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Kirby ED, Andrushko JW, Boyd LA, Koschutnig K, D'Arcy RCN. Sex differences in patterns of white matter neuroplasticity after balance training in young adults. Front Hum Neurosci 2024; 18:1432830. [PMID: 39257696 PMCID: PMC11383771 DOI: 10.3389/fnhum.2024.1432830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Accepted: 08/08/2024] [Indexed: 09/12/2024] Open
Abstract
Introduction In past work we demonstrated different patterns of white matter (WM) plasticity in females versus males associated with learning a lab-based unilateral motor skill. However, this work was completed in neurologically intact older adults. The current manuscript sought to replicate and expand upon these WM findings in two ways: (1) we investigated biological sex differences in neurologically intact young adults, and (2) participants learned a dynamic full-body balance task. Methods 24 participants (14 female, 10 male) participated in the balance training intervention, and 28 were matched controls (16 female, 12 male). Correlational tractography was used to analyze changes in WM from pre- to post-training. Results Both females and males demonstrated skill acquisition, yet there were significant differences in measures of WM between females and males. These data support a growing body of evidence suggesting that females exhibit increased WM neuroplasticity changes relative to males despite comparable changes in motor behavior (e.g., balance). Discussion The biological sex differences reported here may represent an important factor to consider in both basic research (e.g., collapsing across females and males) as well as future clinical studies of neuroplasticity associated with motor function (e.g., tailored rehabilitation approaches).
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Affiliation(s)
- Eric D Kirby
- BrainNet, Health and Technology District, Surrey, BC, Canada
- Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, BC, Canada
- Faculty of Science, Simon Fraser University, Burnaby, BC, Canada
| | - Justin W Andrushko
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, Tyne and Wear, United Kingdom
- Brain Behavior Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Lara A Boyd
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Brain Behavior Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Karl Koschutnig
- Institute of Psychology, BioTechMed Graz, University of Graz, Graz, Austria
| | - Ryan C N D'Arcy
- BrainNet, Health and Technology District, Surrey, BC, Canada
- Djavad Mowafaghian Center for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Faculty of Applied Sciences, Simon Fraser University, Burnaby, BC, Canada
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Li M, Izumoto M, Wang Y, Kato Y, Iwatani Y, Hirata I, Mizuno Y, Tachibana M, Mohri I, Kagitani-Shimono K. Altered white matter connectivity of ventral language networks in autism spectrum disorder: An automated fiber quantification analysis with multi-site datasets. Neuroimage 2024; 297:120731. [PMID: 39002786 DOI: 10.1016/j.neuroimage.2024.120731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 06/28/2024] [Accepted: 07/11/2024] [Indexed: 07/15/2024] Open
Abstract
Comprehension and pragmatic deficits are prevalent in autism spectrum disorder (ASD) and are potentially linked to altered connectivity in the ventral language networks. However, previous magnetic resonance imaging studies have not sufficiently explored the microstructural abnormalities in the ventral fiber tracts underlying comprehension dysfunction in ASD. Additionally, the precise locations of white matter (WM) changes in the long tracts of patients with ASD remain poorly understood. In the current study, we applied the automated fiber-tract quantification (AFQ) method to investigate the fine-grained WM properties of the ventral language pathway and their relationships with comprehension and symptom manifestation in ASD. The analysis included diffusion/T1 weighted imaging data of 83 individuals with ASD and 83 age-matched typically developing (TD) controls. Case-control comparisons were performed on the diffusion metrics of the ventral tracts at both the global and point-wise levels. We also explored correlations between diffusion metrics, comprehension performance, and ASD traits, and conducted subgroup analyses based on age range to examine developmental moderating effects. Individuals with ASD exhibited remarkable hypoconnectivity in the ventral tracts, particularly in the temporal portions of the left inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF). These WM abnormalities were associated with poor comprehension and more severe ASD symptoms. Furthermore, WM alterations in the ventral tract and their correlation with comprehension dysfunction were more prominent in younger children with ASD than in adolescents. These findings indicate that WM disruptions in the temporal portions of the left ILF/IFOF are most notable in ASD, potentially constituting the core neurological underpinnings of comprehension and communication deficits in autism. Moreover, impaired WM connectivity and comprehension ability in patients with ASD appear to improve with age.
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Affiliation(s)
- Min Li
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Maya Izumoto
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yide Wang
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoko Kato
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshiko Iwatani
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Hirata
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshifumi Mizuno
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
| | - Masaya Tachibana
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Mohri
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Kuriko Kagitani-Shimono
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan.
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Wang MB, Rahmani F, Benzinger TLS, Raji CA. Edge Density Imaging Identifies White Matter Biomarkers of Late-Life Obesity and Cognition. Aging Dis 2024; 15:1899-1912. [PMID: 37196133 PMCID: PMC11272213 DOI: 10.14336/ad.2022.1210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 12/10/2022] [Indexed: 05/19/2023] Open
Abstract
Alzheimer disease (AD) and obesity are related to disruptions in the white matter (WM) connectome. We examined the link between the WM connectome and obesity and AD through edge-density imaging/index (EDI), a tractography-based method that characterizes the anatomical embedding of tractography connections. A total of 60 participants, 30 known to convert from normal cognition or mild-cognitive impairment to AD within a minimum of 24 months of follow up, were selected from the Alzheimer disease Neuroimaging Initiative (ADNI). Diffusion-weighted MR images from the baseline scans were used to extract fractional anisotropy (FA) and EDI maps that were subsequently averaged using deterministic WM tractography based on the Desikan-Killiany atlas. Multiple linear and logistic regression analysis were used to identify the weighted sum of tract-specific FA or EDI indices that maximized correlation to body-mass-index (BMI) or conversion to AD. Participants from the Open Access Series of Imaging Studies (OASIS) were used as an independent validation for the BMI findings. The edge-density rich, periventricular, commissural and projection fibers were among the most important WM tracts linking BMI to FA as well as to EDI. WM fibers that contributed significantly to the regression model related to BMI overlapped with those that predicted conversion; specifically in the frontopontine, corticostriatal, and optic radiation pathways. These results were replicated by testing the tract-specific coefficients found using ADNI in the OASIS-4 dataset. WM mapping with EDI enables identification of an abnormal connectome implicated in both obesity and conversion to AD.
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Affiliation(s)
- Maxwell Bond Wang
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA.
- Medical Scientist Training Program, University of Pittsburgh/Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
| | - Tammie L. S Benzinger
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
| | - Cyrus A Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, Missouri, USA.
- Department of Neurology, Washington University in Saint Louis, St. Louis, Missouri, USA
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Zhang P, Feng Y, Xu T, Li Y, Xia J, Zhang H, Sun Z, Tian W, Zhang J. Brain white matter microstructural alterations in patients with systemic lupus erythematosus: an automated fiber quantification study. Brain Imaging Behav 2024; 18:622-629. [PMID: 38332385 DOI: 10.1007/s11682-024-00861-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2024] [Indexed: 02/10/2024]
Abstract
This study aimed to identify damaged segments of brain white matter fiber tracts in patients with systemic lupus erythematosus (SLE) using diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ), and analyze their relationship with cognitive impairment. Clinical and imaging data for 39 female patients with SLE and for 44 female healthy controls (HCs) were collected. AFQ was used to track whole-brain white matter tracts in each participant, and each tract was segmented into 100 equally spaced nodes. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated at each node. Correlations were also explored between DTI metrics in the damaged segments of white matter fiber tracts and neuropsychological test scores of patients with SLE. Compared with HCs, SLE patients exhibited significantly lower FA values, and significantly higher MD, AD, RD values in many white matter tracts (all P < 0.05, false discovery rate-corrected). FA values in nodes 97-100 of the left inferior fronto-occipital fasciculus (IFOF) positively correlated with the mini-mental state examination score. AFQ enables precise and accurate identification of damage to white matter fiber tracts in brains of patients with SLE. FA values in the left IFOF correlate with cognitive impairment in SLE.
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Affiliation(s)
- Peng Zhang
- Graduate School of Dalian Medical University, Liaoning, 116044, China
- The First Affiliated Hospital of Baotou Medical College, Baotou, 014010, China
| | - Yanhong Feng
- Graduate School of Dalian Medical University, Liaoning, 116044, China
| | - Tianye Xu
- Graduate School of Dalian Medical University, Liaoning, 116044, China
| | - Yifan Li
- School of Medicine, Nantong University, Jiangsu, 226019, China
| | - Jianguo Xia
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China.
| | - Hongxia Zhang
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China.
| | - Zhongru Sun
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
| | - Weizhong Tian
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
| | - Ji Zhang
- Department of Imaging, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, 225300, China
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Yan Z, Tan Z, Zhu Q, Shi Z, Feng J, Wei Y, Yin F, Wang X, Li Y. Cross-sectional and longitudinal evaluation of white matter microstructure damage and cognitive correlations by automated fibre quantification in relapsing-remitting multiple sclerosis patients. Brain Imaging Behav 2024:10.1007/s11682-024-00893-8. [PMID: 38814544 DOI: 10.1007/s11682-024-00893-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/02/2024] [Indexed: 05/31/2024]
Abstract
The purpose of this study was to characterize whole-brain white matter (WM) fibre tracts by automated fibre quantification (AFQ), capture subtle changes cross-sectionally and longitudinally in relapsing-remitting multiple sclerosis (RRMS) patients and explore correlations between these changes and cognitive performance A total of 114 RRMS patients and 71 healthy controls (HCs) were enrolled and follow-up investigations were conducted on 46 RRMS patients. Fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (AD), and radial diffusivity (RD) at each node along the 20 WM fibre tracts identified by AFQ were investigated cross-sectionally and longitudinally in entire and pointwise manners. Partial correlation analyses were performed between the abnormal metrics and cognitive performance. At baseline, compared with HCs, patients with RRMS showed a widespread decrease in FA and increases in MD, AD, and RD among tracts. In the pointwise comparisons, more detailed abnormalities were localized to specific positions. At follow-up, although there was no significant difference in the entire WM fibre tract, there was a reduction in FA in the posterior portion of the right superior longitudinal fasciculus (R_SLF) and elevations in MD and AD in the anterior and posterior portions of the right arcuate fasciculus (R_AF) in the pointwise analysis. Furthermore, the altered metrics were widely correlated with cognitive performance in RRMS patients. RRMS patients exhibited widespread WM microstructure alterations at baseline and alterations in certain regions at follow-up, and the altered metrics were widely correlated with cognitive performance in RRMS patients, which will enhance our understanding of WM microstructure damage and its cognitive correlation in RRMS patients.
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Affiliation(s)
- Zichun Yan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Zeyun Tan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Qiyuan Zhu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Zhuowei Shi
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Jinzhou Feng
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yiqiu Wei
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Feiyue Yin
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China
| | - Xiaohua Wang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China.
- College of Medical Informatics, Chongqing Medical University, Chongqing, China.
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, China.
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Lin F, Zou X, Su J, Wan L, Wu S, Xu H, Zeng Y, Li Y, Chen X, Cai G, Ye Q, Cai G. Cortical thickness and white matter microstructure predict freezing of gait development in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:16. [PMID: 38195780 PMCID: PMC10776850 DOI: 10.1038/s41531-024-00629-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 12/29/2023] [Indexed: 01/11/2024] Open
Abstract
The clinical applications of the association of cortical thickness and white matter fiber with freezing of gait (FoG) are limited in patients with Parkinson's disease (PD). In this retrospective study, using white matter fiber from diffusion-weighted imaging and cortical thickness from structural-weighted imaging of magnetic resonance imaging, we investigated whether a machine learning-based model can help assess the risk of FoG at the individual level in patients with PD. Data from the Parkinson's Disease Progression Marker Initiative database were used as the discovery cohort, whereas those from the Fujian Medical University Union Hospital Parkinson's Disease database were used as the external validation cohort. Clinical variables, white matter fiber, and cortical thickness were selected by random forest regression. The selected features were used to train the support vector machine(SVM) learning models. The median area under the receiver operating characteristic curve (AUC) was calculated. Model performance was validated using the external validation cohort. In the discovery cohort, 25 patients with PD were defined as FoG converters (15 men, mean age 62.1 years), whereas 60 were defined as FoG nonconverters (38 men, mean age 58.5 years). In the external validation cohort, 18 patients with PD were defined as FoG converters (8 men, mean age 66.9 years), whereas 37 were defined as FoG nonconverters (21 men, mean age 65.1 years). In the discovery cohort, the model trained with clinical variables, cortical thickness, and white matter fiber exhibited better performance (AUC, 0.67-0.88). More importantly, SVM-radial kernel models trained using random over-sampling examples, incorporating white matter fiber, cortical thickness, and clinical variables exhibited better performance (AUC, 0.88). This model trained using the above mentioned features was successfully validated in an external validation cohort (AUC, 0.91). Furthermore, the following minimal feature sets that were used: fractional anisotropy value and mean diffusivity value for right thalamic radiation, age at baseline, and cortical thickness for left precentral gyrus and right dorsal posterior cingulate gyrus. Therefore, machine learning-based models using white matter fiber and cortical thickness can help predict the risk of FoG conversion at the individual level in patients with PD, with improved performance when combined with clinical variables.
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Affiliation(s)
- Fabin Lin
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Xinyang Zou
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, 350001, Fujian, China
| | - Jiaqi Su
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350001, China
| | - Lijun Wan
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350001, China
| | - Shenglong Wu
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
- School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350001, China
| | - Haoling Xu
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
| | - Yuqi Zeng
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
| | - Yongjie Li
- College of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China
| | - Xiaochun Chen
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China
| | - Guofa Cai
- College of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China.
| | - Qinyong Ye
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China.
| | - Guoen Cai
- Department of Neurology, Center for Cognitive Neurology, Institute of Clinical Neurology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, 350001, China.
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Liu Y, Jiang Y, Du W, Gao B, Gao J, Hu S, Song Q, Wang W, Miao Y. White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance. Sci Rep 2024; 14:270. [PMID: 38167604 PMCID: PMC10762026 DOI: 10.1038/s41598-023-50768-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 12/25/2023] [Indexed: 01/05/2024] Open
Abstract
Microstructural abnormalities of white matter fiber tracts are considered as one of the etiology of diabetes-induced neurological disorders. We explored the cerebral white matter microstructure alteration accurately, and to analyze its correlation between cerebral small vessel disease (CSVD) burden and cognitive performance in type 2 diabetes mellitus (T2DM). The clinical-laboratory data, cognitive scores [including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), California verbal learning test (CVLT), and symbol digit modalities test (SDMT)], CSVD burden scores of the T2DM group (n = 34) and healthy control (HC) group (n = 21) were collected prospectively. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along primary white matter fiber tracts. Diffusion tensor images (DTI) metrics and 100 nodes of white matter fiber tracts between groups were compared. Multiple regression analysis was used to analyze the relationship between DTI metrics and cognitive scores and CSVD burden scores. For fiber-wise and node-wise, DTI metrics in some commissural and association fibers were increased in T2DM. Some white matter fiber tracts DTI metrics were independent predictors of cognitive scores and CSVD burden scores. White matter fiber tracts damage in patients with T2DM may be characterized in specific location, especially commissural and association fibers. Aberrational specific white matter fiber tracts are associated with visuospatial function and CSVD burden.
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Affiliation(s)
- Yangyingqiu Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
- Department of Radiology, Zibo Central Hospital, 54 Gongqingtuan Road, Zhangdian, Zibo, China
| | - Yuhan Jiang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Wei Du
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Bingbing Gao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Jie Gao
- Department of Neurology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Shuai Hu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Weiwei Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China.
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China.
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Li L, Yang W, Wan Y, Shen H, Wang T, Ping L, Liu C, Chen M, Yu H, Jin S, Cheng Y, Xu X, Zhou C. White matter alterations in mild cognitive impairment revealed by meta-analysis of diffusion tensor imaging using tract-based spatial statistics. Brain Imaging Behav 2023; 17:639-651. [PMID: 37656372 DOI: 10.1007/s11682-023-00791-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/28/2023] [Indexed: 09/02/2023]
Abstract
The neuropathological mechanism of mild cognitive impairment (MCI) remains unclarified. Diffusion tensor imaging (DTI) studies revealed white matter (WM) microarchitecture alterations in MCI, but consistent findings and conclusions have not yet been drawn. The present coordinate-based meta-analysis (CBMA) of tract-based spatial statistics (TBSS) studies aimed to identify the most prominent and robust WM abnormalities in patients with MCI. A systematic search of relevant studies was conducted through January 2022 to identify TBSS studies comparing fractional anisotropy (FA) between MCI patients and healthy controls (HC). We used the seed-based d mapping (SDM) software to achieve the CBMA and analyze regional FA alterations in MCI. Meta-regression analysis was subsequently applied to explore the potential associations between clinical variables and FA changes. MCI patients demonstrated significantly decreased FA in widely distributed areas in the corpus callosum (CC), including the genu, body, and splenium of the CC, as well as one cluster in the left striatum. FA in the body of the CC and in three clusters in the splenium of the CC was negatively associated with the mean age. Additionally, FA in the genu of the CC and in three clusters in the splenium of the CC had negative correlations with the MMSE scores. Disrupted integrities of the CC and left striatum might play vital roles in the process of cognitive decline. These findings enhanced our understanding of the neural mechanism underlying WM neurodegeneration in MCI and provided perspectives for the early detection and intervention of dementia.Registration number: CRD42022235716.
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Affiliation(s)
- Longfei Li
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Wei Yang
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Yu Wan
- School of Mental Health, Jining Medical University, Jining, China
| | - Hailong Shen
- School of Mental Health, Jining Medical University, Jining, China
| | - Ting Wang
- Outpatient Department, Affiliated Hospital of Jining Medical University, Jining, China
| | - Liangliang Ping
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Chuanxin Liu
- School of Mental Health, Jining Medical University, Jining, China
| | - Min Chen
- School of Mental Health, Jining Medical University, Jining, China
| | - Hao Yu
- School of Mental Health, Jining Medical University, Jining, China
| | - Shushu Jin
- Department of Psychology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Cong Zhou
- School of Mental Health, Jining Medical University, Jining, China.
- Department of Psychology, Affiliated Hospital of Jining Medical University, Jining, China.
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Qu Y, Wang P, Yao H, Wang D, Song C, Yang H, Zhang Z, Chen P, Kang X, Du K, Fan L, Zhou B, Han T, Yu C, Zhang X, Zuo N, Jiang T, Zhou Y, Liu B, Han Y, Lu J, Liu Y. Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease. Neurosci Bull 2023; 39:1533-1543. [PMID: 37014553 PMCID: PMC10533766 DOI: 10.1007/s12264-023-01041-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/29/2022] [Indexed: 04/05/2023] Open
Abstract
Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.
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Affiliation(s)
- Yida Qu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Hongxiang Yao
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Dawei Wang
- Department of Radiology, Department of Epidemiology and Health Statistics, School of Public Health, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Chengyuan Song
- Department of Neurology, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Hongwei Yang
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Zengqiang Zhang
- Branch of Chinese, PLA General Hospital, Sanya, 572022, China
| | - Pindong Chen
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaopeng Kang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kai Du
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, 300222, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuying Zhou
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Bing Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Lab of Cognition Neuroscience & Learning, Beijing Normal University, Beijing, 100091, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- Beijing Institute of Geriatrics, Beijing, 100053, China
- National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
| | - Yong Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
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Hu R, Tan F, Chen W, Wu Y, Jiang Y, Du W, Zuo Y, Gao B, Song Q, Miao Y. Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study. Front Psychiatry 2023; 14:1237113. [PMID: 37674550 PMCID: PMC10477457 DOI: 10.3389/fpsyt.2023.1237113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023] Open
Abstract
Objective To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function. Methods In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected. Results ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account. Conclusion The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.
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Affiliation(s)
- Rui Hu
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Fan Tan
- Department of Nuclear Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Wen Chen
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yong Wu
- Department of Paediatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yuhan Jiang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Wei Du
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yuchen Zuo
- Department of Paediatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Bingbing Gao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingwei Song
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yanwei Miao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
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Chen Q, Wang M, Wu GW, Li WH, Ren XD, Wang YL, Wei X, Wang JN, Yang Z, Li XH, Li ZJ, Tang LR, Zhang P, Wang Z. Characteristics of white matter alterations along fibres in patients with bulimia nervosa: A combined voxelwise and tractography study. Eur J Neurosci 2023; 58:2874-2887. [PMID: 37423618 DOI: 10.1111/ejn.16077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/16/2023] [Accepted: 06/12/2023] [Indexed: 07/11/2023]
Abstract
Accumulating evidence supports the hypothesis that white matter (WM) abnormalities are involved in the pathophysiology of bulimia nervosa (BN); however, findings from in vivo neuroimaging studies have been inconsistent. We aimed to investigate the possible brain WM alterations, including WM volume and microstructure, in patients with BN. We recruited 43 BN patients and 31 healthy controls (HCs). All participants underwent structural and diffusion tensor imaging. Differences in WM volume and microstructure were evaluated using voxel-based morphometry, tract-based spatial statistics, and automated fibre quantification analysis. Compared with HCs, BN patients showed significantly decreased fractional anisotropy in the middle part of the corpus callosum (nodes 31-32) and increased mean diffusivity in the right cranial nerve V (CN V) (nodes 27-33 and nodes 55-88) and vertical occipital fasciculus (VOF) (nodes 58-85). Moreover, we found decreased axial diffusivity in the right inferior fronto-occipital fasciculus (node 67) and increased radial diffusivity in the CN V (nodes 22-34 and nodes 52-89) and left VOF (nodes 60-66 and nodes 81-85). Meanwhile, WM microstructural changes were correlated with patients' clinical manifestations. We did not find any significant differences in WM volume and the main WM fibre bundle properties between BN patients and HCs. Taken together, these findings provide that BN shows significant brain WM reorganization, but primarily in microstructure (part of WM fibre bundle), which is not sufficient to cause changes in WM volume. The automated fibre quantification analysis could be more sensitive to detect the subtle pathological changes in a point or segment of the WM fibre bundle.
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Affiliation(s)
- Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Miao Wang
- Chinese Institute for Brain Research, Beijing, China
| | - Guo-Wei Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Wei-Hua Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xiao-Dan Ren
- Beijing Anding Hospital Capital Medical University, Beijing, China
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing, China
| | - Yi-Ling Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xuan Wei
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jia-Ni Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xiao-Hong Li
- Beijing Anding Hospital Capital Medical University, Beijing, China
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing, China
| | - Zhan-Jiang Li
- Beijing Anding Hospital Capital Medical University, Beijing, China
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing, China
| | - Li-Rong Tang
- Beijing Anding Hospital Capital Medical University, Beijing, China
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing, China
| | - Peng Zhang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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12
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Andica C, Kamagata K, Aoki S. Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging. Anat Sci Int 2023:10.1007/s12565-023-00715-9. [PMID: 37017902 DOI: 10.1007/s12565-023-00715-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/09/2023] [Indexed: 04/06/2023]
Abstract
White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.
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Affiliation(s)
- Christina Andica
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode, Urayasu, Chiba, 279-0013, Japan.
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shigeki Aoki
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode, Urayasu, Chiba, 279-0013, Japan
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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Maitre M, Jeltsch-David H, Okechukwu NG, Klein C, Patte-Mensah C, Mensah-Nyagan AG. Myelin in Alzheimer's disease: culprit or bystander? Acta Neuropathol Commun 2023; 11:56. [PMID: 37004127 PMCID: PMC10067200 DOI: 10.1186/s40478-023-01554-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder with neuronal and synaptic losses due to the accumulation of toxic amyloid β (Αβ) peptide oligomers, plaques, and tangles containing tau (tubulin-associated unit) protein. While familial AD is caused by specific mutations, the sporadic disease is more common and appears to result from a complex chronic brain neuroinflammation with mitochondriopathies, inducing free radicals' accumulation. In aged brain, mutations in DNA and several unfolded proteins participate in a chronic amyloidosis response with a toxic effect on myelin sheath and axons, leading to cognitive deficits and dementia. Αβ peptides are the most frequent form of toxic amyloid oligomers. Accumulations of misfolded proteins during several years alters different metabolic mechanisms, induce chronic inflammatory and immune responses with toxic consequences on neuronal cells. Myelin composition and architecture may appear to be an early target for the toxic activity of Aβ peptides and others hydrophobic misfolded proteins. In this work, we describe the possible role of early myelin alterations in the genesis of neuronal alterations and the onset of symptomatology. We propose that some pathophysiological and clinical forms of the disease may arise from structural and metabolic disorders in the processes of myelination/demyelination of brain regions where the accumulation of non-functional toxic proteins is important. In these forms, the primacy of the deleterious role of amyloid peptides would be a matter of questioning and the initiating role of neuropathology would be primarily the fact of dysmyelination.
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Affiliation(s)
- Michel Maitre
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France.
| | - Hélène Jeltsch-David
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
- Biotechnologie et signalisation cellulaire, UMR 7242 CNRS, Université de Strasbourg, 300 Boulevard Sébastien Brant CS 10413, Illkirch cedex, 67412, France
| | - Nwife Getrude Okechukwu
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Christian Klein
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Christine Patte-Mensah
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Ayikoe-Guy Mensah-Nyagan
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
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14
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Marcolini S, Rojczyk P, Seitz-Holland J, Koerte IK, Alosco ML, Bouix S. Posttraumatic Stress and Traumatic Brain Injury: Cognition, Behavior, and Neuroimaging Markers in Vietnam Veterans. J Alzheimers Dis 2023; 95:1427-1448. [PMID: 37694363 PMCID: PMC10578246 DOI: 10.3233/jad-221304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/24/2023] [Indexed: 09/12/2023]
Abstract
BACKGROUND Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are common in Veterans and linked to behavioral disturbances, increased risk of cognitive decline, and Alzheimer's disease. OBJECTIVE We studied the synergistic effects of PTSD and TBI on behavioral, cognitive, and neuroimaging measures in Vietnam war Veterans. METHODS Data were acquired at baseline and after about one-year from male Veterans categorized into: PTSD, TBI, PTSD+TBI, and Veteran controls without PTSD or TBI. We applied manual tractography to examine white matter microstructure of three fiber tracts: uncinate fasciculus (N = 91), cingulum (N = 87), and inferior longitudinal fasciculus (N = 95). ANCOVAs were used to compare Veterans' baseline behavioral and cognitive functioning (N = 285), white matter microstructure, amyloid-β (N = 230), and tau PET (N = 120). Additional ANCOVAs examined scores' differences from baseline to follow-up. RESULTS Veterans with PTSD and PTSD+TBI, but not Veterans with TBI only, exhibited poorer behavioral and cognitive functioning at baseline than controls. The groups did not differ in baseline white matter, amyloid-β, or tau, nor in behavioral and cognitive functioning, and tau accumulation change. Progression of white matter abnormalities of the uncinate fasciculus in Veterans with PTSD compared to controls was observed; analyses in TBI and PTSD+TBI were not run due to insufficient sample size. CONCLUSIONS PTSD and PTSD+TBI negatively affect behavioral and cognitive functioning, while TBI does not contribute independently. Whether progressive decline in uncinate fasciculus microstructure in Veterans with PTSD might account for cognitive decline should be further studied. Findings did not support an association between PTSD, TBI, and Alzheimer's disease pathology based on amyloid and tau PET.
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Affiliation(s)
- Sofia Marcolini
- Department of Neurology and Alzheimer Center, University Medical Center Groningen, Groningen, The Netherlands
| | - Philine Rojczyk
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, Germany
| | - Johanna Seitz-Holland
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Inga K. Koerte
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, Germany
| | - Michael L. Alosco
- Department of Neurology, Boston University Alzheimer’s Disease Research Center, Boston University CTE Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Software Engineering and Information Technology, École de Technologie Supe´rieure, Montre´al, Canada
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15
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Huang H, Ma X, Yue X, Kang S, Li Y, Rao Y, Feng Y, Wu J, Long W, Chen Y, Lyu W, Tan X, Qiu S. White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus. Clin Neuroradiol 2022; 33:327-341. [DOI: 10.1007/s00062-022-01213-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/06/2022] [Indexed: 11/03/2022]
Abstract
Abstract
Purpose
The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear.
Methods
In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis.
Results
TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients.
Conclusion
Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.
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16
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Yan Z, Wang X, Zhu Q, Shi Z, Chen X, Han Y, Zheng Q, Wei Y, Wang J, Li Y. Alterations in White Matter Fiber Tracts Characterized by Automated Fiber-Tract Quantification and Their Correlations With Cognitive Impairment in Neuromyelitis Optica Spectrum Disorder Patients. Front Neurosci 2022; 16:904309. [PMID: 35844220 PMCID: PMC9283762 DOI: 10.3389/fnins.2022.904309] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives To investigate whether patients with neuromyelitis optica spectrum disorder (NMOSD) have tract-specific alterations in the white matter (WM) and the correlations between the alterations and cognitive impairment. Materials and Methods In total, 40 patients with NMOSD and 20 healthy controls (HCs) who underwent diffusion tensor imaging (DTI) scan and neuropsychological scale assessments were enrolled. Automated fiber-tract quantification (AFQ) was applied to identify and quantify 100 equally spaced nodes of 18 specific WM fiber tracts for each participant. Then the group comparisons in DTI metrics and correlations between different DTI metrics and neuropsychological scales were performed. Results Regardless of the entire or pointwise level in WM fiber tracts, patients with NMOSD exhibited a decreased fractional anisotropy (FA) in the left inferior fronto-occipital fasciculus (L_IFOF) and widespread increased mean diffusion (MD), axial diffusivity (AD), and radial diffusivity (RD), especially for the thalamic radiation (TR), corticospinal tract (CST), IFOF, inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF) [p < 0.05, false discovery rate (FDR) correction], and the pointwise analyses performed more sensitive. Furthermore, the negative correlations among MD, AD, RD, and symbol digit modalities test (SDMT) scores in the left TR (L_TR) were found in NMOSD. Conclusion Patients with NMOSD exhibited the specific nodes of WM fiber tract damage, which can enhance our understanding of WM microstructural abnormalities in NMOSD. In addition, the altered DTI metrics were correlated with cognitive impairment, which can be used as imaging markers for the early identification of NMOSD cognitive impairment.
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Kim T, Aizenstein HJ, Snitz BE, Cheng Y, Chang YF, Roush RE, Huppert TJ, Cohen A, Doman J, Becker JT. Tract Specific White Matter Lesion Load Affects White Matter Microstructure and Their Relationships With Functional Connectivity and Cognitive Decline. Front Aging Neurosci 2022; 13:760663. [PMID: 35185514 PMCID: PMC8848259 DOI: 10.3389/fnagi.2021.760663] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/27/2021] [Indexed: 11/24/2022] Open
Abstract
White matter hyperintensities (WMHs) are associated with cognitive decline. Assessing the effect of WMH on WM microstructural changes and its relationships with structural and functional connectivity to multiple cognitive domains are helpful to better understand the pathophysiological processes of cognitive impairment. 65 participants (49 normal and 16 MCI subjects, age: 67.4 ± 8.3 years, 44 females) were studied at 3T. The WMHs and fifty fiber tracts were automatically segmented from the T1/T2-weighted images and diffusion-weighted images, respectively. Tract-profiles of WMH were compared with those of apparent fiber density (AFD). The relationship between AFD and tract connectivity (TC) was assessed. Functional connectivity (FC) between tract ends obtained from resting-state functional MRI was examined in relation to TC. Tract-specific relationships of WMH, TC and FC with a multi-domain neuropsychological test battery and Montreal Cognitive Assessment (MoCA) were also separately assessed by lasso linear regression. Indirect pathways of TC and FC between WMH and multiple cognitive measures were tested using the mediation analysis. Higher WMH loads in WM tracts were locally matched with the reduced AFD, which was related to decrease in TC. However, no direct relationship was found between TC and FC. Tract-specific changes on WMH, TC and FC for each cognitive performance may explain that macro- and microstructural and functional changes are associated differently with each cognitive domain in a fiber specific manner. In these identified tracts, the differences between normal and MCI for WMH and TC were increased, and the relationships of WMH, TC and FC with cognitive outcomes were more significant, compared to the results from all tracts. Indirect pathways of two-step (TC-FC) between WMH and all cognitive domains were significant (p < 0.0083 with Bonferroni correction), while the separated indirect pathways through TC and through FC were different depending on cognitive domain. Deterioration in specific cognitive domains may be affected by alterations in a set of different tracts that are differently associated with macrostructural, microstructural, and function changes. Thus, assessments of WMH and its associated changes on specific tracts help for better understanding of the interrelationships of multiple changes in cognitive impairment.
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Affiliation(s)
- Tae Kim
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Tae Kim,
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yu Cheng
- Departments of Statistics and Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yue-Fang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rebecca E. Roush
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Theodore J. Huppert
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Deparement of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Annie Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jack Doman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - James T. Becker
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
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Muncy NM, Kimbler A, Hedges-Muncy AM, McMakin DL, Mattfeld AT. General additive models address statistical issues in diffusion MRI: An example with clinically anxious adolescents. Neuroimage Clin 2022; 33:102937. [PMID: 35033812 PMCID: PMC8762458 DOI: 10.1016/j.nicl.2022.102937] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 12/10/2021] [Accepted: 01/03/2022] [Indexed: 11/29/2022]
Abstract
Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.
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Affiliation(s)
- Nathan M Muncy
- Center for Children and Families, Florida International University, Miami, Florida, USA.
| | - Adam Kimbler
- Center for Children and Families, Florida International University, Miami, Florida, USA
| | | | - Dana L McMakin
- Center for Children and Families, Florida International University, Miami, Florida, USA
| | - Aaron T Mattfeld
- Center for Children and Families, Florida International University, Miami, Florida, USA
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Xu F, Jin C, Zuo T, Wang R, Yang Y, Wang K. Segmental abnormalities of superior longitudinal fasciculus microstructure in patients with schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder: An automated fiber quantification tractography study. Front Psychiatry 2022; 13:999384. [PMID: 36561639 PMCID: PMC9766353 DOI: 10.3389/fpsyt.2022.999384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Superior longitudinal fasciculus (SLF) is a white matter (WM) tract that connects the frontal, parietal and temporal lobes. SLF integrity has been widely assessed in neuroimaging studies of psychiatric disorders, such as schizophrenia (SZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). However, prior studies have revealed inconsistent findings and comparisons across disorders have not been fully examined. METHODS Here, we obtained data for 113 patients (38 patients with SZ, 40 with BD, 35 with ADHD) and 94 healthy controls from the UCLA Consortium for Neuropsychiatric Phenomic LA5c dataset. We assessed the integrity of 20 major WM tracts with a novel segmentation method by automating fiber tract quantification (AFQ). The AFQ divides each tract into 100 equal parts along the direction of travel, with fractional anisotropy (FA) of each part taken as a characteristic. Differences in FA among the four groups were examined. RESULTS Compared to healthy controls, patients with SZ showed significantly lower FA in the second half (51-100 parts) of the SLF. No differences were found between BD and healthy controls, nor between ADHD and healthy controls. Results also demonstrated that patients with SZ showed FA reduction in the second half of the SLF relative to patients with BP. Moreover, greater FA in patients in SLF was positively correlated with the manic-hostility score of the Brief Psychiatry Rating scale. DISCUSSION These findings indicated that differences in focal changes in SLF might be a key neurobiological abnormality contributing to characterization of these psychiatric disorders.
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Affiliation(s)
- Feiyu Xu
- School of Mental Health, Jining Medical University, Jining, China.,Shandong Mental Health Center, Shandong University, Jinan, China
| | - Chengliang Jin
- School of Mental Health, Jining Medical University, Jining, China.,Shandong Mental Health Center, Shandong University, Jinan, China
| | - Tiantian Zuo
- Shandong Mental Health Center, Shandong University, Jinan, China.,Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ruzhan Wang
- Shandong Mental Health Center, Shandong University, Jinan, China
| | - Ying Yang
- Shandong Mental Health Center, Shandong University, Jinan, China.,Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Kangcheng Wang
- School of Psychology, Shandong Normal University, Jinan, China
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20
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Kritikos M, Huang C, Clouston SAP, Pellecchia AC, Mejia-Santiago S, Carr MA, Hagan T, Kotov R, Gandy S, Sano M, Horton M, Bromet EJ, Lucchini RG, Luft BJ. DTI Connectometry Analysis Reveals White Matter Changes in Cognitively Impaired World Trade Center Responders at Midlife. J Alzheimers Dis 2022; 89:1075-1089. [PMID: 35964183 PMCID: PMC9730899 DOI: 10.3233/jad-220255] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND More than 8% of responders who participated in the search and rescue efforts at the World Trade Center (WTC) following 9/11 developed early-onset cognitive impairment (CI). Approximately 23% were also diagnosed with chronic post-traumatic stress disorder (PTSD). OBJECTIVE To shed light on the pathophysiology of these WTC-related conditions, we examined diffusion connectometry to identify altered white matter tracts in WTC responders with CI and/or PTSD compared to unaffected responders. METHODS 99 WTC responders (mean age 56 years) consisting of CI-/PTSD- (n = 27), CI+/PTSD- (n = 25), CI-/PTSD+ (n = 24), and CI+/PTSD+ (n = 23) were matched on age, sex, occupation, race, and education. Cognitive status was determined using the Montreal Cognitive Assessment and PTSD status was determined using the DSM-IV SCID. Diffusion tensor imaging was acquired on a 3T Siemens Biograph mMR scanner. Connectometry analysis was used to examine whole-brain tract-level differences in white matter integrity as reflected by fractional anisotropy (FA) values after adjusting for confounders. RESULTS Analyses identified that FA was negatively correlated with CI and PTSD status in the fornix, cingulum, forceps minor of the corpus callosum and the right uncinate fasciculus. Furthermore, FA was negatively correlated with PTSD status, regardless of CI status in the superior thalamic radiation and the cerebellum. CONCLUSION This is the first connectometry study to examine altered white matter tracts in a sample of WTC responders with CI and/or PTSD. Results from this study suggest that WTC responders with early-onset CI may be experiencing an early neurodegenerative process characterized by decreased FA in white matter tracts.
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Affiliation(s)
- Minos Kritikos
- Program in Public Health and Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Chuan Huang
- Department of Radiology, Renaissance School of Medicine at Stony Brook, Stony Brook, NY
| | - Sean A. P. Clouston
- Program in Public Health and Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Alison C. Pellecchia
- Stony Brook World Trade Center Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Stephanie Mejia-Santiago
- Stony Brook World Trade Center Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Melissa A. Carr
- Stony Brook World Trade Center Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Thomas Hagan
- Department of Radiology, Renaissance School of Medicine at Stony Brook, Stony Brook, NY
| | - Roman Kotov
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Sam Gandy
- James J Peters VA Medical Center, 130 West Kingsbridge Road, Bronx NY, 10468
- Department of Psychiatry and Mount Sinai Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Cognitive Health and Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mary Sano
- Department of Psychiatry and Mount Sinai Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Cognitive Health and Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Megan Horton
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinair, New York, NY, USA
| | - Evelyn J. Bromet
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Roberto G. Lucchini
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinair, New York, NY, USA
| | - Benjamin J. Luft
- Stony Brook World Trade Center Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
- Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
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21
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Li R, Sun H, Hao H, Liu Y, Zhang Y, Zhang T, Wang G, Ming W. White matter integrity in patients with classic trigeminal neuralgia: a multi-node automated fiber tract quantification study. J Int Med Res 2021; 49:3000605211047071. [PMID: 34719991 PMCID: PMC8562620 DOI: 10.1177/03000605211047071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE To study the characteristics of point-by-point destruction of white matter tracts in patients using automated fiber tract quantification (AFQ). METHODS Thirty-four classic trigeminal neuralgia (CTN) patients and 34 healthy control (HC) subjects underwent 3.0 T diffusion tensor magnetic resonance imaging and T1-weighted imaging. The fractional anisotropy (FA) and mean diffusivity (MD) of 100 nodes of 20 fiber tracts were analyzed by AFQ, and the correlations of the FA and MD with the visual analogue scale (VAS) pain score were assessed. RESULTS The FA values of the left thalamic radiation (middle segment), left corticospinal tract, callosum forceps minor, and right uncinate fasciculus were significantly lower in CTN patients than in the HC group. The MD of the left thalamic tract (middle segment), left corticospinal tract, right superior longitudinal fasciculus, and left superior longitudinal fasciculus (anterior segment) were significantly higher in the CTN group. Additionally, the VAS pain score in CTN patients was positively correlated with FA and negatively correlated with MD. CONCLUSION Specific fiber tract nodes were damaged in CTN patients, which was related to the VAS pain score. Multi-node quantitative studies of fiber tract damage are valuable for understanding the white matter tract damage pattern in CTN patients.
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Affiliation(s)
- Rui Li
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P.R. China.,Department of Radiology, Jining No. 1 People's Hospital, Jining, Shandong, P.R. China
| | - Hongfang Sun
- Department of Radiology, Pingyi County Hospital of Traditional Chinese Medicine, Linyi, Shandong, P.R. China
| | - Hongjuan Hao
- Department of Pediatrics, Jining Social Welfare Centre, Jining, Shandong, P.R. China
| | - Yali Liu
- Department of Radiology, Jining No. 1 People's Hospital, Jining, Shandong, P.R. China
| | - Yang Zhang
- Department of Neurosurgery, Jining No. 1 People's Hospital, Jining, Shandong, P.R. China
| | - Tianran Zhang
- Department of Clinical Medicine, Jining Medical College, Jining, Shandong, P.R. China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P.R. China.,Department of Radiology, Shandong Provincial Hospital Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China *These authors contributed equally to this work
| | - Wang Ming
- Department of Radiology, Jining No. 1 People's Hospital, Jining, Shandong, P.R. China
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22
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Qu Y, Wang P, Liu B, Kang X, Chen P, Du K, Liu Y. Altered Connection and Diagnosis Utility of White Matter in Alzheimer's Disease: A Multi-site Automated Fiber Quantification Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:2923-2927. [PMID: 34891857 DOI: 10.1109/embc46164.2021.9630117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Alzheimer's disease (AD) is a typical neurodegenerative disease that is associated with cognitive decline, memory loss, and functional disconnection. Diffusion tensor imaging (DTI) has been widely used to investigate the integrity and degeneration of white matter in AD. In this study, with one of the world's largest DTI biobanks (865 individuals), we aim to explore the diagnosis utility and stability of tractbased features (extracted by automated fiber quantification (AFQ) pipeline) in AD. First, we studied the clinical association of tract-based features by detecting AD-associated alterations of diffusion properties along fiber bundles. Then, a binary classification experiment between AD and normal controls was performed using tract-based diffusion properties as features and support vector machine (SVM) as a classifier with an independent site cross-validation strategy. The average accuracy of 77.90% (the highest was 88.89%) showed that white matter properties as biomarkers had a relatively stable role in the clinical diagnosis of AD.Clinical Relevance- White matter characteristics are valid and robust biomarkers of AD, which have high accuracy and generalizability in the AD diagnosis in a large multi-site dataset.
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23
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Zhang H, Li H, Yin L, Chen Z, Wu B, Huang X, Jia Z, Gong Q. Aberrant White Matter Microstructure in Depressed Patients with Suicidality. J Magn Reson Imaging 2021; 55:1141-1150. [PMID: 34549480 DOI: 10.1002/jmri.27927] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Depression is a common psychiatric disorder affecting 264 million people globally, and the worst outcome is suicide. While regional brain alterations in depressed suicidal brain have previously been reported, knowledge about white matter (WM) microstructure is limited. PURPOSE Automated fiber quantification (AFQ) acquired by magnetic resonance imaging was used to calculate diffusion properties of fiber tracks to explore the structural alteration of WM associated with suicidality in depressive patients. STUDY TYPE Cross-sectional. SUBJECTS Forty-five depressive patients without suicidality (DS- group, 60.00% females), 53 depressed patients with suicidality (DS+ group, 66.04% females), and 59 healthy controls (HC group, 67.80% females). FIELD STRENGTH/SEQUENCE 3.0 T; single-shot echo-planar imaging sequence. ASSESSMENT The point-wise group difference of the fiber tracts was determined by diffusion properties including fractional anisotropy, mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of 18 specific WM tracts. STATISTICAL TESTS Analysis of covariance (ANCOVA) and partial correlation analysis were used. A threshold of P < 0.05 was considered statistically significant. RESULTS The significantly different diffusion properties were found in callosum forceps, left inferior fronto-occipital fasciculus (IFOF), right anterior thalamic radiation (ATR), and left cingulum cingulate in DS- and DS+ groups. The correlation analysis results showed that MD of right ATR was significantly positively correlated with Hamilton Depression Rating Scale (HAMD) scores (r = 0.363). In addition, AD of right ATR (r = 0.372), MD of callosum forceps minor (r = 0.511), RD of left IFOF (r = 0.429), and RD of callosum forceps minor (r = 0.515) were significantly positively correlated with suicide item scores of HAMD. DATA CONCLUSION Our demonstration of decreased WM tract integrity including callosum forceps, IFOF, and ATR confirms the central involvement of the frontal cortex and limbic system with suicidality in depression. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Huawei Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Huiru Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Li Yin
- Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Ziqi Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Baolin Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Zhiyun Jia
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan University, Chengdu, China
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24
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He F, Zhang Y, Wu X, Li Y, Zhao J, Fang P, Fan L, Li C, Liu T, Wang J. Early Microstructure Changes of White Matter Fiber Bundles in Patients with Amnestic Mild Cognitive Impairment Predicts Progression of Mild Cognitive Impairment to Alzheimer's Disease. J Alzheimers Dis 2021; 84:179-192. [PMID: 34487042 DOI: 10.3233/jad-210495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Amnestic mild cognitive impairment (aMCI) is the transitional stage between normal aging and Alzheimer's disease (AD). Some aMCI patients will progress into AD eventually, whereas others will not. If the trajectory of aMCI can be predicted, it would enable early diagnosis and early therapy of AD. OBJECTIVE To explore the development trajectory of aMCI patients, we used diffusion tensor imaging to analyze the white matter microstructure changes of patients with different trajectories of aMCI. METHODS We included three groups of subjects:1) aMCI patients who convert to AD (MCI-P); 2) aMCI patients who remain in MCI status (MCI-S); 3) normal controls (NC). We analyzed the fractional anisotropy and mean diffusion rate of brain regions, and we adopted logistic binomial regression model to predicate the development trajectory of aMCI. RESULTS The fraction anisotropy value is significantly reduced, the mean diffusivity value is significantly increased in the two aMCI patient groups, and the MCI-P patients presented greater changes. Significant changes are mainly located in the cingulum, fornix, hippocampus, and uncinate fasciculus. These changed brain regions significantly correlated with the patient's Mini-Mental State Examination scores. CONCLUSION The study predicted the disease trajectory of different types of aMCI patients based on the characteristic values of the above-mentioned brain regions. The prediction accuracy rate can reach 90.2%, and the microstructure characteristics of the right cingulate band and the right hippocampus may have potential clinical application value to predict the disease trajectory.
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Affiliation(s)
- Fangmei He
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Yuchen Zhang
- Department of Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Jie Zhao
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Peng Fang
- Department of Military Medical Psychology, Air Force Medical University, Xi'an, Shaanxi, P.R. China
| | - Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Chenxi Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P.R. China.,National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China.,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, P.R. China
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25
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Bi XA, Li L, Xu R, Xing Z. Pathogenic Factors Identification of Brain Imaging and Gene in Late Mild Cognitive Impairment. Interdiscip Sci 2021; 13:511-520. [PMID: 34106420 DOI: 10.1007/s12539-021-00449-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 06/01/2021] [Accepted: 06/04/2021] [Indexed: 11/28/2022]
Abstract
Mild cognitive impairment (MCI) is a dangerous signal of severe cognitive decline. It can be separated into two steps: early MCI (EMCI) and late MCI (LMCI). As the post-state of MCI and pre-state of Alzheimer's disease (AD), LMCI receives insufficient attention in the field of brain science, causing the internal mechanism of LMCI has not been well understood. To better explore the focus and pathological mechanism of LMCI, a method called genetic evolved random forest (GERF) is applied. Resting functional magnetic resonance imaging (rfMRI) and gene data are obtained from 62 subjects (36 LMCI and 26 normal controls), and Pearson correlation analysis is adopted to perform the multimodal fusion of two types of data to construct fusion features. We identified pathogenic brain regions and genes that are highly related to LMCI using GERF and achieves a good effect. Compared with the normal control (NC) group, the abnormal brain regions of LMCI are PUT.L, PreCG.L, IFGtriang.R, REC.R, DCG.R, PoCG.L, and HES.L, and the pathogenic genes are FHIT, RF00019, FRMD4A, PTPRD, and RBFOX1. More importantly, most of these risk genes and abnormal brain regions have been confirmed to be related to AD and MCI in previous studies. In this study, we mapped them to LMCI with higher accuracies, so as to provide a more robust understanding of the physiological mechanism of MCI.
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Affiliation(s)
- Xia-An Bi
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China. .,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China.
| | - Lou Li
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Ruihui Xu
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Zhaoxu Xing
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
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26
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Pichet Binette A, Theaud G, Rheault F, Roy M, Collins DL, Levin J, Mori H, Lee JH, Farlow MR, Schofield P, Chhatwal JP, Masters CL, Benzinger T, Morris J, Bateman R, Breitner JC, Poirier J, Gonneaud J, Descoteaux M, Villeneuve S. Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease. eLife 2021; 10:62929. [PMID: 33983116 PMCID: PMC8169107 DOI: 10.7554/elife.62929] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 05/12/2021] [Indexed: 12/12/2022] Open
Abstract
Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.
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Affiliation(s)
- Alexa Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - François Rheault
- Electrical Engineering, Vanderbilt University, Nashville, United States
| | - Maggie Roy
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Osaka, Japan
| | - Jae Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | | | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, UNSW Sydney, Sydney, Australia
| | - Jasmeer P Chhatwal
- Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Tammie Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - Randall Bateman
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Cs Breitner
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Judes Poirier
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Julie Gonneaud
- Douglas Mental Health University Institute, Montreal, Canada.,Normandie Univ, UNICAEN, INSERM, U1237, Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Sylvia Villeneuve
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
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27
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Shekari E, Goudarzi S, Shahriari E, Joghataei MT. Extreme capsule is a bottleneck for ventral pathway. IBRO Neurosci Rep 2021; 10:42-50. [PMID: 33861816 PMCID: PMC8019950 DOI: 10.1016/j.ibneur.2020.11.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 11/30/2020] [Indexed: 11/25/2022] Open
Abstract
As neuroscience literature suggests, extreme capsule is considered a whiter matter tract. Nevertheless, it is not clear whether extreme capsule itself is an association fiber pathway or only a bottleneck for other association fibers to pass. Via our review, investigating anatomical position, connectivity and cognitive role of the bundles in extreme capsule, and by analyzing data from the dissection, it can be argued that extreme capsule is probably a bottleneck for the passage of uncinated fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF), and these fasciculi are responsible for the respective roles in language processing.
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Affiliation(s)
- Ehsan Shekari
- Department of Advanced Technologies in Medicine, Iran University of Medical Science, Tehran, Iran
| | - Sepideh Goudarzi
- Department of pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Elahe Shahriari
- Department of Physiology, Faculty of Medicine, Iran University of Medical Science, Tehran, Iran
| | - Mohammad Taghi Joghataei
- Department of Advanced Technologies in Medicine, Iran University of Medical Science, Tehran, Iran
- Corresponding author.
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28
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van Hespen KM, Zwanenburg JJM, Dankbaar JW, Geerlings MI, Hendrikse J, Kuijf HJ. An anomaly detection approach to identify chronic brain infarcts on MRI. Sci Rep 2021; 11:7714. [PMID: 33833297 PMCID: PMC8032662 DOI: 10.1038/s41598-021-87013-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 03/23/2021] [Indexed: 02/05/2023] Open
Abstract
The performance of current machine learning methods to detect heterogeneous pathology is limited by the quantity and quality of pathology in medical images. A possible solution is anomaly detection; an approach that can detect all abnormalities by learning how 'normal' tissue looks like. In this work, we propose an anomaly detection method using a neural network architecture for the detection of chronic brain infarcts on brain MR images. The neural network was trained to learn the visual appearance of normal appearing brains of 697 patients. We evaluated its performance on the detection of chronic brain infarcts in 225 patients, which were previously labeled. Our proposed method detected 374 chronic brain infarcts (68% of the total amount of brain infarcts) which represented 97.5% of the total infarct volume. Additionally, 26 new brain infarcts were identified that were originally missed by the radiologist during radiological reading. Our proposed method also detected white matter hyperintensities, anomalous calcifications, and imaging artefacts. This work shows that anomaly detection is a powerful approach for the detection of multiple brain abnormalities, and can potentially be used to improve the radiological workflow efficiency by guiding radiologists to brain anomalies which otherwise remain unnoticed.
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Affiliation(s)
- Kees M van Hespen
- Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, Postbox 85500, 3584 CX, Utrecht, The Netherlands.
| | - Jaco J M Zwanenburg
- Department of Radiology, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Jan W Dankbaar
- Department of Radiology, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Mirjam I Geerlings
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Department of Radiology, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
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29
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Qu Y, Wang P, Liu B, Song C, Wang D, Yang H, Zhang Z, Chen P, Kang X, Du K, Yao H, Zhou B, Han T, Zuo N, Han Y, Lu J, Yu C, Zhang X, Jiang T, Zhou Y, Liu Y. AI4AD: Artificial intelligence analysis for Alzheimer's disease classification based on a multisite DTI database. BRAIN DISORDERS 2021. [DOI: 10.1016/j.dscb.2021.100005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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30
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Wang S, Rao J, Yue Y, Xue C, Hu G, Qi W, Ma W, Ge H, Zhang F, Zhang X, Chen J. Altered Frequency-Dependent Brain Activation and White Matter Integrity Associated With Cognition in Characterizing Preclinical Alzheimer's Disease Stages. Front Hum Neurosci 2021; 15:625232. [PMID: 33664660 PMCID: PMC7921321 DOI: 10.3389/fnhum.2021.625232] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 01/06/2021] [Indexed: 01/21/2023] Open
Abstract
Background Subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI) are regarded to be at high risk of converting to Alzheimer's disease (AD). Amplitude of low-frequency fluctuations (ALFF) can reflect functional deterioration while diffusion tensor imaging (DTI) is capable of detecting white matter integrity. Our study aimed to investigate the structural and functional alterations to further reveal convergence and divergence among SCD, naMCI, and aMCI and how these contribute to cognitive deterioration. Methods We analyzed ALFF under slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands and white matter fiber integrity among normal controls (CN), SCD, naMCI, and aMCI groups. Correlation analyses were further utilized among paired DTI alteration, ALFF deterioration, and cognitive decline. Results For ALFF calculation, ascended ALFF values were detected in the lingual gyrus (LING) and superior frontal gyrus (SFG) within SCD and naMCI patients, respectively. Descended ALFF values were presented mainly in the LING, SFG, middle frontal gyrus, and precuneus in aMCI patients compared to CN, SCD, and naMCI groups. For DTI analyses, white matter alterations were detected within the uncinate fasciculus (UF) in aMCI patients and within the superior longitudinal fasciculus (SLF) in naMCI patients. SCD patients presented alterations in both fasciculi. Correlation analyses revealed that the majority of these structural and functional alterations were associated with complicated cognitive decline. Besides, UF alterations were correlated with ALFF deterioration in the SFG within aMCI patients. Conclusions SCD shares structurally and functionally deteriorative characteristics with aMCI and naMCI, and tends to convert to either of them. Furthermore, abnormalities in white matter fibers may be the structural basis of abnormal brain activation in preclinical AD stages. Combined together, it suggests that structural and functional integration may characterize the preclinical AD progression.
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Affiliation(s)
- Siyu Wang
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China.,Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Jiang Rao
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China.,Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yingying Yue
- Department of Psychosomatics and Psychiatry, The Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chen Xue
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China.,Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Guanjie Hu
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Wenzhang Qi
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China.,Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenying Ma
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Honglin Ge
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Fuquan Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiangrong Zhang
- Fourth Clinical College of Nanjing Medical University, Nanjing, China.,Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China.,Fourth Clinical College of Nanjing Medical University, Nanjing, China
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31
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Wang Y, Wang X, Shi H, Xia L, Dong J, Nguchu BA, Uwisengeyimana JDD, Liu Y, Zhang D, Feng L, Qiu B. Microstructural properties of major white matter tracts in constant exotropia before and after strabismus surgery. Br J Ophthalmol 2021; 106:870-877. [PMID: 33468491 DOI: 10.1136/bjophthalmol-2020-317948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 12/08/2020] [Accepted: 01/04/2021] [Indexed: 11/04/2022]
Abstract
AIMS The purpose of this study was to explore the microstructural properties of the major white matter (WM) tracts in constant exotropia (XT) before and after strabismus surgery, and further investigate the association between microstructural alterations and the ocular dominance (OD). METHODS We collected diffusion tensor imaging data of patients with XT before (n=19) and after (n=15) strabismus surgery and 20 healthy controls and evaluated OD and stereopsis. The probabilistic streamline tractography of the 24 major WM tracts was reconstructed by using the automated fibre quantification package. Fractional anisotropy and mean diffusivity (MD) along each tract were estimated, and their differences between the groups were examined. Furthermore, we evaluated the relationship between OD and the absolute value of altered microstructural parameters. RESULTS While all postoperative XT patients restored normal stereopsis, most of their OD remained aberrant (9 out of 11). Compared with that of preoperation, the MD of postoperative patients decreased significantly along left anterior thalamic radiation (ATR), left arcuate fasciculus (AF), left corticospinal tract (CST), left cingulum cingulate (CGC) and left inferior fronto-occipital fasciculus. Moreover, OD was negatively correlated with the absolute value of MD changes in left ATR, left AF, left CST and left CGC. CONCLUSION Microstructural alterations after surgery in the visuospatial network tracts may contribute to the stereopsis restoration. Additionally, the results of the correlation analysis may signify that the balanced binocular input may be more conducive for the restoration and improvement of binocular visual function, including stereopsis. Thus, restoring normal ocular balance after surgical correction may be necessary to achieve more substantial improvements.
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Affiliation(s)
- Yanming Wang
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Xiaoxiao Wang
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Hongmei Shi
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.,Department of Ophthalmology, The People's Hospital of Bozhou, Bozhou, Anhui, China
| | - Lin Xia
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jiong Dong
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Benedictor Alexander Nguchu
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Jean De Dieu Uwisengeyimana
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Yanpeng Liu
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Du Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
| | - Lixia Feng
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Bensheng Qiu
- Hefei National Laboratory for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, China
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32
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Huang L, Chen X, Sun W, Chen H, Ye Q, Yang D, Li M, Luo C, Ma J, Shao P, Xu H, Zhang B, Zhu X, Xu Y. Early Segmental White Matter Fascicle Microstructural Damage Predicts the Corresponding Cognitive Domain Impairment in Cerebral Small Vessel Disease Patients by Automated Fiber Quantification. Front Aging Neurosci 2021; 12:598242. [PMID: 33505302 PMCID: PMC7829360 DOI: 10.3389/fnagi.2020.598242] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 12/07/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: To characterize earlier damage pattern of white matter (WM) microstructure in cerebral small vessel disease (CSVD) and its relationship with cognitive domain dysfunction. Methods: A total of 144 CSVD patients and 100 healthy controls who underwent neuropsychological measurements and diffusion tensor imaging (DTI) examination were recruited. Cognitive function, emotion, and gait were assessed in each participant. The automated fiber quantification (AFQ) technique was used to extract different fiber properties between groups, and partial correlation and general linear regression analyses were performed to assess the relationship between position-specific WM microstructure and cognitive function. Results: Specific segments in the association fibers, commissural WM regions of interest (ROIs), and projection fibers were damaged in the CSVD group [P < 0.05, family-wise error (FWE) correction], and these damaged segments showed interhemispheric symmetry. In addition, the damage to specific tract profiles [including the posteromedial component of the right cingulum cingulate (CC), the occipital lobe portion of the callosum forceps major, the posterior portion of the left superior longitudinal fasciculus (SLF), and the bilateral anterior thalamic radiation (ATR)] was related to the dysfunction in specific cognitive domains. Among these tracts, we found the ATR to be the key set of tracts whose profiles were most associated with cognitive dysfunction. The left ATR was a specific fiber bundle associated with episode memory and language function, whereas the fractional anisotropy (FA) values of the intermediate component of the right ATR were negatively correlated with executive function and gait evaluation. It should be noted that the abovementioned relationships could not survive the Bonferroni correction (p < 0.05/27), so we chose more liberal uncorrected statistical thresholds. Conclusions: Damage to the WM fiber bundles showed extensive interhemispheric symmetry and was limited to particular segments in CSVD patients. Disruption of strategically located fibers was associated with different cognitive deficits, especially the bilateral ATR.
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Affiliation(s)
- Lili Huang
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Xin Chen
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Wenshan Sun
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Qing Ye
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Dan Yang
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Junyi Ma
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Hengheng Xu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Xiaolei Zhu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neurological Medical Center, Nanjing, China
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Rosas HD, Hsu E, Mercaldo ND, Lai F, Pulsifer M, Keator D, Brickman AM, Price J, Yassa M, Hom C, Krinsky‐McHale SJ, Silverman W, Lott I, Schupf N. Alzheimer-related altered white matter microstructural integrity in Down syndrome: A model for sporadic AD? ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12040. [PMID: 33204811 PMCID: PMC7648416 DOI: 10.1002/dad2.12040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 02/14/2020] [Accepted: 02/19/2020] [Indexed: 11/08/2022]
Abstract
INTRODUCTION Virtually all adults with Down syndrome (DS) develop Alzheimer's disease (AD)-associated neuropathology by the age of 40, with risk for dementia increasing from the early 50s. White matter (WM) pathology has been reported in sporadic AD, including early demyelination, microglial activation, loss of oligodendrocytes and reactive astrocytes but has not been extensively studied in the at-risk DS population. METHODS Fifty-six adults with DS (35 cognitively stable adults, 11 with mild cognitive impairment, 10 with dementia) underwent diffusion-weighted magnetic resonance imaging (MRI), amyloid imaging, and had assessments of cognition and functional abilities using tasks appropriate for persons with intellectual disability. RESULTS Early changes in late-myelinating and relative sparing of early-myelinating pathways, consistent with the retrogenesis model proposed for sporadic AD, were associated with AD-related cognitive deficits and with regional amyloid deposition. DISCUSSION Our findings suggest that quantification of WM changes in DS could provide a promising and clinically relevant biomarker for AD clinical onset and progression.
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Affiliation(s)
- H. Diana Rosas
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyAthinoula Martinos CenterMassachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Eugene Hsu
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyAthinoula Martinos CenterMassachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Nathaniel D. Mercaldo
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Florence Lai
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Margaret Pulsifer
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - David Keator
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Adam M. Brickman
- G. H. Sergievsky Center and Taub Institute for Research on Alzheimer's Disease and the Aging BrainCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
- Department of NeurologyCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Julie Price
- Department of RadiologyAthinoula Martinos CenterMassachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Michael Yassa
- Department of Neurobiology and BehaviorUniversity of CaliforniaCalifornia, USAIrvine
| | - Christy Hom
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | | | - Wayne Silverman
- Kennedy Krieger InstituteJohns Hopkins University School of Medicine, BaltimoreMarylandUSA
- Department of PediatricsIrvine Medical CenterUniversity of CaliforniaIrvineCaliforniaUSA
| | - Ira Lott
- Department of PediatricsIrvine Medical CenterUniversity of CaliforniaIrvineCaliforniaUSA
| | - Nicole Schupf
- G. H. Sergievsky Center and Taub Institute for Research on Alzheimer's Disease and the Aging BrainCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
- Department of NeurologyCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
- Department of EpidemiologyMailman School of Public HealthColumbia UniversityNew YorkNew YorkUSA
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Yang FPG, Bal SS, Lee JF, Chen CC. White Matter Differences in Networks in Elders with Mild Cognitive Impairment and Alzheimer's Disease. Brain Connect 2020; 11:180-188. [PMID: 32731749 DOI: 10.1089/brain.2020.0767] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Alzheimer's disease (AD) is associated with impairment of large-scale brain networks, disruption in structural connections, and functional disconnection between distant brain regions. Although decreased functional connectivity has been thoroughly investigated and reported by existing functional neuroimaging literature, this study investigated network-based differences due to the structural changes in white matter pathways in AD patients. We hypothesize that diffusion metrics of disrupted tracts that go through cognitive networks related with intrinsic awareness, motor movement, and executive control can be utilized as biomarkers to distinguish prodromal stage from AD stage. Methods: Diffusion MRI data of a total 154 subjects, including patients with clinical AD (n = 47) and patients with mild cognitive impairment (MCI) (n = 107) was used. To study structural changes associated with white matter fiber pathways voxel-averaged diffusion metrics and fiber density metrics were calculated. Results: Study revealed that AD patients exhibit disruptions in intrahemispheric tracts and projection fiber tracts as suggested by diffusion indices. Our whole brain analysis revealed that network differences within default mode network (DMN), sensory motor network, and frontoparietal networks are associated with disruption in inferior fronto-occipital fasciculus (IFOF), corticospinal tract, and superior longitudinal fasciculus. Global function revealed by Mini Mental State Examination correlate with those fiber pathways that form reciprocal connections within networks associated with motor movement and executive control. Conclusion: Diffusion metrics appear to be more sensitive than fiber density metrics in differentiating the structural changes in the white matter. Decreased fractional anisotropy along with increased mean diffusivity and radial diffusivity in forceps minor, corticospinal tract, and IFOF as an imaging biomarker would be ideal to distinguish AD patients from MCI patients. Difference of DMN, sensory motor network, and frontal parietal network in our study reveals that AD patients may suffer from poor motor movement and degraded executive control.
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Affiliation(s)
- Fan Pei Gloria Yang
- Center for Cognition and Mind Sciences, National Tsing Hua University, Hsinchu, Taiwan
| | - Sukhdeep Singh Bal
- Department of Mathematical Sciences Liverpool, University of Liverpool, Merseyside, United Kingdom.,International Intercollegiate PhD Programme, National Tsing Hua University, Hsinchu, Taiwan
| | - Jia-Fu Lee
- Department of Psychiatry, Taipei Tzu Chi Hospital, Taipei, Taiwan
| | - Chia-Chi Chen
- Department of Early Childhood Care and Education, Kang Ning Junior College of Nursing, Taipei, Taiwan
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Gozdas E, Fingerhut H, Chromik LC, O'Hara R, Reiss AL, Hosseini SMH. Focal white matter disruptions along the cingulum tract explain cognitive decline in amnestic mild cognitive impairment (aMCI). Sci Rep 2020; 10:10213. [PMID: 32576866 PMCID: PMC7311416 DOI: 10.1038/s41598-020-66796-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 05/27/2020] [Indexed: 12/11/2022] Open
Abstract
White matter abnormalities of the human brain are implicated in typical aging and neurodegenerative diseases. However, our understanding of how fine-grained changes in microstructural properties along white matter tracts are associated with memory and cognitive decline in normal aging and mild cognitive impairment remains elusive. We quantified tract profiles with a newer method that can reliably measure fine-grained changes in white matter properties along the tracts using advanced multi-shell diffusion magnetic resonance imaging in 25 patients with amnestic mild cognitive impairment (aMCI) and 23 matched healthy controls (HC). While the changes in tract profiles were parallel across aMCI and HC, we found a significant focal shift in the profile at specific locations along major tracts sub-serving memory in aMCI. Particularly, our findings depict white matter alterations at specific locations on the right cingulum cingulate, the right cingulum hippocampus and anterior corpus callosum (CC) in aMCI compared to HC. Notably, focal changes in white matter tract properties along the cingulum tract predicted memory and cognitive functioning in aMCI. The results suggest that white matter disruptions at specific locations of the cingulum bundle may be a hallmark for the early prediction of Alzheimer’s disease and a predictor of cognitive decline in aMCI.
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Affiliation(s)
- Elveda Gozdas
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Hannah Fingerhut
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Lindsay C Chromik
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Ruth O'Hara
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Allan L Reiss
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - S M Hadi Hosseini
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
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Chen HF, Huang LL, Li HY, Qian Y, Yang D, Qing Z, Luo CM, Li MC, Zhang B, Xu Y. Microstructural disruption of the right inferior fronto-occipital and inferior longitudinal fasciculus contributes to WMH-related cognitive impairment. CNS Neurosci Ther 2020; 26:576-588. [PMID: 31901155 PMCID: PMC7163793 DOI: 10.1111/cns.13283] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 12/07/2019] [Accepted: 12/12/2019] [Indexed: 01/03/2023] Open
Abstract
Aims White matter hyperintensity (WMH) is the most common neuroimaging manifestation of cerebral small vessel disease and is related to cognitive dysfunction or dementia. This study aimed to investigate the mechanism and effective indicators to predict WMH‐related cognitive impairment. Methods We recruited 22 healthy controls (HC), 25 cases of WMH with normal cognition (WMH‐NC), and 23 cases of WMH with mild cognitive impairment (WMH‐MCI). All individuals underwent diffusion tensor imaging (DTI) and a standardized neuropsychological assessment. Automated Fiber Quantification was used to extract altered DTI metrics between groups, and partial correlation was performed to assess the associations between WM integrity and cognitive performance. Furthermore, machine learning analyses were performed to determine underlying imaging markers of WMH‐related cognitive impairment. Results Our study found that mean diffusivity (MD) values of several fiber bundles including the bilateral anterior thalamic radiation (ATR), the left inferior fronto‐occipital fasciculus (IFOF), the right inferior longitudinal fasciculus (ILF), and the right superior longitudinal fasciculus (SLF) were negatively correlated with memory function, while that of the anterior component of the right IFOF and the posterior and intermediate component of the right ILF showed significant negative correlation with MMSE and episodic memory, respectively. Furthermore, machine learning analyses showed that the accuracy of recognizing WMH‐MCI patients from the WMH populations was up to 80.5% and the intermediate and posterior components of the right ILF and the anterior component of the right IFOF contribute the most. Conclusions Changes in the properties of DTI may be the potential mechanism of WMH‐related MCI, especially the right IFOF and the right ILF, which may become imaging markers for predicting WMH‐related cognitive dysfunction.
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Affiliation(s)
- Hai-Feng Chen
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Li-Li Huang
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Hui-Ya Li
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Yi Qian
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Dan Yang
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Zhao Qing
- Department of Radiology, Afliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Cai-Mei Luo
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Meng-Chun Li
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Afliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yun Xu
- Department of Neurology, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Drum Tower Hospital, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Clinic Medical Center for Neurology, Nanjing, China
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Reas ET, Hagler DJ, Kuperman JM, Wierenga CE, Galasko D, White NS, Dale AM, Banks SJ, McEvoy LK, Brewer JB. Associations Between Microstructure, Amyloid, and Cognition in Amnestic Mild Cognitive Impairment and Dementia. J Alzheimers Dis 2020; 73:347-357. [PMID: 31796676 PMCID: PMC7266036 DOI: 10.3233/jad-190871] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Although amyloid-β (Aβ) and microstructural brain changes are both effective biomarkers of Alzheimer's disease, their independent or synergistic effects on cognitive decline are unclear. OBJECTIVE To examine associations of Aβ and brain microstructure with cognitive decline in amnestic mild cognitive impairment and dementia. METHODS Restriction spectrum imaging, cerebrospinal fluid Aβ, and longitudinal cognitive data were collected on 23 healthy controls and 13 individuals with mild cognitive impairment or mild to moderate Alzheimer's disease. Neurite density (ND) and isotropic free water diffusion (IF) were computed in fiber tracts and cortical regions of interest. We examined associations of Aβ with regional and whole-brain microstructure, and assessed whether microstructure mediates effects of Aβ on cognitive decline. RESULTS Lower ND in limbic and association fibers and higher medial temporal lobe IF predicted baseline impairment and longitudinal decline across multiple cognitive domains. ND and IF predicted cognitive outcomes after adjustment for Aβ or whole-brain microstructure. Correlations between microstructure and cognition were present for both amyloid-positive and amyloid-negative individuals. Aβ correlated with whole-brain, rather than regional, ND and IF. CONCLUSION Aβ correlates with widespread microstructural brain changes, whereas regional microstructure correlates with cognitive decline. Microstructural abnormalities predict cognitive decline regardless of amyloid, and may inform about neural injury leading to cognitive decline beyond that attributable to amyloid.
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Affiliation(s)
- Emilie T. Reas
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Donald J. Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Joshua M. Kuperman
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Christina E. Wierenga
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Veterans Affairs, San Diego Healthcare system, La Jolla, CA, USA
| | - Douglas Galasko
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Nathan S. White
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Anders M. Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Sarah J. Banks
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Linda K. McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
| | - James B. Brewer
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
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