Wei Chen1,2, Hai Lin3, Minrui Lyu4, Victoria J Wang5, Xiang Li6, Shixing Bao7, Guoping Sun2, Jun Xia4, Peijun Wang1. 1. Department of Radiology, Tongji Hospital, Tongji University School of Medicine, Shanghai, China. 2. Department of Radiology, Pingshan District People's Hospital, Pingshan General Hospital of Southern Medical University, Shenzhen, China. 3. Department of Neurosurgery, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China. 4. Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China. 5. Department of Nephrology, Tufts Medical Center, Boston, MA, USA. 6. Guangdong Provincial Key Laboratory of Brain Connectome and Behaviour, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China. 7. Department of Radiology, Osaka University, Osaka, Japan.
Abstract
BACKGROUND: Leukoaraiosis (LA) is a phenomenon of the brain that is often observed in elderly people. However, little is known about the role of LA in cognitive impairment in neurodegeneration and disease. This cross-sectional, retrospective Leukoaraiosis And Disability (LADIS) study aimed to characterize the relationship between brain white matter connectivity properties with LA ratings in patients with Alzheimer's disease (AD) as compared with age-matched cognitively normal controls. METHODS: Patients with AD (n=76) and elderly individuals with normal cognitive (NC) function (n=82) were classified into 3 groups, LA1, LA2, and LA3, according to the rating of their white matter changes (WMCs). Diffusion tensor imaging (DTI) data were analyzed by quantifying and comparing the white matter connectivity properties and gray matter (GM) volume of brain regions of interest (ROIs). RESULTS: The rich-club network properties in the AD LA1 and LA2 groups showed significant patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA1 and LA2 groups, respectively. However, the rich-club network properties in the AD LA3 group showed similar patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA3 group, despite there being significant hippocampal and amygdala atrophic differences between AD patients and NC elders. Compared to the NC LA1 group, the characteristic path length of white matter fiber connectivity in the NC LA3 group was significantly increased, and the brain's global efficiency, clustering coefficient, and network connectivity strength were significantly reduced (P<0.05, respectively). However, no significant differences (P>0.05) were observed in characteristic path length, reduced global efficiency, or the clustering coefficient between the NC LA3 and AD LA1 groups, or between the NC LA3 and AD LA2 groups. CONCLUSIONS: Our findings offer some insights into a potential role of LA in cognitive impairment that may predict the development of disability in older adults. The occurrence of LA, an intermediate degenerative change, during neurodegeneration and disease may potentially lead to the remodeling of the brain network through brain plasticity. LA, therefore, representing a possible compensatory mechanism to buffer cognitive decline. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: Leukoaraiosis (LA) is a phenomenon of the brain that is often observed in elderly people. However, little is known about the role of LA in cognitive impairment in neurodegeneration and disease. This cross-sectional, retrospective Leukoaraiosis And Disability (LADIS) study aimed to characterize the relationship between brain white matter connectivity properties with LA ratings in patients with Alzheimer's disease (AD) as compared with age-matched cognitively normal controls. METHODS: Patients with AD (n=76) and elderly individuals with normal cognitive (NC) function (n=82) were classified into 3 groups, LA1, LA2, and LA3, according to the rating of their white matter changes (WMCs). Diffusion tensor imaging (DTI) data were analyzed by quantifying and comparing the white matter connectivity properties and gray matter (GM) volume of brain regions of interest (ROIs). RESULTS: The rich-club network properties in the AD LA1 and LA2 groups showed significant patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA1 and LA2 groups, respectively. However, the rich-club network properties in the AD LA3 group showed similar patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA3 group, despite there being significant hippocampal and amygdala atrophic differences between AD patients and NC elders. Compared to the NC LA1 group, the characteristic path length of white matter fiber connectivity in the NC LA3 group was significantly increased, and the brain's global efficiency, clustering coefficient, and network connectivity strength were significantly reduced (P<0.05, respectively). However, no significant differences (P>0.05) were observed in characteristic path length, reduced global efficiency, or the clustering coefficient between the NC LA3 and AD LA1 groups, or between the NC LA3 and AD LA2 groups. CONCLUSIONS: Our findings offer some insights into a potential role of LA in cognitive impairment that may predict the development of disability in older adults. The occurrence of LA, an intermediate degenerative change, during neurodegeneration and disease may potentially lead to the remodeling of the brain network through brain plasticity. LA, therefore, representing a possible compensatory mechanism to buffer cognitive decline. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
Entities:
Keywords:
White matter hyperintensities (WMH); brain plasticity; network-based statistic (NBS); quantitative magnetic resonance imaging (qMRI); rich club; voxel-based morphometry (VBM)
Authors: Hae-Jeong Park; Marek Kubicki; Carl-Fredrik Westin; Ion-Florin Talos; Anders Brun; Steve Peiper; Ron Kikinis; Ference A Jolesz; Robert W McCarley; Martha E Shenton Journal: AJNR Am J Neuroradiol Date: 2004-09 Impact factor: 3.825
Authors: Madelaine Daianu; Neda Jahanshad; Talia M Nir; Clifford R Jack; Michael W Weiner; Matt A Bernstein; Paul M Thompson Journal: Hum Brain Mapp Date: 2015-06-03 Impact factor: 5.038
Authors: Alison D Murray; Roger T Staff; Christopher J McNeil; Sima Salarirad; Trevor S Ahearn; Nazahah Mustafa; Lawrence J Whalley Journal: Brain Date: 2011-11-18 Impact factor: 13.501
Authors: Joanna M Wardlaw; Eric E Smith; Geert J Biessels; Charlotte Cordonnier; Franz Fazekas; Richard Frayne; Richard I Lindley; John T O'Brien; Frederik Barkhof; Oscar R Benavente; Sandra E Black; Carol Brayne; Monique Breteler; Hugues Chabriat; Charles Decarli; Frank-Erik de Leeuw; Fergus Doubal; Marco Duering; Nick C Fox; Steven Greenberg; Vladimir Hachinski; Ingo Kilimann; Vincent Mok; Robert van Oostenbrugge; Leonardo Pantoni; Oliver Speck; Blossom C M Stephan; Stefan Teipel; Anand Viswanathan; David Werring; Christopher Chen; Colin Smith; Mark van Buchem; Bo Norrving; Philip B Gorelick; Martin Dichgans Journal: Lancet Neurol Date: 2013-08 Impact factor: 44.182
Authors: Guusje Collin; René S Kahn; Marcel A de Reus; Wiepke Cahn; Martijn P van den Heuvel Journal: Schizophr Bull Date: 2013-12-02 Impact factor: 9.306