Impaired morphological processing: insights from multiple sclerosis

R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal's dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.

Should Spinal MRI Be Routinely Performed in Patients With Clinically Isolated Optic Neuritis?

ObjectivesTo evaluate white matter and grey matter T1-weighted (w)/T2w ratio (T1w/T2w ratio) in healthy controls and patients with multiple sclerosis, and its association with clinical disability.MethodsIn this cross-sectional study, 270...

Multiple sclerosis (MS) and several other neurodegenerative disorders affect structurally- and functionally-connected brain networks. However, the extent of structural damage within specific networks relative to global white matter has not been systematically explored in MS. The aims of this study were therefore to investigate white matter within six brain networks - i.e., dorsal/ventral Default Mode, left/right Executive Control, and anterior/posterior Salience Networks - to: 1) determine whether MS white matter lesions are disproportionately prevalent in these regions compared to global white matter; 2) quantify microstructural degradation in these regions among persons with MS (pwMS) compared to healthy controls (HCs); and 3) ascertain whether network degradation is larger than expected compared to global white matter differences between pwMS and HCs. White matter lesion maps, global white matter masks, and whole-brain diffusion MRI maps of mean diffusivity from 104 pwMS (48±12 years; 85 female) and 100 HCs (39±16; 65 female), were analyzed using the UManitoba-JHU Functionally-Defined Human White Matter Atlases. Statistical analyses included parametric t-tests and post hoc non-parametric Wilcoxon tests. Among pwMS, 4/6 white matter networks contained disproportionately high lesion volumes (p < 0.008). All 6 networks exhibited lower microstructure among pwMS compared to HCs (p < 0.008); and even after controlling for subject-specific global white matter values, 5/6 white matter networks exhibited disproportionately reduced tissue microstructure among pwMS compared to HCs (p < 0.008). These findings suggest that MS disproportionately affects white matter structural connections underlying specific intrinsic brain networks, including the Default Mode, Executive Control, and Salience Networks.Significance statement White matter lesions and diffuse white matter damage are among the hallmark pathologies of multiple sclerosis (MS). However, although MS-related functional activity and connectivity changes throughout large-scale brain networks (including the Default Mode, Executive Control, and Salience Networks) have been previously characterized, the current study is the first to systematically examine the concentration of white matter lesions and the degree of diffuse white matter damage underlying these networks. Our findings suggest that white matter structural connections underlying the Default Mode, Executive Control, and Salience Networks are disproportionately affected in persons with MS, with higher-than-expected concentrations of cerebral white matter lesions and greater than expected amounts of diffuse white matter damage.

Measuring the similarity between implicit semantic relations is an important task in information retrieval and natural language processing. For example, consider the situation where you know an entity-pair (e.g. Google, YouTube), between which a particular relation holds (e.g. acquisition), and you are interested in retrieving other entity-pairs for which the same relation holds (e.g. Yahoo, Inktomi). Existing keyword-based search engines cannot be directly applied in this case because in keyword-based search, the goal is to retrieve documents that are relevant to the words used in the query -- not necessarily to the relations implied by a pair of words. Accurate measurement of relational similarity is an important step in numerous natural language processing tasks such as identification of word analogies, and classification of noun-modifier pairs. We propose a method that uses Web search engines to efficiently compute the relational similarity between two pairs of words. Our method consists of three components: representing the various semantic relations that exist between a pair of words using automatically extracted lexical patterns, clustering the extracted lexical patterns to identify the different semantic relations implied by them, and measuring the similarity between different semantic relations using an inter-cluster correlation matrix. We propose a pattern extraction algorithm to extract a large number of lexical patterns that express numerous semantic relations. We then present an efficient clustering algorithm to cluster the extracted lexical patterns. Finally, we measure the relational similarity between word-pairs using inter-cluster correlation. We evaluate the proposed method in a relation classification task. Experimental results on a dataset covering multiple relation types show a statistically significant improvement over the current state-of-the-art relational similarity measures.

Identifying the role of compartmentalized inflammation within the central nervous system (CNS) and its association with chronic active lesions is essential for advancing our overall understanding of disease progression in multiple sclerosis (MS). In this study, we explore whether the inflammatory activity is higher in white matter (WM) tracts disrupted by paramagnetic rim lesions (PRLs) and if inflammation in PRL-disrupted WM tracts is associated with disability in people with MS. Forty-four MS patients and 11 healthy controls were included. 18 kDa-translocator protein positron emission tomography (TSPO-PET) with the 11C-PK11195 radioligand was used to measure the neuroinflammatory activity. The Network Modification Tool was used to identify WM tracts disrupted by PRLs and non-PRLs that were delineated on MRI. The Expanded Disability Status Scale was used to measure disability. MS patients had higher inflammatory activity in whole-brain WM compared to healthy controls (p = 0.001). Compared to patients without PRLs, patients with PRLs exhibited higher levels of inflammatory activity in the WM tracts disrupted by any type of lesions (p = 0.02) or PRLs (p = 0.004). In patients with at least one PRL, inflammatory activity was higher in WM tracts highly disrupted by PRLs compared to WM tracts highly disrupted by non-PRLs (p = 0.009). Elevated inflammatory activity in highly disrupted WM tracts was associated with increased disability in patients with PRL (p = 0.03), but not in patients without PRL (p = 0.2). This study suggests that patients with PRLs may exhibit more diffuse WM inflammation in addition to higher inflammation along WM tracts disrupted by PRLs compared to non-PRLs, which could contribute to larger lesion volumes and faster disability progression. Imaging PRLs may serve to identify patients with both focal and diffuse inflammation, guiding therapeutic interventions aimed at reducing inflammation and preventing progressive disability in MS.

Oligodendrocyte Progenitor Cell Susceptibility to Injury in Multiple Sclerosis

T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties.We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component’s volume and structural white matter damage identified on FLAIR MRI scans in patients with MS.A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006–0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients.In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

McAlpine's Multiple Sclerosis

White matter tracts that overlap with the thalamus and the putamen are protected against multiple sclerosis pathology

IntroductionAdult genetic leukoencephalopathies are rare neurological disorders that present unique diagnostic challenges due to their clinical and radiological overlap with more common white matter diseases, notably multiple sclerosis (MS). In this context, a strong collaborative multidisciplinary network is beneficial for shortening the diagnostic odyssey of these patients and preventing misdiagnosis. The White Matter Rounds (WM Rounds) are multidisciplinary international online meetings attended by more than 30 physicians and scientists from 15 participating sites that gather every month to discuss patients with atypical white matter disorders. We aim to present the experience of the WM Rounds Network and demonstrate the value of collaborative multidisciplinary international case discussion meetings in differentiating and preventing misdiagnoses between genetic white matter diseases and atypical MS.MethodsWe retrospectively reviewed the demographic, clinical and radiological data of all the subjects presented at the WM Rounds since their creation in 2013.ResultsSeventy-four patients (mean age 44.3) have been referred and discussed at the WM Rounds since 2013. Twenty-five (33.8%) of these patients were referred by an MS specialist for having an atypical presentation of MS, while in most of the remaining cases, the referring physician was a geneticist (23; 31.1%). Based on the WM Rounds recommendations, a definite diagnosis was made in 36/69 (52.2%) patients for which information was available for retrospective review. Of these diagnosed patients, 20 (55.6%) had a genetic disease, 8 (22.2%) had MS, 3 (8.3%) had both MS and a genetic disorder and 5 (13.9%) had other non-genetic conditions. Interestingly, among the patients initially referred by an MS specialist, 7/25 were definitively diagnosed with MS, 5/25 had a genetic condition (e.g., X-linked adrenoleukodystrophy and hereditary small vessel diseases like Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) and COL4A1-related disorder), and one had both MS and a genetic demyelinating neuropathy. Thanks to the WM Rounds collaborative efforts, the subjects who currently remain without a definite diagnosis, despite extensive investigations performed in the clinical setting, have been recruited in research studies aimed at identifying novel forms of genetic MS mimickers.ConclusionsThe experience of the WM Rounds Network demonstrates the benefit of collective discussions on complex cases to increase the diagnostic rate and decrease misdiagnosis in patients with rare or atypical white matter diseases. Networks of this nature allow physicians and scientists to compare and share information on challenging cases from across the world, provide a basis for future multicenter research studies, and serve as model for other rare diseases.

Objective: To classify spinal cord lesions in multiple sclerosis (MS) based on white matter (WM) columns, and grey matter (GM) and WM involvement using magnetic resonance imaging (MRI). Background The localization of spinal cord lesions has not been well documented on MRI, although morphology and distribution of plaques have been characterized in post-mortem studies. Design/Methods: MRI was performed on the cervical cord in 16 MS patients (10 female, mean age 44.8) (8 relapsing remitting (RR) MS, 7 secondary progressive (SP) MS, 1 clinically isolated syndrome (CIS)). Axial phase sensitive inversion recovery (PSIR) and gradient-echo sequences were acquired. Two readers reviewed both images simultaneously and reached a consensus about classification of lesions by location: anterior (AC), lateral (LC) or posterior columns (PC). A sub-classification of lesions in mixed WM/GM and those involving WM only was also performed. Lesions were outlined manually on PSIR images and compared with mean cord area. Results: 51 lesions were identified, 24 in RRMS, 22 in SPMS, 5 in CIS. Three lesions were seen in AC (5.8%), 18 in PC (35.3%) and 30 in LC (58.9%). 33% of lesions involved WM alone and 67% involved both GM and WM; no pure GM lesions were identified. Mean lesion area in AC was 4.3mm2, LC 8.5mm2, PC 11.3mm2, with lesions in each column covering 6.1%, 12% and 16.1% of mean cord area respectively, mean lesion length in AC 18.3mm, LC 17.6mm and PC 24.8mm. Conclusions: Most lesions seen involved GM and WM, and were in the PC and LC, in agreement with post-mortem studies. However, no pure GM lesions were seen, suggesting technical limitations or a difference in patient characteristics from post-mortem studies. MRI may permit classification of spinal cord lesion location, area and length, which maybe correlated in future with disability to provide new insights into their functional effects. Supported by: MS Society. Disclosure: Dr. Kearney has nothing to disclose. Dr. Miszkiel has received research support from Biogen Idec and GlaxoSmithKline, Inc. Dr. Yiannakas has nothing to disclose. Dr. Ciccarelli has nothing to disclose. Dr. Miller has received personal compensation for activities with UCL Institute of Neurology, Biogen Idec, GlaxoSmithKline, and Bayer Schering Pharma. Dr. Miller has received personal compensation in an editorial capacity for Journal of Neurology. Dr. Miller has received research support from GlaxoSmithKline, Biogen Idec, and Novartis.

BackgroundAs disease progression remains poorly understood in multiple sclerosis (MS), we aim to investigate the sequence in which different disease milestones occur using a novel data-driven approach. MethodsWe analysed a cohort of 295 relapse-onset MS patients and 96 healthy controls, and considered 28 features, capturing information on T2-lesion load, regional brain and spinal cord volumes, resting-state functional centrality (“hubness”), microstructural tissue integrity of major white matter (WM) tracts and performance on multiple cognitive tests. We used a discriminative event-based model to estimate the sequence of biomarker abnormality in MS progression in general, as well as specific models for worsening physical disability and cognitive impairment. ResultsWe demonstrated that grey matter (GM) atrophy of the cerebellum, thalamus, and changes in corticospinal tracts are early events in MS pathology, whereas other WM tracts as well as the cognitive domains of working memory, attention, and executive function are consistently late events. The models for disability and cognition show early functional changes of the default-mode network and earlier changes in spinal cord volume compared to the general MS population. Overall, GM atrophy seems crucial due to its early involvement in the disease course, whereas WM tract integrity appears to be affected relatively late despite the early onset of WM lesions. ConclusionData-driven modelling revealed the relative occurrence of both imaging and non-imaging events as MS progresses, providing insights into disease propagation mechanisms, and allowing fine-grained staging of patients for monitoring purposes

The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.

MULTIPLE SCLEROSIS AFTER COVID-19: A SIGN OF THINGS TO COME?