overcoming the clinical mr imaging paradox of multiple sclerosis mr imaging data assessed with a random forest approach

BACKGROUND AND PURPOSE: In MS, the relation between clinical and MR imaging measures is still suboptimal. We assessed the correlation of disability and specific impairment of the clinical functional system with overall and regional CNS damage in a large cohort of patients with MS with different clinical phenotypes by using a random forest approach. MATERIALS AND METHODS: Brain conventional MR imaging and DTI were performed in 172 patients with MS and 46 controls. Cervical cord MR imaging was performed in a subgroup of subjects. To evaluate whether MR imaging measures were able to correctly classify impairment in specific clinical domains, we performed a random forest analysis. RESULTS: Between-group differences were found for most of the MR imaging variables, which correlated significantly with clinical measures ( r ranging from −0.57 to 0.55). The random forest analysis showed a high performance in identifying impaired versus unimpaired patients, with a global error between 7% (pyramidal functional system) and 31% (Ambulation Index) in the different outcomes considered. When considering the performance in the unimpaired and impaired groups, the random forest analysis showed a high performance in identifying patients with impaired sensory, cerebellar, and brain stem functions (error below 10%), while it performed poorly in defining impairment of visual and mental systems (error of 91% and 70%, respectively). In analyses with a good level of classification, for most functional systems, damage of the WM fiber bundles subserving their function, measured by using DTI tractography, had the highest classification power. CONCLUSIONS: Random forest analysis, especially if applied to DTI tractography data, is a valuable approach, which might contribute to overcoming the MS clinical−MR imaging paradox

Retinal Vascular Fractal Dimension, Childhood IQ, and Cognitive Ability in Old Age: The Lothian Birth Cohort Study 1936

<div><p>Purpose</p><p>Cerebral microvascular disease is associated with dementia. Differences in the topography of the retinal vascular network may be a marker for cerebrovascular disease. The association between cerebral microvascular state and non-pathological cognitive ageing is less clear, particularly because studies are rarely able to adjust for pre-morbid cognitive ability level. We measured retinal vascular fractal dimension (<i>D</i>_<i>f</i>) as a potential marker of cerebral microvascular disease. We examined the extent to which it contributes to differences in non-pathological cognitive ability in old age, after adjusting for childhood mental ability.</p><p>Methods</p><p>Participants from the Lothian Birth Cohort 1936 Study (LBC1936) had cognitive ability assessments and retinal photographs taken of both eyes aged around 73 years (<i>n</i> = 648). IQ scores were available from childhood. Retinal vascular <i>D</i>_<i>f</i> was calculated with monofractal and multifractal analysis, performed on custom-written software. Multiple regression models were applied to determine associations between retinal vascular <i>D</i>_<i>f</i> and general cognitive ability (<i>g</i>), processing speed, and memory.</p><p>Results</p><p>Only three out of 24 comparisons (two eyes × four <i>D</i>_<i>f</i> parameters × three cognitive measures) were found to be significant. This is little more than would be expected by chance. No single association was verified by an equivalent association in the contralateral eye.</p><p>Conclusions</p><p>The results show little evidence that fractal measures of retinal vascular differences are associated with non-pathological cognitive ageing.</p></div