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. 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. 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). 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.

BACKGROUND AND PURPOSE: Postgadolinium MR imaging is crucial for brain tumor diagnosis and morphometric assessment. We compared brain tumor enhancement visualization and the “target” object morphometry obtained with the most commonly used 3D MR imaging technique, MPRAGE, with 2 other routinely available techniques: sampling perfection with application-optimized contrasts by using different flip angle evolutions (SPACE) and volumetric interpolated brain examination (VIBE). MATERIALS AND METHODS: Fifty-four contrast-enhancing tumors (38 gliomas and 16 metastases) were assessed using MPRAGE, VIBE, and SPACE techniques randomly acquired after gadolinium-based contrast agent administration on a 3T scanner. Enhancement conspicuity was assessed quantitatively by calculating the contrast rate and contrast-to-noise ratio, and qualitatively, by consensus visual comparative ratings. The total enhancing tumor volume and between-sequence discrepancy in the margin delineation were assessed on the corresponding 3D target objects contoured with a computer-assisted software for neuronavigation. The Wilcoxon signed rank and Pearson χ² nonparametric tests were used to investigate between-sequence discrepancies in the contrast rate, contrast-to-noise ratio, visual conspicuity ratings, tumor volume, and margin delineation estimates. Differences were also tested for 1D (Response Evaluation Criteria in Solid Tumors) and 2D (Response Assessment in Neuro-Oncology) measurements. RESULTS: Compared with MPRAGE, both SPACE and VIBE obtained higher contrast rate, contrast-to-noise ratio, and visual conspicuity ratings in both gliomas and metastases (P range, <.001–.001). The between-sequence 3D target object margin discrepancy ranged between 3% and 19.9% of lesion tumor volume. Larger tumor volumes, 1D and 2D measurements were obtained with SPACE (P range, <.01–.007). CONCLUSIONS: Superior conspicuity for brain tumor enhancement can be achieved using SPACE and VIBE techniques, compared with MPRAGE. Discrepancies were also detected when assessing target object size and morphology, with SPACE providing more accurate estimates.

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and monitoring of cord compression or neurodegenerative diseases such as multiple sclerosis. While several semi and automatic methods exist, one key limitation remains: the segmentation depends on the MRI contrast, resulting in different CSA across contrasts. This is partly due to the varying appearance of the boundary between the spinal cord and the cerebrospinal fluid that depends on the sequence and acquisition parameters. This contrast-sensitive CSA adds variability in multi-center studies where protocols can vary, reducing the sensitivity to detect subtle atrophies. Moreover, existing methods enhance the CSA variability by training one model per contrast, while also producing binary masks that do not account for partial volume effects. In this work, we present a deep learning-based method that produces soft segmentations of the spinal cord that are stable across MRI contrasts. Using the Spine Generic Public Database of healthy participants (n=267; contrasts=6), we first generated participant-wise soft ground truth (GT) by averaging the binary segmentations across all 6 contrasts. These soft GT, along with aggressive data augmentation and a regression-based loss function, were then used to train a U-Net model for spinal cord segmentation. We evaluated our model against state-of-the-art methods and performed ablation studies involving different GT mask types, loss functions, contrast-specific models and domain generalization methods. Our results show that using the soft average segmentations along with a regression loss function reduces CSA variability (p<0.05, Wilcoxon signed-rank test). The proposed spinal cord segmentation model generalizes better than the state-of-the-art contrast-specific methods amongst unseen datasets, vendors, contrasts, and pathologies (compression, lesions), while accounting for partial volume effects. Our model is integrated into the Spinal Cord Toolbox (v6.2 and higher).

Background: Phase II and observational studies support the use of rituximab in multiple sclerosis. Standard protocols are lacking, but studies suggest comparable efficacy between low- and high-dose regimens. Objective: To evaluate effectiveness and safety of de-escalating rituximab dose from 1000 to 500 mg/6 months in multiple sclerosis. Methods: Patients were switched from rituximab 1000 to 500 mg/6 months and prospectively followed for 12 months. Relapses, disability, occurrence of brain/spinal magnetic resonance imaging (MRI) lesions, serum neurofilament light chain (NfL), CD19⁺ B cell, and IgG concentrations were analyzed. Results: Fifty-nine patients were included (37 relapsing-remitting, 22 secondary progressive). No relapses occurred, with no difference in expanded disability status scale (EDSS) between baseline (4 (2.5–4.5) and 12 months (3.5 (2.5–5.5) p = 0.284). Overall, three new T2 lesions appeared during follow-up. NfL concentration was stable between baseline (7.9 (5.9–45.2) pg/mL) and 12 months (9.1 (5.9–21.3) pg/mL, p = 0.120). IgG concentrations decreased with greater rituximab load (coefficient = −0.439, p = 0.041). IgG deficient patients had greater risk of infections (OR = 6.27, 95% CI = 1.71–22.9, p = 0.005). Conclusion: De-escalating rituximab dose from 1000 to 500 mg/6 months is safe, results in clinical and radiological stability, and does not affect serum NfL over 12 months. Rituximab load negatively influences IgG concentrations, and IgG deficient patients are at higher risk of infections.

BACKGROUND AND PURPOSE: Ischemic stroke can be mimicked by nonischemic conditions. Due to emphasis on the rapid treatment of acute ischemic stroke, it is crucial to identify these conditions to avoid unnecessary therapies and potential complications. We investigated the performance of the multimodal CT protocol (unenhanced brain CT, CTA, and CTP) to discriminate stroke mimics from acute ischemic stroke. MATERIALS AND METHODS: We retrospectively selected multimodal CT studies performed for clinical suspicion of acute ischemic stroke in our center in a 24-month period, including patients with at least 1 follow-up imaging study (brain CT or MR imaging). Hemorrhagic strokes were excluded. We measured the performance of multimodal CT, comparing the original diagnostic results with the final clinical diagnosis at discharge. RESULTS: Among 401 patients, a stroke mimic condition was diagnosed in 89 (22%), including seizures (34.8%), migraine with aura attack (12.4%), conversion disorder (12.4%), infection (7.9%), brain tumor (7.9%), acute metabolic condition (6.7%), peripheral vertigo (5.6%), syncope (5.6%), transient global amnesia (3.4%), subdural hematoma (1.1%), cervical epidural hematoma (1.1%), and dural AVF (1.1%). Multimodal CT sensitivity, specificity, and accuracy were 24.7%, 99.7%, and 83%. Multimodal CT revealed peri-ictal changes in 13/31 seizures and diagnosed 7/7 brain tumors, 1/1 dural AVF, and 1/1 subdural hematoma. CT perfusion played a pivotal diagnostic role. CONCLUSIONS: Multimodal CT demonstrated low sensitivity but high specificity in the diagnosis of stroke mimics in the acute setting. The high specificity of multimodal CT allows ruling out stroke and thereby avoiding unnecessary revascularization treatment in patients with diagnosis of a stroke mimic.

Spinal magnetic resonance imaging (MRI) is currently not recommended for the routine monitoring of clinically stable multiple sclerosis (MS) patients. We aimed to investigate the occurrence of asymptomatic spinal lesions (a-SL) in clinically stable MS patients, and their association with clinical and radiological outcomes, including the recurrence of spinal lesions. The hospital MS registry was searched for clinically stable MS patients (no relapses, no disability progression) with spinal MRIs performed at T1 (baseline) and T2 (9–36 months after T1). Information on relapses, disability and new brain/spinal MRI lesions at T3 (≥6 months after T2) was collected and analyzed. Out of 300 MS patients, 45 showed a-SL between T1 and T2. The presence of a-SL was not associated with the subsequent occurrence of relapses or disability progression at T3, but did correlate with the risk of new brain (rate ratio (RR) = 1.63, 95% CI = 1.16−2.25, p = 0.003) and recurrent spinal lesions (RR = 7.28, 95% CI = 4.02–13.22, p < 0.0001). Accounting for asymptomatic brain lesions (a-BL), the presence of either a-BL or a-SL was associated with subsequent risk for new brain (OR = 1.81, 95% CI = 1.25–2.60, p = 0.001) or spinal (RR = 2.63, 95% CI = 1.27–5.45, p = 0.009) lesions. Asymptomatic spinal demyelinating lesions occurred in 15% of clinically stable MS patients within a median period of 14 months and conferred an increased risk of future radiological activity at the brain and spinal level.