Spinal cord reserve in multiple sclerosis.

BACKGROUND: The spinal cord (SC) is a preferential target of multiple sclerosis (MS) damage highly relevant towards disability. Differential impact of such damage could be due to the initial amount of SC tissue, as described for the brain parenchyma (brain reserve concept). We aimed to test the existence of SC reserve by using spinal canal area (SCaA) as a proxy. METHODS: Brain sagittal three-dimensional T1-weighted scans covering down to C5 level were acquired in 2930 people with MS and 43 healthy controls (HCs) in a cross-sectional, multicentre study. SC area (SCA) and SCaA were obtained with the Spinal Cord Toolbox. Demographical data and patient-derived disability scores were obtained. SC parameters were compared between groups with age-adjusted and sex-adjusted linear regression models. The main outcome of the study, the existence of an association between SCaA and Patient Determined Disease Steps, was tested with scaled linear models. RESULTS: 1747 persons with MS (mean age: 46.35 years; 73.2% female) and 42 HCs (mean age: 45.56 years; 78.6% female) were analysed after exclusion of post-processing errors and application of quality criteria. SCA (60.41 mm2 vs 65.02 mm2, p<0.001) was lower in people with MS compared with HC; no differences in SCaA were observed (213.24 mm2 vs 212.61 mm2, p=0.125). Adjusted scaled linear models showed that a larger SCaA was significantly associated with lower scores on Patient Determined Disease Steps (beta coefficient: -0.12, p=0.0124) independently of spinal cord atrophy, brain T2 lesion volume, age and sex. CONCLUSIONS: A larger SCaA may be protective against disability in MS, possibly supporting the existence of SC reserve.

Prognosis of a second clinical event from baseline MRI in patients with a CIS: a multicenter study using a machine learning approach.

PURPOSE: To predict the occurrence of a second clinical event in patients with a CIS suggestive of MS, from baseline magnetic resonance imaging (MRI), by means of a pattern recognition approach. METHODS: Two hundred sixty-six patients with a CIS were recruited from four participating centers. Over a follow-up of 3 years, 130 patients had a second clinical episode and 136 did not. Grey matter and white matter T1-hypointensities masks segmented from 3D T1-weighted images acquired on 3 T scanners were used as features for the classification approach. Differences between CIS that remained CIS and those that developed a second event were assessed at a global level and at a regional level, arranging the regions according to their contribution to the classification model. RESULTS: All classification metrics were around or even below 50% for both global and regional approaches. Accuracies did not change when T1-hypointensity maps were added to the model; just the specificity was increased up to 80%. Among the 30 regions with the largest contribution, 26 were grey matter and 4 were white matter regions. For grey matter, regions contributing showed either a larger or a smaller volume in the group of patients that remained CIS, compared to those with a second event. The volume of T1-hypointensities was always larger for the group that presented a second event. CONCLUSIONS: Prediction of a second clinical event in CIS patients from baseline MRI seems to present a highly heterogeneous pattern, leading to very low classification accuracies. Adding the T1-hypointensity maps does not seem to improve the accuracy of the classification model.

T1/T2-weighted ratio in multiple sclerosis: A longitudinal study with clinical associations.

BACKGROUND: T1w/T2-w ratio has been proposed as a clinically feasible MRI biomarker to assess tissue integrity in multiple sclerosis. However, no data is available in the earliest stages of the disease and longitudinal studies analysing clinical associations are scarce. OBJECTIVE: To describe longitudinal changes in T1-w/T2-w in patients with clinically isolated syndrome (CIS) and multiple sclerosis, and to investigate their clinical associations. METHODS: T1-w/T2-w images were generated and the mean value obtained in the corresponding lesion, normal-appearing grey (NAGM) and white matter (NAWM) masks. By co-registering baseline to follow-up MRI, evolved lesions were assessed; and by placing the mask of new lesions to the baseline study, the pre-lesional tissue integrity was measured. RESULTS: We included 171 CIS patients and 22 established multiple sclerosis patients. In CIS, evolved lesions showed significant T1-w/T2-w increases compared to baseline (+7.6%, P < 0.001). T1-w/T2-w values in new lesions were lower than in pre-lesional tissue (-28.2%, P < 0.001), and pre-lesional tissue was already lower than baseline NAWM (-7.8%, P < 0.001). In CIS at baseline, higher NAGM T1-w/T2-w was associated with multiple sclerosis diagnosis, and longitudinal decreases in NAGM and NAWM T1-w/T2-w were associated with disease activity. In established multiple sclerosis, T1-w/T2-w was inversely correlated with clinical disability and disease duration. CONCLUSION: A decrease in T1-w/T2-w ratio precedes lesion formation. In CIS, higher T1-w/T2-w was associated with multiple sclerosis diagnosis. In established multiple sclerosis, lower T1-w/T2-w values were associated with clinical disability. The possible differential impact of chronic inflammation, iron deposition and demyelination should be considered to interpret these findings.

Can Cognitive training Reignite Compensatory Mechanisms in Advanced Multiple Sclerosis Patients? An Explorative Morphological Network Approach.

Multiple Sclerosis (MS) has been shown to significantly impair brain connectivity, as alterations in functional and structural networks have been identified and associated with clinical status, particularly cognitive deficits. We aimed to identify structural connectivity changes in grey matter networks following cognitive rehabilitation (CR) in persons with MS (PwMS). Fifteen long-standing PwMS underwent a 5-week CR-program and five healthy controls (HC) were also investigated. T1-weighted MRI scans and neuropsychological tests were obtained before and after CR. T1-weighted scans were used to examine grey matter networks with graph analytic parameters [betweenness centrality (BC), degree (D), clustering (Cl), path length (PL) and small world properties: connectedness, gamma and lambda values]. Results were analysed at the whole brain level and for each brain lobe. Before CR, PwMS displayed lower values for D in the left parietal lobe (p = 0.009) compared to HC. After CR, significant increases in Cl located in frontal (p = 0.024) and temporal (p = 0.026) regions in PwMS were accompanied by significant decreases in PL located in the right parietal lobe (p = 0.025) and BC globally (p = 0.010). Overall, CR may prevent a network worsening in long-standing PwMS by increasing local efficiency of the brain and therefore facilitating compensation mechanisms.

Detection of lesions in the optic nerve with magnetic resonance imaging using a 3D convolutional neural network.

BACKGROUND: Optic neuritis (ON) is one of the first manifestations of multiple sclerosis, a disabling disease with rising prevalence. Detecting optic nerve lesions could be a relevant diagnostic marker in patients with multiple sclerosis. OBJECTIVES: We aim to create an automated, interpretable method for optic nerve lesion detection from MRI scans. MATERIALS AND METHODS: We present a 3D convolutional neural network (CNN) model that learns to detect optic nerve lesions based on T2-weighted fat-saturated MRI scans. We validated our system on two different datasets (N = 107 and 62) and interpreted the behaviour of the model using saliency maps. RESULTS: The model showed good performance (68.11% balanced accuracy) that generalizes to unseen data (64.11%). The developed network focuses its attention to the areas that correspond to lesions in the optic nerve. CONCLUSIONS: The method shows robustness and, when using only a single imaging sequence, its performance is not far from diagnosis by trained radiologists with the same constraint. Given its speed and performance, the developed methodology could serve as a first step to develop methods that could be translated into a clinical setting.