanced MRI. This work provides a viable alternative to performing high-cost, advanced MRI in patient populations, bringing the connectome one step closer to the clinic.

Dataset Information

Functional brain networks: linking thalamic atrophy to clinical disability in multiple sclerosis, a multimodal fMRI and MEG study.

Publications

Functional brain networks: linking thalamic atrophy to clinical disability in multiple sclerosis, a multimodal fMRI and MEG study.

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