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Gray matter (GM) atrophy and white matter (WM) lesions may contribute to cognitive decline in patients with delayed neurological sequelae (DNS) after carbon monoxide (CO) poisoning. However, there is currently a lack of evidence supporting this relationship. This study aimed to investigate the volume of GM, cortical thickness, and burden of WM lesions in 33 DNS patients with dementia, 24 DNS patients with mild cognitive impairment, and 51 healthy controls. Various methods, including voxel‐based, deformation‐based, surface‐based, and atlas‐based analyses, were used to examine GM structures. Furthermore, we explored the connection between GM volume changes, WM lesions burden, and cognitive decline. Compared to the healthy controls, both patient groups exhibited widespread GM atrophy in the cerebral cortices (for volume and cortical thickness), subcortical nuclei (for volume), and cerebellum (for volume) (p <.05 corrected for false discovery rate [FDR]). The total volume of GM atrophy in 31 subregions, which included the default mode network (DMN), visual network (VN), and cerebellar network (CN) (p <.05, FDR‐corrected), independently contributed to the severity of cognitive impairment (p <.05). Additionally, WM lesions impacted cognitive decline through both direct and indirect effects, with the latter mediated by volume reduction in 16 subregions of cognitive networks (p <.05). These preliminary findings suggested that both GM atrophy and WM lesions were involved in cognitive decline in DNS patients following CO poisoning. Moreover, the reduction in the volume of DMN, VN, and posterior CN nodes mediated the WM lesions‐induced cognitive decline. [ABSTRACT FROM AUTHOR]

We previously showed that dual‐task cost (DTC) on gait speed in people with Parkinson's disease (PD) improved after 6 weeks of the Agility Boot Camp with Cognitive Challenge (ABC‐C) exercise program. Since deficits in dual‐task gait speed are associated with freezing of gait and gray matter atrophy, here we performed preplanned secondary analyses to answer two questions: (a) Do people with PD who are freezers present similar improvements compared to nonfreezers in DTC on gait speed with ABC‐C? (b) Can cortical thickness at baseline predict responsiveness to the ABC‐C? The DTC from 39 freezers and 43 nonfreezers who completed 6 weeks of ABC‐C were analyzed. A subset of 51 participants (21 freezers and 30 nonfreezers) with high quality imaging data were used to characterize relationships between baseline cortical thickness and delta (Δ) DTC on gait speed following ABC‐C. Freezers showed larger ΔDTC on gait speed than nonfreezers with ABC‐C program (p <.05). Cortical thickness in visual and fronto‐parietal areas predicted ΔDTC on gait speed in freezers, whereas sensorimotor‐lateral thickness predicted ΔDTC on gait speed in nonfreezers (p <.05). When matched for motor severity, visual cortical thickness was a common predictor of response to exercise in all individuals, presenting the largest effect size. In conclusion, freezers improved gait automaticity even more than nonfreezers from cognitively challenging exercise. DTC on gait speed improvement was associated with larger baseline cortical thickness from different brain areas, depending on freezing status, but visual cortex thickness showed the most robust relationship with exercise‐induced improvements in DTC. [ABSTRACT FROM AUTHOR]

Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders. Diffeomorphic registration‐based cortical thickness (DiReCT) is a known technique to derive such measures from non‐surface‐based volumetric tissue maps. ANTs provides an open‐source method for estimating cortical thickness, derived by applying DiReCT to an atlas‐based segmentation. In this paper, we propose DL+DiReCT, a method using high‐quality deep learning‐based neuroanatomy segmentations followed by DiReCT, yielding accurate and reliable cortical thickness measures in a short time. We evaluate the methods on two independent datasets and compare the results against surface‐based measures from FreeSurfer. Good correlation of DL+DiReCT with FreeSurfer was observed (r =.887) for global mean cortical thickness compared to ANTs versus FreeSurfer (r =.608). Experiments suggest that both DiReCT‐based methods had higher sensitivity to changes in cortical thickness than Freesurfer. However, while ANTs showed low scan‐rescan robustness, DL+DiReCT showed similar robustness to Freesurfer. Effect‐sizes for group‐wise differences of healthy controls compared to individuals with dementia were highest with the deep learning‐based segmentation. DL+DiReCT is a promising combination of a deep learning‐based method with a traditional registration technique to detect subtle changes in cortical thickness. [ABSTRACT FROM AUTHOR]

Abstract: In this article, SIENA‐XL, a new segmentation‐based longitudinal pipeline is introduced, for: (i) increasing the precision of longitudinal volume change estimation for white (WM) and gray (GM) matter separately, compared with cross‐sectional segmentation methods such as SIENAX; and (ii) avoiding potential biases in registration‐based methods when Jacobians are used, with a smoothing extent larger than spatial scale between tissue‐interfaces, which is where atrophy usually occurs. SIENA‐XL implements a new brain extraction procedure and a multi‐time‐point intensity equalization step before performing the final segmentation that also includes separate segmentation of deep GM structures by using FMRIB's Integrated Registration and Segmentation Tool. The detection of GM and WM volume changes with SIENA‐XL was evaluated using different healthy control (HC) and multiple sclerosis (MS) MRI datasets and compared with the traditional SIENAX and two Jacobian‐based approaches, SPM12 and SIENAX‐JI (a version of SIENAX including Jacobian integration ‐ JI). In scan‐rescan data from HCs, SIENA‐XL showed: (i) a significant decrease in error, of 50–70% when compared with SIENAX; (ii) no significant differences in error when compared with SIENAX‐JI and SPM12 in a scan‐rescan HC dataset that included repositioning. When tested in a HC dataset with scan‐rescan both at baseline and after 1 year of follow‐up, SIENA‐XL showed: (i) significantly higher precision (P < 0.01) than SIENAX; (ii) no significant differences to SIENAX‐JI and SPM12. Finally, in a dataset of 79 MS patients with a 2 years follow‐up, SIENA‐XL showed a substantial reduction of sample size, by comparison with SIENAX, SIENAX‐JI, and SPM12, for detecting treatment effects of 25, 30, and 50%. Hum Brain Mapp 39:1063–1077, 2018. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Introduction Gray matter (GM) atrophy is common in multiple sclerosis (MS), but the relationship with white matter (WM) pathology is largely unknown. Some studies found a co-occurrence in specific systems, but a regional analysis across the brain in different clinical phenotypes is necessary to further understand the disease mechanism underlying GM atrophy in MS. Therefore, we investigated the association between regional GM atrophy and pathology in anatomically connected WM tracts. Methods Conventional and diffusion tensor imaging was performed at 3T in 208 patients with long-standing MS and 60 healthy controls. Deep and cortical GM regions were segmented and quantified, and both lesion volumes and average normal appearing WM fractional anisotropy of their associated tracts were derived using an atlas obtained by probabilistic tractography in the controls. Linear regression was then performed to quantify the amount of regional GM atrophy that can be explained by WM pathology in the connected tract. Results MS patients showed extensive deep and cortical GM atrophy. Cortical atrophy was particularly present in frontal and temporal regions. Pathology in connected WM tracts statistically explained both regional deep and cortical GM atrophy in relapsing-remitting (RR) patients, but only deep GM atrophy in secondary-progressive (SP) patients. Conclusion In RRMS patients, both deep and cortical GM atrophy were associated with pathology in connected WM tracts. In SPMS patients, only regional deep GM atrophy could be explained by pathology in connected WM tracts. This suggests that in SPMS patients cortical GM atrophy and WM damage are (at least partly) independent disease processes. Hum Brain Mapp, 36:1796-1807, 2015. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]