Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes

Background: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes.Methods: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups.Results: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes.Conclusions: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor

Asymmetries and visual field summaries as predictors of glaucoma in the ocular hypertension treatment study

PURPOSE. To evaluate whether baseline visual field data and asymmetries between eyes predict the onset of primary open-angle glaucoma (POAG) in Ocular Hypertension Treatment Study (OHTS) participants. METHODS. A new index, mean prognosis (MP), was designed for optimal combination of visual field thresholds, to discriminate between eyes that developed POAG from eyes that did not. Baseline intraocular pressure (IOP) in fellow eyes was used to construct measures of IOP asymmetry. Age-adjusted baseline thresholds were used to develop indicators of visual field asymmetry and summary measures of visual field defects. Marginal multivariate failure time models were constructed that relate the new index MP, IOP asymmetry, and visual field asymmetry to POAG onset for OHTS participants. RESULTS. The marginal multivariate failure time analysis showed that the MP index is significantly related to POAG onset (P &lt; 0.0001) and appears to be a more highly significant predictor of POAG onset than either mean deviation (MD; P = 0.17) or pattern standard deviation (PSD; P = 0.046). A 1-mm Hg increase in IOP asymmetry between fellow eyes is associated with a 17% increase in risk for development of POAG. When threshold asymmetry between eyes existed, the eye with lower thresholds was at a 37% greater risk of development of POAG, and this feature was more predictive of POAG onset than the visual field index MD, though not as strong a predictor as PSD. CONCLUSIONS. The MP index, IOP asymmetry, and binocular test point asymmetry can assist in clinical evaluation of eyes at risk of development of POAG.</p