Objective

To investigate the relationship between brain volume and disability worsening over ≥3 years in the natural history of primary progressive multiple sclerosis using data from the placebo group of the INFORMS trial (n = 487; clinicaltrials.gov NCT00731692).

Methods

Magnetic resonance imaging scans were collected annually. Brain volume loss was determined using SIENA. Patients were stratified by baseline normalized brain volume after adjusting for demographic and disease-burden covariates.

Results

Baseline normalized brain volume was predictive of disability worsening: Risk of 3-month confirmed disability progression was reduced by 36% for high versus low baseline normalized brain volume (Cox's model hazard ratio 0.64, P = 0.0339; log-rank test: P = 0.0297). Moreover, on-study brain volume loss was significantly associated with disability worsening (P = 0.012) and was evident in patients with or without new lesions or relapses. Brain volume loss depended significantly on baseline T2 lesion volume (P < 0.0001). Despite low inflammatory activity at baseline (13% of patients had gadolinium-enhancing lesions) and throughout the study (mean 0.5 new/enlarging T2 lesions and 172 mm³ T2 lesion volume increase per year), baseline T2 lesion volume was substantial (mean 10 cm³). Lower normalized brain volume at baseline correlated with higher baseline T2 volume and older age (both P < 0.0001).

Interpretation

Baseline brain volume and the rate of ongoing brain atrophy are significantly associated with disability worsening in primary progressive multiple sclerosis. Brain volume loss is significantly related to baseline T2 lesion volume, but partially independent of new lesion activity, which might explain the limited efficacy of anti-inflammatory treatment.

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.