scholarly journals Word-finding difficulty is a prevalent disease-related deficit in early multiple sclerosis

2019 ◽  
Vol 26 (13) ◽  
pp. 1752-1764 ◽  
Author(s):  
Rachel Brandstadter ◽  
Michelle Fabian ◽  
Victoria M Leavitt ◽  
Stephen Krieger ◽  
Anusha Yeshokumar ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Gray Matter ◽  
Objective Assessment ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Patient Report ◽  
Word Finding ◽  
Cognitive Complaint ◽  
Two Samples ◽  
Patient Reported

Background: Persons with multiple sclerosis (MS) commonly report word-finding difficulty clinically, yet this language deficit remains underexplored. Objective: To investigate the prevalence and nature of word-finding difficulty in persons with early MS on three levels: patient report, cognitive substrates, and neuroimaging. Methods: Two samples of early MS patients ( n = 185 and n = 55; ⩽5 years diagnosed) and healthy controls ( n = 50) reported frequency/severity of cognitive deficits and underwent objective assessment with tasks of rapid automatized naming (RAN), measuring lexical access speed, memory, word generation, and cognitive efficiency. High-resolution brain magnetic resonance imaging (MRI) derived measurements of regional cortical thickness, global and deep gray matter volume, and T2 lesion volume. Relationships among patient-reported word-finding difficulty, cognitive performance, and neural correlates were examined. Results: Word-finding difficulty was the most common cognitive complaint of MS patients and the only complaint reported more by patients than healthy controls. Only RAN performance discriminated MS patients with subjective word-finding deficits from those without subjective complaints and from healthy controls. Thinner left parietal cortical gray matter independently predicted impaired RAN performance, driven primarily by the left precuneus. Conclusion: Three levels of evidence (patient-report, objective behavior, regional gray matter) support word-finding difficulty as a prevalent, measurable, disease-related deficit in early MS linked to left parietal cortical thinning.

scholarly journals Altered Functional Connectivity in White and Gray Matter in Patients With Multiple Sclerosis

2020 ◽  
Vol 14 ◽  
Author(s):  
Jing Huang ◽  
Muwei Li ◽  
Qiongge Li ◽  
Zhipeng Yang ◽  
Bowen Xin ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Functional Connectivity ◽  
Gray Matter ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Resting State Fmri ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Functional Changes ◽  
Time Courses

Background: Functional magnetic resonance imaging (fMRI) has been widely used to assess neural activity changes in gray matter (GM) in patients with multiple sclerosis (MS); however, brain function alterations in white matter (WM) relatively remain under-explored.Purpose: This work aims to identify the functional connectivity in both the WM and the GM of patients with MS using fMRI and the correlations between these functional changes and cumulative disability as well as the lesion ratio.Materials and Methods: For this retrospective study, 37 patients with clinically definite MS and 43 age-matched healthy controls were included between 2010 and 2014. Resting-state fMRI was performed. The WFU Pick and JHU Eve atlases were used to define 82 GM and 48 WM regions in common spaces, respectively. The time courses of blood oxygen level-dependent (BOLD) signals were averaged over each GM or WM region. The averaged time courses for each pair of GM and WM regions were correlated. All 82 × 48 correlations for each subject formed a functional correlation matrix.Results: Compared with the healthy controls, the MS patients had a decreased temporal correlation between the WM and the GM regions. Five WM bundles and four GM regions had significantly decreased mean correlation coefficients (CCs). More specifically, the WM functional alterations were negatively correlated with the lesion volume in the bilateral fornix, and the mean GM-averaged CCs of the WM bundles were inversely correlated with the lesion ratio (r = −0.36, P = 0.012). No significant correlation was found between WM functional alterations and the paced auditory serial addition test score, Expanded Disease Severity Scale score, and Multiple Sclerosis Severity Score (MSSS) in MS.Conclusions: These findings highlight current gaps in our knowledge of the WM functional alterations in patients with MS and may link WM function with pathological mechanisms.

scholarly journals Detection of subtle gait disturbance and future fall risk in early multiple sclerosis

Neurology ◽  
2020 ◽  
Vol 94 (13) ◽  
pp. e1395-e1406 ◽  
Author(s):  
Rachel Brandstadter ◽  
Oluwasheyi Ayeni ◽  
Stephen C. Krieger ◽  
Noam Y. Harel ◽  
Miguel X. Escalon ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Fall Risk ◽  
Dynamic Balance ◽  
Gait Disturbance ◽  
Cervical Cord ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Brain Volumes ◽  
Patient Reported ◽  
Gait Dysfunction

ObjectiveTo test the hypothesis that higher-challenge gait and balance tasks are more sensitive than traditional metrics to subtle patient-reported gait dysfunction and future fall risk in early multiple sclerosis (MS).MethodsPersons with early MS (n = 185; ≤5 years diagnosed) reported gait function (MS Walking Scale) and underwent traditional disability metrics (Expanded Disability Status Scale [EDSS], Timed 25 Foot Walk). Patients and healthy controls (n = 50) completed clinically feasible challenge tasks of gait endurance (2-Minute Walk Test), standing balance (NIH Toolbox), and dynamic balance (balance boards; tandem walk on 2 ten-foot boards of different widths, 4.5 and 1.5 in). MRI assessed global and regional brain volumes, total T2 lesion volume (T2LV), infratentorial T2LVs and counts, and cervical cord lesion counts. Falls, near falls, and fall-related injuries were assessed after 1 year. We examined links between all tasks and patient-reported gait, MRI markers, and fall data.ResultsPatients performed worse on higher challenge balance, but not gait, tasks compared with healthy controls. Worse patient-reported gait disturbance was associated with worse performance on all tasks, but only dynamic balance was sensitive to mild patient-reported gait difficulty. Balance tasks were more correlated with MRI metrics than were walking tasks or EDSS score. Thirty percent of patients reported either a fall or near fall after 1 year, with poor dynamic balance as the only task independently predicting falls.ConclusionsBalance plays a leading role in gait dysfunction early in MS. Clinically feasible higher-challenge balance tasks were most sensitive to patient-reported gait, MRI disease markers, and risk of future falls, highlighting potential to advance functional outcomes in clinical practice and trials.

Association of Age at Onset With Gray Matter Volume and White Matter Microstructural Abnormalities in People With Multiple Sclerosis

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012869
Author(s):  
Raffaello Bonacchi ◽  
Alessandro Meani ◽  
Elisabetta Pagani ◽  
Olga Marchesi ◽  
Andrea Falini ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Gray Matter ◽  
Linear Models ◽  
Gray Matter Volume ◽  
Age At Onset ◽  
Healthy Controls ◽  
Compensatory Mechanisms ◽  
Cross Sectional ◽  
Matter Volume

Objective:To investigate whether age at onset influences brain gray matter volume (GMV) and white matter (WM) microstructural abnormalities in adult multiple sclerosis (MS) patients, given its influence on clinical phenotype and disease course.Method:In this hypothesis-driven cross-sectional study, we enrolled 67 pediatric-onset MS (POMS) patients and 143 sex- and disease duration (DD)-matched randomly-selected adult-onset MS (AOMS) patients, together with 208 healthy controls. All subjects underwent neurological evaluation and 3T MRI acquisition. MRI variables were standardized based on healthy controls, to remove effects of age and sex. Associations with DD in POMS and AOMS patients were studied with linear models. Time to reach clinical and MRI milestones was assessed with product-limit approach.Results:At DD=1 year, GMV and WM fractional anisotropy (FA) were abnormal in AOMS but not in POMS patients. Significant interaction of age at onset (POMS vs AOMS) into the association with DD was found for GMV and WM FA. The crossing point of regression lines in POMS and AOMS patients was at 20 years of DD for GMV and 14 for WM FA. For POMS and AOMS patients, median DD was 29 and 19 years to reach Expanded Disability Status Scale=3 (p<0.001), 31 and 26 years to reach abnormal Paced Auditory Serial Addition Task-3 (p=0.01), 24 and 18 years to reach abnormal GMV (p=0.04), and 19 and 17 years to reach abnormal WM FA (p=0.36).Conclusions:Younger patients are initially resilient to MS-related damage. Then, compensatory mechanisms start failing with loss of WM integrity, followed by GM atrophy and finally disability.

scholarly journals Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Ashika Mani ◽  
Tales Santini ◽  
Radhika Puppala ◽  
Megan Dahl ◽  
Shruthi Venkatesh ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Deep Learning ◽  
Magnetic Resonance ◽  
Image Quality ◽  
Repeated Measures ◽  
Financial Burden ◽  
Brain Magnetic Resonance Imaging ◽  
Lesion Volume ◽  
Patient Reported

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model in restoring the image quality of accelerated routine clinical brain MR scans for PwMS.Methods: We acquired fast 3D T1w BRAVO and fast 3D T2w FLAIR MRI sequences (half the phase encodes and half the number of slices) in parallel to conventional parameters. Using a subset of the scans, we trained a DL model to generate images from fast scans with quality similar to the conventional scans and then applied the model to the remaining scans. We calculated clinically relevant T1w volumetrics (normalized whole brain, thalamic, gray matter, and white matter volume) for all scans and T2 lesion volume in a sub-analysis. We performed paired t-tests comparing conventional, fast, and fast with DL for these volumetrics, and fit repeated measures mixed-effects models to test for differences in correlations between volumetrics and clinically relevant patient-reported outcomes (PRO).Results: We found statistically significant but small differences between conventional and fast scans with DL for all T1w volumetrics. There was no difference in the extent to which the key T1w volumetrics correlated with clinically relevant PROs of MS symptom burden and neurological disability.Conclusion: A deep learning model that improves the image quality of the accelerated routine clinical brain MR scans has the potential to inform clinically relevant outcomes in MS.

Gray matter trophism, cognitive impairment, and depression in patients with multiple sclerosis

2017 ◽  
Vol 23 (14) ◽  
pp. 1864-1874 ◽  
Author(s):  
Emanuele Pravatà ◽  
Maria A Rocca ◽  
Paola Valsasina ◽  
Gianna C Riccitelli ◽  
Claudio Gobbi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Gray Matter ◽  
Rating Scale ◽  
Three Dimensional ◽  
Emotional Behavior ◽  
Cortical Atrophy ◽  
Lesion Volume ◽  
Cortical Thinning ◽  
C Statistic

Background: Cognitive impairment and depression frequently affects patients with multiple sclerosis (MS). However, the relationship between the occurrence of depression and cognitive impairment and the development of cortical atrophy has not been fully elucidated yet. Objectives: To investigate the association of cortical and deep gray matter (GM) volume with depression and cognitive impairment in MS. Methods: Three-dimensional (3D) T1-weighted scans were obtained from 126 MS patients and 59 matched healthy controls. Cognitive impairment was assessed using the Brief Repeatable Battery of Neuropsychological Tests and depression with the Montgomery-Asberg Depression Rating Scale (MADRS). Using FreeSurfer and FIRST software, we assessed cortical thickness (CTh) and deep GM volumetry. Magnetic resonance imaging (MRI) variables explaining depression and cognitive impairment were investigated using factorial and classification analysis. Multivariate regression models correlated GM abnormalities with symptoms severity. Results: Compared with controls, MS patients exhibited widespread bilateral cortical thinning involving all brain lobes. Depressed MS showed selective CTh decrease in fronto-temporal regions, whereas cognitive impairment MS exhibited widespread fronto-parietal cortical and subcortical GM atrophy. Frontal cortical thinning was the best predictor of depression ( C-statistic = 0.7), whereas thinning of the right precuneus and high T2 lesion volume best predicted cognitive impairment ( C-statistic = 0.8). MADRS severity correlated with right entorhinal cortex thinning, whereas cognitive impairment severity correlated with left entorhinal and thalamus atrophy. Conclusion: MS-related depression is linked to circumscribed CTh changes in areas deputed to emotional behavior, whereas cognitive impairment is correlated with cortical and subcortical GM atrophy of circuits involved in cognition.

scholarly journals Subjective cognitive concern in multiple sclerosis is associated with reduced thalamic and cortical gray matter volumes

2019 ◽  
Vol 5 (1) ◽  
pp. 205521731982761 ◽  
Author(s):  
Isaiah Kletenik ◽  
Enrique Alvarez ◽  
Justin M Honce ◽  
Brooke Valdez ◽  
Timothy L Vollmer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Dysfunction ◽  
Gray Matter ◽  
Brain Volume ◽  
Brain Magnetic Resonance Imaging ◽  
Regions Of Interest ◽  
Patient Reported ◽  
Cortical Gray Matter ◽  
Gray Matter Volumes ◽  
The Relationship

Objective Brain atrophy has been correlated with objective cognitive dysfunction in multiple sclerosis but few studies have explored self-reported subjective cognitive concerns and their relationship to brain volume changes. This study explores the relationship between subjective cognitive concerns in multiple sclerosis and reduced brain volume in regions of interest implicated in cognitive dysfunction. Methods A total of 158 patients with multiple sclerosis completed the Quality of Life in Neurologic Disorders Measures (Neuro-QoL) short forms to assess subjective cognitive concerns and underwent brain magnetic resonance imaging. Regional brain volumes from regions of interest implicated in cognitive dysfunction were measured using NeuroQuant automated volumetric quantitation. Linear regression was used to analyze the relationship between subjective cognitive concerns and brain volume. Results Controlling for age, disease duration, gender, depression and fatigue, increased subjective cognitive concerns were associated with reduced thalamic volume (standardized β = 0.223, t150 =2.406, P = 0.017) and reduced cortical gray matter volume (standardized β = 0.240, t150 = 2.777, P = 0.006). Increased subjective cognitive concerns were not associated with any other regions of interest that were analyzed. Conclusions Subjective cognitive concern in MS is associated with reduced thalamic and cortical gray matter volumes, areas of the brain that have been implicated in objective cognitive impairment. These findings may lend neuroanatomical significance to subjective cognitive concerns and patient-reported outcomes as measured by Neuro-QoL.

The relationship between white matter fiber damage and gray matter perfusion in large-scale functionally defined networks in multiple sclerosis

2017 ◽  
Vol 23 (14) ◽  
pp. 1884-1892 ◽  
Author(s):  
Ashley Y Ma ◽  
Rita C Vitorino ◽  
Seyed-Parsa Hojjat ◽  
Alannah D Mulholland ◽  
Liying Zhang ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Gray Matter ◽  
Large Scale ◽  
Progressive Multiple Sclerosis ◽  
Functional Networks ◽  
Lesion Volume ◽  
Fiber Damage ◽  
Damage Extent ◽  
The Relationship

Background: Recent studies utilizing perfusion as a surrogate of cortical integrity show promise for overall cognition, but the association between white matter (WM) damage and gray matter (GM) integrity in specific functional networks is not previously studied. Objective: To investigate the relationship between WM fiber integrity and GM node perfusion within six functional networks of relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) patients. Methods: Magnetic resonance imaging (MRI) and neurocognitive testing were performed on 19 healthy controls (HC), 39 RRMS, and 45 SPMS patients. WM damage extent and severity were quantified with T2-hyper/T1-hypointense (T2h/T1h) lesion volume and degree of perfusion reduction in lesional and normal-appearing white matter (NAWM), respectively. A two-step linear regression corrected for confounders was employed. Results: Cognitive impairment was present in 20/39 (51%) RRMS and 25/45 (53%) SPMS patients. GM node perfusion was associated with WM fiber damage severity (WM hypoperfusion) within each network—including both NAWM ( R2 = 0.67–0.89, p < 0.0001) and T2h ( R2 = 0.39–0.62, p < 0.0001) WM regions—but was not significantly associated ( p > 0.01) with WM fiber damage extent (i.e. T2h/T1h lesion volumes). Conclusion: Overall, GM node perfusion was associated with severity rather than extent of WM network damage, supporting a primary etiology of GM hypoperfusion.

Iron content of the pulvinar nucleus of the thalamus is increased in adolescent multiple sclerosis

2012 ◽  
Vol 19 (5) ◽  
pp. 567-576 ◽  
Author(s):  
Jesper Hagemeier ◽  
E Ann Yeh ◽  
Mari Heininen Brown ◽  
Niels Bergsland ◽  
Michael G Dwyer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Gray Matter ◽  
Iron Content ◽  
Neurological Disorders ◽  
Normal Phase ◽  
Susceptibility Weighted Imaging ◽  
Healthy Controls ◽  
Volume Measurements ◽  
Deep Gray Matter ◽  
Age And Sex

Objective: The objective of this paper is to assess abnormal phase values, indicative of increased iron content, using susceptibility-weighted imaging (SWI)-filtered phase of the subcortical deep gray matter (SDGM) in adolescent multiple sclerosis (MS) and other neurological disorders (OND) patients, and in healthy controls (HC). Methods: Twenty adolescent MS and eight adolescent OND patients and 21 age- and sex-matched HC were scanned on a 3T GE scanner. Mean phase of abnormal phase tissue (MP-APT), MP-APT volume, normal phase tissue volume (NPTV) and normalized volume measurements were obtained for total SDGM, as well as specific structures separately. Results: Significantly increased MP-APT (28.2%, p<.001) and MP-APT volume (82.7%, p<.001), and decreased NPTV (−23.3%, p<.001) and normalized volume (−15.5%, p<.001) in the pulvinar nucleus of the thalamus was found in MS patients compared to HC. MP-APT in MS patients was also increased in total SDGM ( p=.012) and thalamus ( p=.044). Compared to OND patients, MS patients had increased MP-APT volume in the pulvinar nucleus of the thalamus ( p=.044) and caudate ( p=.045). Increased MP-APT of the SDGM structures were associated with increased T2 and T1 lesion burden and brain atrophy in MS patients. Conclusion: Adolescent MS patients showed increased iron content in the SDGM compared to OND patients and HC.

scholarly journals Structural and functional connectomes in people with multiple sclerosis

2020 ◽  
Author(s):  
Ceren Tozlu ◽  
Keith Jamison ◽  
Susan Gauthier ◽  
Amy Kuceyeski
Keyword(s):  
Multiple Sclerosis ◽  
Functional Mri ◽  
Imaging Modality ◽  
Structural Connectivity ◽  
Receiver Operating Curve ◽  
Ensemble Prediction ◽  
P Value ◽  
Lesion Volume ◽  
Healthy Controls ◽  
Functional Connectome

One of the challenges in multiple sclerosis is that lesion volume does not correlate with symptom severity. Advanced techniques such as diffusion and functional MRI allow imaging of the brain's connectivity networks, which may provide better insight as to brain-behavior relationships in impairment and compensation in multiple sclerosis. We aim to build machine learning models based on structural and functional connectomes to classify a) healthy controls versus people with multiple sclerosis and b) impaired versus not impaired people with multiple sclerosis. We also aim to identify the most important imaging modality for both classification tasks, and, finally, to investigate which brain regions' connectome measures contribute most to the classification. Fifteen healthy controls (age=43.6 ± 8.6, 53% female) and 76 people with multiple sclerosis (age: 45.2 ± 11.4 years, 65% female, disease duration: 12.2 ± 7.2 years) were included. Twenty-three people with multiple sclerosis were considered impaired, with an Expanded Disability Status Scale of 2 or higher. Subjects underwent MRI scans that included anatomical, diffusion and resting-state functional MRI. Random Forest models were constructed using structural and static/dynamic functional connectome measures independently; single modality models were then combined for an ensemble prediction. The accuracy of the models was assessed by the area under the receiver operating curve. Models that included structural connectomes significantly outperformed others when classifying healthy controls and people with multiple sclerosis, having a median accuracy of 0.86 (p-value<0.05, corrected). Models that included dynamic functional connectome metrics significantly outperformed others when distinguishing people with multiple sclerosis by impairment level, having a median accuracy of 0.63 (p-value<0.05, corrected). Structural connectivity between subcortical, somatomotor, and visual networks was most damaged by multiple sclerosis. For the classification of patients with multiple sclerosis into impairment severity groups, the most discriminatory metric was dwell time in a dynamic functional connectome state characterized by strong connectivity between and among somatomotor and visual networks. These results suggest that damage to the structural connectome, particularly in the subcortical, visual, and somatomotor networks, is a hallmark of multiple sclerosis, and, furthermore, that increased functional coordination between these same regions may be related to severity of motor disability in multiple sclerosis. The use of multi-modal connectome imaging has the potential to shed light on mechanisms of disease and compensation in multiple sclerosis, thus enabling more accurate prognoses and possibly the development of novel therapeutics.

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