While a very-low fat, plant-based diet was well adhered to and tolerated, it resulted in no significant improvement on brain MRI, relapse rate or disability as assessed by EDSS scores in subjects with RRMS over one year. The diet group however showed significant improvements in measures of fatigue, BMI and metabolic biomarkers. The study was powered to detect only very large effects on MRI activity so smaller but clinically meaningful effects cannot be excluded. The diet intervention resulted in a beneficial effect on the self-reported outcome of fatigue but these results should be interpreted cautiously as a wait-list control group may not completely control for a placebo effect and there was a baseline imbalance on fatigue scores between the groups. If maintained, the improved lipid profile and BMI could yield long-term vascular health benefits. Longer studies with larger sample sizes are needed to better understand the long-term health benefits of this diet.

The risk of conversion from a clinically isolated syndrome to multiple sclerosis was significantly lower with minocycline than with placebo over 6 months but not over 24 months. (Funded by the Multiple Sclerosis Society of Canada; ClinicalTrials.gov number, NCT00666887 .).

Many current methods for multiple sclerosis (MS) lesion segmentation require radiologist seed points as input, but do not necessarily allow the expert to work in an intuitive or efficient way. Ironically, most methods also assume that the points are placed optimally. This paper examines how seed points can be processed with intuitive heuristics, which provide improved segmentation accuracy while facilitating quick and natural point placement. Using a large set of MRIs from an MS clinical trial, two radiologists are asked to seed the lesions while unaware that the points would be fed into a classifier, based on Parzen windows, that automatically delineates each marked lesion. To evaluate the impact of the new heuristics, an interactive region-growing method is used to provide ground truth and the Dice coefficient (DC) and Spearman’s rank correlation are used as the primary measures of agreement. A stratified analysis is performed to determine the effect on scans with low-, medium-, and high lesion loads. Compared to the unenhanced classifier, the heuristics dramatically improve the DC (+32.91 pt.) and correlation (+0.50) for the scans with low lesion loads, and also improve the DC (+14.55 pt.) and correlation (+0.15) for the scans with medium lesion loads, while having aminimal effect for the scans with high lesion loads, which are already segmented accurately by Parzen windows.With the heuristics, the DC is close to 80% and the correlation is above 0.9 for all three load categories.

BACKGROUND AND PURPOSE Multiple sclerosis (MS) diffusely abnormal white matter (DAWM) is a mildly hyperintense magnetic resonance imaging abnormality distinct from typical lesions. Our goal was to investigate the prevalence and natural history of DAWM in a large cohort (n = 348) of relapsing–remitting MS (RRMS) patients. METHODS The presence of DAWM and relationship to changes in T2 burden of disease (BOD), brain volume (brain fractional ratio, BFR), and disability (Expanded Disability Status Scale, EDSS) were investigated at baseline and year 7–8 (long‐term follow‐up, LTF). RESULTS DAWM was present in 25.3% (88 of 348) of patients at baseline. At LTF, DAWM was unchanged in 69.3% (61 of 88), decreased in 28.4% (25 of 88), and increased in 2.3% (2 of 88) of patients. Baseline BOD and change in BOD did not significantly differ between patients with and without DAWM. DAWM was associated with greater reduction in BFR at LTF (P = .038). DAWM and DAWM change did not predict EDSS or EDSS progression. CONCLUSIONS DAWM is present in a quarter of RRMS patients, and rarely increases or develops de novo. DAWM predicts brain atrophy but does not predict physical disability. Because of its posterior periventricular location, further investigation is warranted to evaluate its relationship to other measures of disability, including visual spatial processing and cognitive function.

Intensity variations can have a large impact on black hole-EDSS correlation. Restricting the measurement to a subset of the darkest voxels may yield stronger correlations.