Objective: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion-defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods. Methods: Thirty-eight MS patients were scanned with diffusion-weighted imaging, magnetization transfer imaging, and standard conventional MRI sequences (cMRI). A total of 499 regions of interest were identified on standard MRI and labeled as persistent black holes (PBH), persistent gray holes (PGH), acute black holes (ABH), acute gray holes (AGH), nonblack or gray holes (NBH), and normal appearing white matter (NAWM). DBSI, diffusion tensor imaging (DTI), and magnetization transfer ratio (MTR) were applied to the 43,261 imaging voxels extracted from these ROIs. The optimized DNN with 10 fully connected hidden layers was trained using the imaging metrics of the lesion subtypes and NAWM. Results: Concordance, sensitivity, specificity, and accuracy were determined for the different imaging methods. DBSI-DNN derived lesion classification achieved 93.4% overall concordance with predetermined lesion types, compared with 80.2% for DTI-DNN model, 78.3% for MTR-DNN model, and 74.2% for cMRI-DNN model. DBSI-DNN also produced the highest specificity, sensitivity, and accuracy. Conclusions: DBSI-DNN improves the classification of different MS lesion subtypes, which could aid clinical decision making. The efficacy and efficiency of DBSI-DNN shows great promise for clinical applications in automatic MS lesion detection and classification.

Gait impairments in persons with multiple sclerosis (pwMS) leading to decreased ambulation and reduced walking endurance remain poorly understood. our objective was to assess gait asymmetry (GA) and bilateral coordination of gait (BCG), among pwMS during the six-minute walk test (6MWT), and determine their association with disease severity. We recruited 92 pwMS (age: 46.6 ± 7.9; 83% females) with a range of clinical disability, who completed the 6MWT wearing gait analysis system. GA was assessed by comparing left and right swing times, and BcG was assessed by the phase coordination index (pci). Several functional and subjective gait assessments were performed. Results show that gait is more asymmetric and less coordinated as the disease progresses (p < 0.0001). Participants with mild MS showed significantly better BCG as reflected by lower PCI values in comparison to the other two MS severity groups (severe: p = 0.001, moderate: p = 0.02). GA and PCI also deteriorated significantly each minute during the 6MWT (p < 0.0001). GA and PCI (i.e., BCG) show weaker associations with clinical MS status than associations observed between functional and subjective gait assessments and MS status. Similar to other neurological cohorts, GA and pci may be important parameters to assess and target in interventions among pwMS. Multiple sclerosis (MS) is a degenerative, progressive, autoimmune disease of the central nervous system, often resulting in a continuous deterioration of walking 1. Hence, gait parameters, e.g. cadence, step-length, step-time, are impaired as compared to those measured in abled bodied individuals 1-4. This gait deterioration has been demonstrated as a decline in the ability to walk long distances, based on the 6-min or 500-m walk tests 5,6. One critical component of walking impairment is gait variability. Gait variability tends to change throughout the MS disease course, with greater variability in the higher levels of disability 7,8. Furthermore, gait variability is associated with increased fall risk 9. Human gait requires a high degree of symmetry and coordination. Gait asymmetry is associated with reduced walking velocity 10-12 and increased energy expenditure 13. Spinal cord injury is frequent in persons with multiple sclerosis (pwMS), noted in 83% by MRI and up to 99% at autopsy 14,15. Spinal cord injury is associated with lower extremity sensorimotor deficits and impaired ambulation. It was previously reported that walking velocity in pwMS was reduced when in vivo diffusion tensor imaging (DTI) of the cervical spinal cord reveals myelin and tissue injury within posterior columns (PC) and lateral corticospinal tracts (CST) 16. Since CST injury in pwMS is asymmetric 17 , we hypothesize that MS will be associated with increased gait asymmetry, since asymmetric lesions in the spinal white matter lesions have been shown to correspond to asymmetric motor function 18. Gait coordination is the ability to maintain a consistent phase-dependent cyclical relationship between different body segments or joints in...

Background Limited randomized controlled trials (RCTs) have been performed comparing endovascular thrombectomy (EVT) to medical therapy (MEDT) for acute ischemic stroke with extensive baseline ischemic injury (AIS-EBI). We conducted a systematic review and meta-analysis of RCTs reporting EVT for AIS-EBI. Methods Using the Nested Knowledge AutoLit software, we conducted a systematic literature review from inception to 12 February 2023 within Web of Science, Embase, Scopus, and PubMed databases. Results of the TESLA trial were included on 10 June 2023. We included RCTs that compared EVT to MEDT for AIS with large ischemic core volume. The primary outcome of interest was a modified Rankin Score (mRS) 0-2. Secondary outcomes of interest included early neurological improvement (ENI), mRS 0-3, thrombolysis in cerebral infarction (TICI) 2b-3, symptomatic intracranial hemorrhage (sICH), and mortality. A random-effects model was used to calculate risk ratios (RRs) and their corresponding 95% confidence intervals (CIs). Results We included four RCTs with 1310 patients, 661 of whom underwent EVT and 649 of whom were treated with MEDT. EVT was associated with greater rates of mRS 0-2 (RR = 2.33, 95% CI = 1.75–3.09; P-value < 0.001), mRS 0-3 (RR = 1.68, 95% CI = 1.33–2.12; P-value < 0.001), and ENI (RR = 2.24, 95% CI = 1.55–3.24; P-value < 0.001). Rates of sICH (RR = 1.99, 95% CI = 1.07–3.69; P-value = 0.03) were greater in the EVT group. Mortality (RR = 0.98, 95% CI = 0.83–1.15; P-value = 0.79) was comparable between the EVT and MEDT groups. The rate of successful reperfusion in the EVT group was 79.9% (95% CI = 75.6–83.6). Conclusions Although the rate of sICH was greater in the EVT group, EVT conferred a greater clinical benefit to MEDT for AIS-EBI based on available RCTs.

This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging.

Most studies define the technical success of endovascular thrombectomy (EVT) as a Thrombolysis in Cerebral Infarction (TICI) revascularization grade of 2b or higher. However, growing evidence suggests that TICI 3 is the best angiographic predictor of improved functional outcomes. To assess the association between successful TICI revascularization grades and functional independence at 90 days, we performed a systematic review and network meta-analysis of thrombectomy studies that reported TICI scores and functional outcomes, measured by the modified Rankin Scale, using the semi-automated AutoLit software platform. Forty studies with 8691 patients were included in the quantitative synthesis. Across TICI, modified TICI (mTICI), and expanded TICI (eTICI), the highest rate of good functional outcomes was observed in patients with TICI 3 recanalization, followed by those with TICI 2c and TICI 2b recanalization, respectively. Rates of good functional outcomes were similar among patients with either TICI 2c or TICI 3 grades. On further sensitivity analysis of the eTICI scale, the rates of good functional outcomes were equivalent between eTICI 2b50 and eTICI 2b67 (OR 0.81, 95% CI 0.52 to 1.25). We conclude that near complete or complete revascularization (TICI 2c/3) is associated with higher rates of functional outcomes after EVT.