Automatic segmentation of white matter hyperintensities: validation and comparison with state-of-the-art methods on both Multiple Sclerosis and elderly subjects.

Different types of white matter hyperintensities (WMH) can be observed through MRI in the brain and spinal cord, especially Multiple Sclerosis (MS) lesions for patients suffering from MS and age-related WMH for subjects with cognitive disorders and/or elderly people. To better diagnose and monitor the disease progression, the quantitative evaluation of WMH load has proven to be useful for clinical routine and trials. Since manual delineation for WMH segmentation is highly time-consuming and suffers from intra and inter observer variability, several methods have been proposed to automatically segment either MS lesions or age-related WMH, but none is validated on both WMH types. Here, we aim at proposing the White matter Hyperintensities Automatic Segmentation Algorithm adapted to 3D T2-FLAIR datasets (WHASA-3D), a fast and robust automatic segmentation tool designed to be implemented in clinical practice for the detection of both MS lesions and age-related WMH in the brain, using both 3D T1-weighted and T2-FLAIR images. In order to increase its robustness for MS lesions, WHASA-3D expands the original WHASA method, which relies on the coupling of non-linear diffusion framework and watershed parcellation, where regions considered as WMH are selected based on intensity and location characteristics, and finally refined with geodesic dilation. The previous validation was performed on 2D T2-FLAIR and subjects with cognitive disorders and elderly subjects. 60 subjects from a heterogeneous database of dementia patients, multiple sclerosis patients and elderly subjects with multiple MRI scanners and a wide range of lesion loads were used to evaluate WHASA and WHASA-3D through volume and spatial agreement in comparison with consensus reference segmentations. In addition, a direct comparison on the MS database with six available supervised and unsupervised state-of-the-art WMH segmentation methods (LST-LGA and LPA, Lesion-TOADS, lesionBrain, BIANCA and nicMSlesions) with default and optimised settings (when feasible) was conducted. WHASA-3D confirmed an improved performance with respect to WHASA, achieving a better spatial overlap (Dice) (0.67 vs 0.63), a reduced absolute volume error (AVE) (3.11 vs 6.2 mL) and an increased volume agreement (intraclass correlation coefficient, ICC) (0.96 vs 0.78). Compared to available state-of-the-art algorithms on the MS database, WHASA-3D outperformed both unsupervised and supervised methods when used with their default settings, showing the highest volume agreement (ICC = 0.95) as well as the highest average Dice (0.58). Optimising and/or retraining LST-LGA, BIANCA and nicMSlesions, using a subset of the MS database as training set, resulted in improved performances on the remaining testing set (average Dice: LST-LGA default/optimized = 0.41/0.51, BIANCA default/optimized = 0.22/0.39, nicMSlesions default/optimized = 0.17/0.63, WHASA-3D = 0.58). Evaluation and comparison results suggest that WHASA-3D is a reliable and easy-to-use method for the automated segmentation of white matter hyperintensities, for both MS lesions and age-related WMH. Further validation on larger datasets would be useful to confirm these first findings.

Neuroimaging correlates of persistent fatigue in older adults: A secondary analysis from the Multidomain Alzheimer Preventive Trial (MAPT) trial.

OBJECTIVES: Fatigue has been suggested as a marker of biological aging. It seems plausible that this symptom might be associated with changes in brain health. The objective of this study was to examine the associations between persistent fatigue and neuroimaging correlates in a non-disease-specific population of community-dwelling older adults. METHODS: We performed a cross-sectional analysis using data from The Multidomain Alzheimer Preventive Trial (MAPT). We included 458 subjects. Persistent fatigue was defined as meeting exhaustion criterion of Fried frailty phenotype in two consecutive clinical visits six months apart between study baseline and one year. Brain imaging correlates, assessed by magnetic resonance imaging (MRI), were the outcomes. The associations between persistent fatigue and brain correlates were explored using mixed model linear regressions with random effect at the center level. RESULTS: The mean age of the participants was 74.8 ± 4 years old, and 63% of the subjects were women. Forty-seven participants (10%) exhibited a persistent fatigue profile. People with persistent fatigue were older compared to subjects without persistent fatigue (76.2 years ± 4.3 vs.74.7 ± 3.9 p = 0.009). Persistent fatigue was associated with higher white matter hyperintensity volume in the fully adjusted analysis. We did not find any cross-sectional association between persistent fatigue and sub-cortical volumes and global and regional cortical thickness. CONCLUSION: Persistent fatigue was cross-sectionnally associated with higher white matter hyperintensity volume in older adults. Further longitudinal studies, using an assessment tool specifically designed and validated for measuring fatigue, are needed to confirm our findings.

Impact of multidomain preventive strategies on functional brain connectivity in older adults with cognitive complaint: Subset from the Montpellier center of the ancillary MAPT-MRI study.

Introduction: The impact of multi-domain preventive interventions on older adults, in particular on those with higher risk to develop Alzheimer's disease (AD), could be beneficial, as it may delay cognitive decline. However, the precise mechanism of such positive impact is not fully understood and may involve brain reserve and adaptability of brain functional connectivity (FC). Methods: To determine the effect of multidomain interventions (involving physical activity, cognitive training, nutritional counseling alone or in combination with omega-3 fatty acid supplementation and vs. a placebo) on the brain, longitudinal FC changes were assessed after 36 months of intervention on 100 older adults (above 70 year-old) with subjective cognitive complaints. Results: No global change in FC was detected after uni or multidomain preventive interventions. However, an effect of omega-3 fatty acid supplementation dependent on cognitive decline status was underlined for frontoparietal, salience, visual and sensorimotor networks FC. These findings were independent of the cortical thickness and vascular burden. Discussion: These results emphasize the importance of patient stratification, based on risk factors, for preventive interventions.