Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.

Introduction: Multi-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics. Methods: Data from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases. Results: Fractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%. Discussion: In conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

A novel imaging marker of cortical "cellularity" in multiple sclerosis patients.

Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model ("soma and neurite density imaging (SANDI)") to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (fsoma)-a marker of cellularity-in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI fsoma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI fsoma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI fsoma in the outer part of the cortex compared to relapsing-remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing-remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI fsoma and serum neurofilament light chain-a biomarker of inflammatory axonal damage-suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI fsoma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.

Association of Spinal Cord Atrophy and Brain Paramagnetic Rim Lesions With Progression Independent of Relapse Activity in People With MS.

BACKGROUND AND OBJECTIVES: Progression independent of relapse activity (PIRA) is a crucial determinant of overall disability accumulation in multiple sclerosis (MS). Accelerated brain atrophy has been shown in patients experiencing PIRA. In this study, we assessed the relation between PIRA and neurodegenerative processes reflected by (1) longitudinal spinal cord atrophy and (2) brain paramagnetic rim lesions (PRLs). Besides, the same relationship was investigated in progressive MS (PMS). Last, we explored the value of cross-sectional brain and spinal cord volumetric measurements in predicting PIRA. METHODS: From an ongoing multicentric cohort study, we selected patients with MS with (1) availability of a susceptibility-based MRI scan and (2) regular clinical and conventional MRI follow-up in the 4 years before the susceptibility-based MRI. Comparisons in spinal cord atrophy rates (explored with linear mixed-effect models) and PRL count (explored with negative binomial regression models) were performed between: (1) relapsing-remitting (RRMS) and PMS phenotypes and (2) patients experiencing PIRA and patients without confirmed disability accumulation (CDA) during follow-up (both considering the entire cohort and the subgroup of patients with RRMS). Associations between baseline MRI volumetric measurements and time to PIRA were explored with multivariable Cox regression analyses. RESULTS: In total, 445 patients with MS (64.9% female; mean [SD] age at baseline 45.0 [11.4] years; 11.2% with PMS) were enrolled. Compared with patients with RRMS, those with PMS had accelerated cervical cord atrophy (mean difference in annual percentage volume change [MD-APC] -1.41; p = 0.004) and higher PRL load (incidence rate ratio [IRR] 1.93; p = 0.005). Increased spinal cord atrophy (MD-APC -1.39; p = 0.0008) and PRL burden (IRR 1.95; p = 0.0008) were measured in patients with PIRA compared with patients without CDA; such differences were also confirmed when restricting the analysis to patients with RRMS. Baseline volumetric measurements of the cervical cord, whole brain, and cerebral cortex significantly predicted time to PIRA (all p ≤ 0.002). DISCUSSION: Our results show that PIRA is associated with both increased spinal cord atrophy and PRL burden, and this association is evident also in patients with RRMS. These findings further point to the need to develop targeted treatment strategies for PIRA to prevent irreversible neuroaxonal loss and optimize long-term outcomes of patients with MS.

Characteristics, Prevalence, and Clinical Relevance of Juxtacortical Paramagnetic Rims in Patients With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: A subgroup of patients with multiple sclerosis (MS) presents focal paramagnetic rims at the border between cortex and white matter (juxtacortical paramagnetic rims [JPRs]). We investigated the presence of this finding in our in vivo MS cohort and explored its potential clinical relevance. Moreover, we exploited postmortem MRI of fixed whole MS brains to (1) detect those rims and (2) investigate their histologic correlation. METHODS: Quantitative susceptibility mapping (QSM) and magnetization-prepared 2 rapid acquisition gradient-echo (MP2RAGE) images at 3T-MRI of 165 patients with MS from the in vivo cohort were screened for JPRs and the presence of cortical lesions. Five postmortem brains from patients with MS were imaged with 3T-MRI to obtain QSM and MP2RAGE sequences. Tissue blocks containing JPRs were excised and paraffin-embedded slices stained by immunohistochemistry for myelin basic protein (for myelin) and anti-CR3/43 (for major histocompatibility complex II-positive microglia/macrophages). DAB-Turnbull stain was performed to detect iron. RESULTS: JPRs are present in approximately 10% of in vivo patients and are associated with increased cortical lesion load. One of the 5 postmortem brains showed JPRs. Histologically, JPRs correspond to an accumulation of activated iron-laden phagocytes and are associated with demyelination of the whole overlying cortical ribbon. DISCUSSION: JPRs are a novel potential MRI biomarker of focal cortical demyelination, which seems related to global cortical pathology and might be useful for diagnostic and stratification purposes in a clinical setting.

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

PURPOSE: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. THEORY AND METHODS: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images. RESULTS: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes. CONCLUSION: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis.

Importance: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures: MS/CIS vs non-MS conditions. Main Outcomes and Measures: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

Impact of follow ups, time interval and study duration in diffusion & myelin MRI clinical study in MS.

It is currently unknown how quantitative diffusion and myelin MRI designs affect the results of a longitudinal study. We used two independent datasets containing 6 monthly MRI measurements from 20 healthy controls and 20 relapsing-remitting multiple sclerosis (RR-MS) patients. Six designs were tested, including 3 MRI acquisitions, either over 6 months or over a shorter study duration, with balanced (same interval) or unbalanced (different interval) time intervals between MRI acquisitions. First, we show that in RR-MS patients, the brain changes over time obtained with 3 MRI acquisitions were similar to those observed with 5 MRI acquisitions and that designs with an unbalanced time interval showed the highest similarity, regardless of study duration. No significant brain changes were found in the healthy controls over the same periods. Second, the study duration affects the sample size in the RR-MS dataset; a longer study requires more subjects and vice versa. Third, the number of follow-up acquisitions and study duration affect the sensitivity and specificity of the associations with clinical parameters, and these depend on the white matter bundle and MRI measure considered. Together, this suggests that the optimal design depends on the assumption of the dynamics of change in the target population and the accuracy required to capture these dynamics. Thus, this work provides a better understanding of key factors to consider in a longitudinal study and provides clues for better strategies in clinical trial design.

Optical coherence tomography versus other biomarkers: Associations with physical and cognitive disability in multiple sclerosis.

BACKGROUND: Optical coherence tomography (OCT) is a biomarker of neuroaxonal loss in multiple sclerosis (MS). OBJECTIVE: The objective was to assess the relative role of OCT, next to magnetic resonance imaging (MRI) and serum markers of disability in MS. METHODS: A total of 100 patients and 52 controls underwent OCT to determine peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layers (GCIPL). Serum neurofilament light chain (sNfL), total lesion volume (TLV), and brain parenchymal fraction (BPF) were also assessed. The associations of OCT with disability were examined in linear regression models with correction for age, vision, and education. RESULTS: In patients, pRNFL was associated with the Symbol Digit Modalities Test (SDMT; p = 0.030). In the multivariate analysis including sNfL and MRI measures, pRNFL (ß = 0.19, p = 0.044) and TLV (ß = -0.24, p = 0.023) were the only markers associated with the SDMT. pRNFL (p < 0.001) and GCIPL (p < 0.001) showed associations with the Expanded Disability Status Scale (EDSS). In the multivariate analysis, GCIPL showed the strongest association with the EDSS (ß = -0.32, p < 0.001) followed by sNfL (ß = 0.18, p = 0.024). CONCLUSION: The associations of OCT measures with cognitive and physical disability were independent of serum and brain MRI markers of neuroaxonal loss. OCT can be an important tool for stratification in MS, while longitudinal studies using combinations of biomarkers are warranted.

How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review.

INTRODUCTION: Over the past few years, the deep learning community has developed and validated a plethora of tools for lesion detection and segmentation in Multiple Sclerosis (MS). However, there is an important gap between validating models technically and clinically. To this end, a six-step framework necessary for the development, validation, and integration of quantitative tools in the clinic was recently proposed under the name of the Quantitative Neuroradiology Initiative (QNI). AIMS: Investigate to what extent automatic tools in MS fulfill the QNI framework necessary to integrate automated detection and segmentation into the clinical neuroradiology workflow. METHODS: Adopting the systematic Cochrane literature review methodology, we screened and summarised published scientific articles that perform automatic MS lesions detection and segmentation. We categorised the retrieved studies based on their degree of fulfillment of QNI's six-steps, which include a tool's technical assessment, clinical validation, and integration. RESULTS: We found 156 studies; 146/156 (94%) fullfilled the first QNI step, 155/156 (99%) the second, 8/156 (5%) the third, 3/156 (2%) the fourth, 5/156 (3%) the fifth and only one the sixth. CONCLUSIONS: To date, little has been done to evaluate the clinical performance and the integration in the clinical workflow of available methods for MS lesion detection/segmentation. In addition, the socio-economic effects and the impact on patients' management of such tools remain almost unexplored.

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology.

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm2) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement.

FIESTA: Autoencoders for accurate fiber segmentation in tractography.

White matter bundle segmentation is a cornerstone of modern tractography to study the brain's structural connectivity in domains such as neurological disorders, neurosurgery, and aging. In this study, we present FIESTA (FIbEr Segmentation in Tractography using Autoencoders), a reliable and robust, fully automated, and easily semi-automatically calibrated pipeline based on deep autoencoders that can dissect and fully populate white matter bundles. This pipeline is built upon previous works that demonstrated how autoencoders can be used successfully for streamline filtering, bundle segmentation, and streamline generation in tractography. Our proposed method improves bundle segmentation coverage by recovering hard-to-track bundles with generative sampling through the latent space seeding of the subject bundle and the atlas bundle. A latent space of streamlines is learned using autoencoder-based modeling combined with contrastive learning. Using an atlas of bundles in standard space (MNI), our proposed method segments new tractograms using the autoencoder latent distance between each tractogram streamline and its closest neighbor bundle in the atlas of bundles. Intra-subject bundle reliability is improved by recovering hard-to-track streamlines, using the autoencoder to generate new streamlines that increase the spatial coverage of each bundle while remaining anatomically correct. Results show that our method is more reliable than state-of-the-art automated virtual dissection methods such as RecoBundles, RecoBundlesX, TractSeg, White Matter Analysis and XTRACT. Our framework allows for the transition from one anatomical bundle definition to another with marginal calibration efforts. Overall, these results show that our framework improves the practicality and usability of current state-of-the-art bundle segmentation framework.

High-frequency longitudinal white matter diffusion- and myelin-based MRI database: Reliability and variability.

Assessing the consistency of quantitative MRI measurements is critical for inclusion in longitudinal studies and clinical trials. Intraclass coefficient correlation and coefficient of variation were used to evaluate the different consistency aspects of diffusion- and myelin-based MRI measures. Multi-shell diffusion and inhomogeneous magnetization transfer data sets were collected from 20 healthy adults at a high-frequency of five MRI sessions. The consistency was evaluated across whole bundles and the track-profile along the bundles. The impact of the fiber populations on the consistency was also evaluated using the number of fiber orientations map. For whole and profile bundles, moderate to high reliability of diffusion and myelin measures were observed. We report higher reliability of measures for multiple fiber populations than single. The overall portrait of the most consistent measurements and bundles drawn from a wide range of MRI techniques presented here will be particularly useful for identifying reliable biomarkers capable of detecting, monitoring and predicting white matter changes in clinical applications and has the potential to inform patient-specific treatment strategies.

Serum Glial Fibrillary Acidic Protein Compared With Neurofilament Light Chain as a Biomarker for Disease Progression in Multiple Sclerosis.

Importance: There is a lack of validated biomarkers for disability progression independent of relapse activity (PIRA) in multiple sclerosis (MS). Objective: To determine how serum glial fibrillary acidic protein (sGFAP) and serum neurofilament light chain (sNfL) correlate with features of disease progression vs acute focal inflammation in MS and how they can prognosticate disease progression. Design, Setting, and Participants: Data were acquired in the longitudinal Swiss MS cohort (SMSC; a consortium of tertiary referral hospitals) from January 1, 2012, to October 20, 2022. The SMSC is a prospective, multicenter study performed in 8 centers in Switzerland. For this nested study, participants had to meet the following inclusion criteria: cohort 1, patients with MS and either stable or worsening disability and similar baseline Expanded Disability Status Scale scores with no relapses during the entire follow-up; and cohort 2, all SMSC study patients who had initiated and continued B-cell-depleting treatment (ie, ocrelizumab or rituximab). Exposures: Patients received standard immunotherapies or were untreated. Main Outcomes and Measures: In cohort 1, sGFAP and sNfL levels were measured longitudinally using Simoa assays. Healthy control samples served as the reference. In cohort 2, sGFAP and sNfL levels were determined cross-sectionally. Results: This study included a total of 355 patients (103 [29.0%] in cohort 1: median [IQR] age, 42.1 [33.2-47.6] years; 73 female patients [70.9%]; and 252 [71.0%] in cohort 2: median [IQR] age, 44.3 [33.3-54.7] years; 156 female patients [61.9%]) and 259 healthy controls with a median [IQR] age of 44.3 [36.3-52.3] years and 177 female individuals (68.3%). sGFAP levels in controls increased as a function of age (1.5% per year; P < .001), were inversely correlated with BMI (-1.1% per BMI unit; P = .01), and were 14.9% higher in women than in men (P = .004). In cohort 1, patients with worsening progressive MS showed 50.9% higher sGFAP levels compared with those with stable MS after additional sNfL adjustment, whereas the 25% increase of sNfL disappeared after additional sGFAP adjustment. Higher sGFAP at baseline was associated with accelerated gray matter brain volume loss (per doubling: 0.24% per year; P < .001) but not white matter loss. sGFAP levels remained unchanged during disease exacerbations vs remission phases. In cohort 2, median (IQR) sGFAP z scores were higher in patients developing future confirmed disability worsening compared with those with stable disability (1.94 [0.36-2.23] vs 0.71 [-0.13 to 1.73]; P = .002); this was not significant for sNfL. However, the combined elevation of z scores of both biomarkers resulted in a 4- to 5-fold increased risk of confirmed disability worsening (hazard ratio [HR], 4.09; 95% CI, 2.04-8.18; P < .001) and PIRA (HR, 4.71; 95% CI, 2.05-9.77; P < .001). Conclusions and Relevance: Results of this cohort study suggest that sGFAP is a prognostic biomarker for future PIRA and revealed its complementary potential next to sNfL. sGFAP may serve as a useful biomarker for disease progression in MS in individual patient management and drug development.

An investigation of the association between focal damage and global network properties in cognitively impaired and cognitively preserved patients with multiple sclerosis.

Introduction: The presence of focal cortical and white matter damage in patients with multiple sclerosis (pwMS) might lead to specific alterations in brain networks that are associated with cognitive impairment. We applied microstructure-weighted connectomes to investigate (i) the relationship between global network metrics and information processing speed in pwMS, and (ii) whether the disruption provoked by focal lesions on global network metrics is associated to patients' information processing speed. Materials and methods: Sixty-eight pwMS and 92 healthy controls (HC) underwent neuropsychological examination and 3T brain MRI including multishell diffusion (dMRI), 3D FLAIR, and MP2RAGE. Whole-brain deterministic tractography and connectometry were performed on dMRI. Connectomes were obtained using the Spherical Mean Technique and were weighted for the intracellular fraction. We identified white matter lesions and cortical lesions on 3D FLAIR and MP2RAGE images, respectively. PwMS were subdivided into cognitively preserved (CPMS) and cognitively impaired (CIMS) using the Symbol Digit Modalities Test (SDMT) z-score at cut-off value of -1.5 standard deviations. Statistical analyses were performed using robust linear models with age, gender, and years of education as covariates, followed by correction for multiple testing. Results: Out of 68 pwMS, 18 were CIMS and 50 were CPMS. We found significant changes in all global network metrics in pwMS vs HC (p < 0.05), except for modularity. All global network metrics were positively correlated with SDMT, except for modularity which showed an inverse correlation. Cortical, leukocortical, and periventricular lesion volumes significantly influenced the relationship between (i) network density and information processing speed and (ii) modularity and information processing speed in pwMS. Interestingly, this was not the case, when an exploratory analysis was performed in the subgroup of CIMS patients. Discussion: Our study showed that cortical (especially leukocortical) and periventricular lesions affect the relationship between global network metrics and information processing speed in pwMS. Our data also suggest that in CIMS patients increased focal cortical and periventricular damage does not linearly affect the relationship between network properties and SDMT, suggesting that other mechanisms (e.g. disruption of local networks, loss of compensatory processes) might be responsible for the development of processing speed deficits.

Personalized maps of T1 relaxometry abnormalities provide correlates of disability in multiple sclerosis patients.

OBJECTIVES AND AIMS: Quantitative MRI (qMRI) has greatly improved the sensitivity and specificity of microstructural brain pathology in multiple sclerosis (MS) when compared to conventional MRI (cMRI). More than cMRI, qMRI also provides means to assess pathology within the normal-appearing and lesion tissue. In this work, we further developed a method providing personalized quantitative T1 (qT1) abnormality maps in individual MS patients by modeling the age dependence of qT1 alterations. In addition, we assessed the relationship between qT1 abnormality maps and patients' disability, in order to evaluate the potential value of this measurement in clinical practice. METHODS: We included 119 MS patients (64 relapsing-remitting MS (RRMS), 34 secondary progressive MS (SPMS), 21 primary progressive MS (PPMS)), and 98 Healthy Controls (HC). All individuals underwent 3T MRI examinations, including Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) for qT1 maps and High-Resolution 3D Fluid Attenuated Inversion Recovery (FLAIR) imaging. To calculate personalized qT1 abnormality maps, we compared qT1 in each brain voxel in MS patients to the average qT1 obtained in the same tissue (grey/white matter) and region of interest (ROI) in healthy controls, hereby providing individual voxel-based Z-score maps. The age dependence of qT1 in HC was modeled using linear polynomial regression. We computed the average qT1 Z-scores in white matter lesions (WMLs), normal-appearing white matter (NAWM), cortical grey matter lesions (GMcLs) and normal-appearing cortical grey matter (NAcGM). Lastly, a multiple linear regression (MLR) model with the backward selection including age, sex, disease duration, phenotype, lesion number, lesion volume and average Z-score (NAWM/NAcGM/WMLs/GMcLs) was used to assess the relationship between qT1 measures and clinical disability (evaluated with EDSS). RESULTS: The average qT1 Z-score was higher in WMLs than in NAWM. (WMLs: 1.366 ± 0.409, NAWM: -0.133 ± 0.288, [mean ± SD], p < 0.001). The average Z-score in NAWM in RRMS patients was significantly lower than in PPMS patients (p = 0.010). The MLR model showed a strong association between average qT1 Z-scores in white matter lesions (WMLs) and EDSS (R2 = 0.549, ß = 0.178, 97.5 % CI = 0.030 to 0.326, p = 0.019). Specifically, we measured a 26.9 % increase in EDSS per unit of qT1 Z-score in WMLs in RRMS patients (R2 = 0.099, ß = 0.269, 97.5 % CI = 0.078 to 0.461, p = 0.007). CONCLUSIONS: We showed that personalized qT1 abnormality maps in MS patients provide measures related to clinical disability, supporting the use of those maps in clinical practice.

Longitudinal assessment of cervical spinal cord compartments in multiple sclerosis.

BACKGROUND: Although cervical spinal cord (cSC) area is an established biomarker in MS, there is currently a lack of longitudinal assessments of cSC gray and white matter areas. OBJECTIVE: We conducted an explorative analysis of longitudinal changes of cSC gray and white matter areas in MS patients. METHODS: 65 MS patients (33 relapsing-remitting; 20 secondary progressive and 12 primary progressive) and 20 healthy controls (HC) received clinical and upper cSC MRI assessments over 1.10±0.28 years. cSC compartments were quantified on MRI using the novel averaged magnetization inversion recovery acquisitions sequence (in-plane resolution=0.67 × 0.67mm2), and in-house developed post-processing methods. Patients were stratified regarding clinical progression. RESULTS: Patients with clinical progression showed faster reduction of cSC areas over time at the level of cSC enlargement (approximate vertebral level C4-C5) compared to stable patients (p<0.05). In addition, when compared to the rostral-cSC (approximate vertebral level C2-C3), a preferential reduction of cSC and white matter areas over time at the level of cSC enlargement (p<0.05 and p<0.01, respectively) was demonstrated only in patients with clinical progression, but not in stable MS patients and HC. Compared to HC, MS patients showed comparable changes over time in all cSC compartments. CONCLUSIONS: MS patients with clinical disease progression demonstrate subtle signs of a more pronounced tissue loss at the level of cSC enlargement. Future studies should consider larger sample sizes and more extended observation periods.

Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis.

BACKGROUND: Retinal degeneration leading to optical coherence tomography (OCT) changes is frequent in patients with multiple sclerosis (PwMS). OBJECTIVE: To investigate associations among OCT changes, MRI measurements of global and regional brain volume loss, and physical and cognitive impairment in PwMS. METHODS: 95 PwMS and 52 healthy controls underwent OCT and MRI examinations. Mean peripapillary retinal nerve fiber layer (pRNFL) thickness and ganglion cell/inner plexiform layer (GCIPL) volume were measured. In PwMS disability was quantified with the Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). Associations between OCT, MRI, and clinical measures were investigated with multivariable regression models. RESULTS: In PwMS, pRNFL and GCIPL were associated with the volume of whole brain (p < 0.04), total gray matter (p < 0.002), thalamus (p ≤ 0.04), and cerebral cortex (p ≤ 0.003) -both globally and regionally-, but not white matter. pRNFL and GCIPL were also inversely associated with T2-lesion volume (T2LV), especially in the optic radiations (p < 0.0001). The brain volumes associated with EDSS and SDMT significantly overlapped with those correlating with pRNFL and GCIPL. CONCLUSIONS: In PwMS, pRNFL and GCIPL reflect the integrity of clinically-relevant gray matter structures, underling the value of OCT measures as markers of neurodegeneration and disability in multiple sclerosis.

A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients.

BACKGROUND: Detecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarged white matter lesions (NELs) in the follow-up of MS patients; however, multicenter validation studies are lacking. PURPOSE: To assess the accuracy of LeMan-PV for the longitudinal detection NEL white-matter MS lesions in a multicenter clinical setting. STUDY TYPE: Retrospective, longitudinal. SUBJECTS: A total of 206 patients with a definitive MS diagnosis and at least two follow-up MRI studies from five centers participating in the Swiss Multiple Sclerosis Cohort study. Mean age at first follow-up = 45.2 years (range: 36.9-52.8 years); 70 males. FIELD STRENGTH/SEQUENCE: Fluid attenuated inversion recovery (FLAIR) and T1-weighted magnetization prepared rapid gradient echo (T1-MPRAGE) sequences at 1.5 T and 3 T. ASSESSMENT: The study included 313 MRI pairs of datasets. Data were analyzed with LeMan-PV and compared with a manual "reference standard" provided by a neuroradiologist. A second rater (neurologist) performed the same analysis in a subset of MRI pairs to evaluate the rating-accuracy. The Sensitivity (Se), Specificity (Sp), Accuracy (Acc), F1-score, lesion-wise False-Positive-Rate (aFPR), and other measures were used to assess LeMan-PV performance for the detection of NEL at 1.5 T and 3 T. The performance was also evaluated in the subgroup of 123 MRI pairs at 3 T. STATISTICAL TESTS: Intraclass correlation coefficient (ICC) and Cohen's kappa (CK) were used to evaluate the agreement between readers. RESULTS: The interreader agreement was high for detecting new lesions (ICC = 0.97, Pvalue < 10-20 , CK = 0.82, P value = 0) and good (ICC = 0.75, P value < 10-12 , CK = 0.68, P value = 0) for detecting enlarged lesions. Across all centers, scanner field strengths (1.5 T, 3 T), and for NEL, LeMan-PV achieved: Acc = 61%, Se = 65%, Sp = 60%, F1-score = 0.44, aFPR = 1.31. When both follow-ups were acquired at 3 T, LeMan-PV accuracy was higher (Acc = 66%, Se = 66%, Sp = 66%, F1-score = 0.28, aFPR = 3.03). DATA CONCLUSION: In this multicenter study using clinical data settings acquired at 1.5 T and 3 T, and variations in MRI protocols, LeMan-PV showed similar sensitivity in detecting NEL with respect to other recent 3 T multicentric studies based on neural networks. While LeMan-PV performance is not optimal, its main advantage is that it provides automated clinical decision support integrated into the radiological-routine flow. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis.

Quantitative MRI (qMRI) probes the microstructural properties of the central nervous system (CNS) by providing biophysical measures of tissue characteristics. In this work, we aimed to (i) identify qMRI measures that distinguish histological lesion types in postmortem multiple sclerosis (MS) brains, especially the remyelinated ones; and to (ii) investigate the relationship between those measures and quantitative histological markers of myelin, axons, and astrocytes in the same experimental setting. Three fixed MS whole brains were imaged with qMRI at 3T to obtain magnetization transfer ratio (MTR), myelin water fraction (MWF), quantitative T1 (qT1), quantitative susceptibility mapping (QSM), fractional anisotropy (FA) and radial diffusivity (RD) maps. The identification of lesion types (active, inactive, chronic active, or remyelinated) and quantification of tissue components were performed using histological staining methods as well as immunohistochemistry and immunofluorescence. Pairwise logistic and LASSO regression models were used to identify the best qMRI discriminators of lesion types. The association between qMRI and quantitative histological measures was performed using Spearman's correlations and linear mixed-effect models. We identified a total of 65 lesions. MTR and MWF best predicted the chance of a lesion to be remyelinated, whereas RD and QSM were useful in the discrimination of active lesions. The measurement of microstructural properties through qMRI did not show any difference between chronic active and inactive lesions. MWF and RD were associated with myelin content in both lesions and normal-appearing white matter (NAWM), FA was the measure most associated with axon content in both locations, while MWF was associated with astrocyte immunoreactivity only in lesions. Moreover, we provided evidence of extensive astrogliosis in remyelinated lesions. Our study provides new information on the discriminative power of qMRI in differentiating MS lesions -especially remyelinated ones- as well as on the relative association between multiple qMRI measures and myelin, axon and astrocytes.

Anterior horn atrophy in the cervical spinal cord: A new biomarker in progressive multiple sclerosis.

BACKGROUND: Spinal cord (SC) gray and white matter pathology plays a central role in multiple sclerosis (MS). OBJECTIVE: We aimed to investigate the extent, pattern, and clinical relevance of SC gray and white matter atrophy in vivo. METHODS: 39 relapsing-remitting patients (RRMS), 40 progressive MS patients (PMS), and 24 healthy controls (HC) were imaged at 3T using the averaged magnetization inversion recovery acquisitions sequence. Total and lesional cervical gray and white matter, and posterior (SCPH) and anterior horn (SCAH) areas were automatically quantified. Clinical assessment included the expanded disability status scale, timed 25-foot walk test, nine-hole peg test, and the 12-item MS walking scale. RESULTS: PMS patients had significantly reduced cervical SCAH - but not SCPH - areas compared with HC and RRMS (both p < 0.001). In RRMS and PMS, the cervical SCAH areas increased significantly less in the region of cervical SC enlargement compared with HC (all p < 0.001). This reduction was more pronounced in PMS compared with RRMS (both p < 0.001). In PMS, a lower cervical SCAH area was the most important magnetic resonance imaging (MRI)-variable for higher disability scores. CONCLUSION: MS patients show clinically relevant cervical SCAH atrophy, which is more pronounced in PMS and at the level of cervical SC enlargement.