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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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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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Murdy TJ, Dunn AR, Singh S, Telpoukhovskaia MA, Zhang S, White JK, Kahn I, Febo M, Kaczorowski CC. Leveraging genetic diversity in mice to inform individual differences in brain microstructure and memory. Front Behav Neurosci 2023; 16:1033975. [PMID: 36703722 PMCID: PMC9871587 DOI: 10.3389/fnbeh.2022.1033975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 12/08/2022] [Indexed: 01/11/2023] Open
Abstract
In human Alzheimer's disease (AD) patients and AD mouse models, both differential pre-disease brain features and differential disease-associated memory decline are observed, suggesting that certain neurological features may protect against AD-related cognitive decline. The combination of these features is known as brain reserve, and understanding the genetic underpinnings of brain reserve may advance AD treatment in genetically diverse human populations. One potential source of brain reserve is brain microstructure, which is genetically influenced and can be measured with diffusion MRI (dMRI). To investigate variation of dMRI metrics in pre-disease-onset, genetically diverse AD mouse models, we utilized a population of genetically distinct AD mice produced by crossing the 5XFAD transgenic mouse model of AD to 3 inbred strains (C57BL/6J, DBA/2J, FVB/NJ) and two wild-derived strains (CAST/EiJ, WSB/EiJ). At 3 months of age, these mice underwent diffusion magnetic resonance imaging (dMRI) to probe neural microanatomy in 83 regions of interest (ROIs). At 5 months of age, these mice underwent contextual fear conditioning (CFC). Strain had a significant effect on dMRI measures in most ROIs tested, while far fewer effects of sex, sex*strain interactions, or strain*sex*5XFAD genotype interactions were observed. A main effect of 5XFAD genotype was observed in only 1 ROI, suggesting that the 5XFAD transgene does not strongly disrupt neural development or microstructure of mice in early adulthood. Strain also explained the most variance in mouse baseline motor activity and long-term fear memory. Additionally, significant effects of sex and strain*sex interaction were observed on baseline motor activity, and significant strain*sex and sex*5XFAD genotype interactions were observed on long-term memory. We are the first to study the genetic influences of brain microanatomy in genetically diverse AD mice. Thus, we demonstrated that strain is the primary factor influencing brain microstructure in young adult AD mice and that neural development and early adult microstructure are not strongly altered by the 5XFAD transgene. We also demonstrated that strain, sex, and 5XFAD genotype interact to influence memory in genetically diverse adult mice. Our results support the usefulness of the 5XFAD mouse model and convey strong relationships between natural genetic variation, brain microstructure, and memory.
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Affiliation(s)
| | - Amy R. Dunn
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Surjeet Singh
- The Jackson Laboratory, Bar Harbor, ME, United States
| | | | | | | | - Itamar Kahn
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Marcelo Febo
- Department of Neuroscience, University of Florida College of Medicine, Gainesville, FL, United States
| | - Catherine C. Kaczorowski
- The Jackson Laboratory, Bar Harbor, ME, United States,*Correspondence: Catherine C. Kaczorowski,
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Granger SJ, Colon-Perez L, Larson MS, Phelan M, Keator DB, Janecek JT, Sathishkumar MT, Smith AP, McMillan L, Greenia D, Corrada MM, Kawas CH, Yassa MA. Hippocampal dentate gyrus integrity revealed with ultrahigh resolution diffusion imaging predicts memory performance in older adults. Hippocampus 2022; 32:627-638. [PMID: 35838075 PMCID: PMC10510739 DOI: 10.1002/hipo.23456] [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: 07/08/2021] [Revised: 05/26/2022] [Accepted: 06/30/2022] [Indexed: 11/08/2022]
Abstract
Medial temporal lobe (MTL) atrophy is a core feature of age-related cognitive decline and Alzheimer's disease (AD). While regional volumes and thickness are often used as a proxy for neurodegeneration, they lack the sensitivity to serve as an accurate diagnostic test and indicate advanced neurodegeneration. Here, we used a submillimeter resolution diffusion weighted MRI sequence (ZOOMit) to quantify microstructural properties of hippocampal subfields in older adults (63-98 years old) using tensor derived measures: fractional anisotropy (FA) and mean diffusivity (MD). We demonstrate that the high-resolution sequence, and not a standard resolution sequence, identifies dissociable profiles for CA1, dentate gyrus (DG), and the collateral sulcus. Using ZOOMit, we show that advanced age is associated with increased MD of the CA1 and DG as well as decreased FA of the DG. Increased MD of the DG, reflecting decreased cellular density, mediated the relationship between age and word list recall. Further, increased MD in the DG, but not DG volume, was linked to worse spatial pattern separation. Our results demonstrate that ultrahigh-resolution diffusion imaging enables the detection of microstructural differences in hippocampal subfield integrity and will lead to novel insights into the mechanisms of age-related memory loss.
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Affiliation(s)
- Steven J. Granger
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Luis Colon-Perez
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Myra Saraí Larson
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Michael Phelan
- UC Institute for Memory Impairments and Neurological Disorders, University of California, Irvine 92697
| | - David B. Keator
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA 92697
| | - John T. Janecek
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Mithra T. Sathishkumar
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Anna P. Smith
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Liv McMillan
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
| | - Dana Greenia
- Department of Neurology, University of California, Irvine 92697
| | | | - Claudia H. Kawas
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
- Department of Neurology, University of California, Irvine 92697
| | - Michael A. Yassa
- Center for the Neurobiology of Learning and Memory, University of California, Irvine 92697
- Department of Neurobiology and Behavior, University of California, Irvine 92697
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA 92697
- Department of Neurology, University of California, Irvine 92697
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Ni R. Magnetic Resonance Imaging in Animal Models of Alzheimer's Disease Amyloidosis. Int J Mol Sci 2021; 22:12768. [PMID: 34884573 PMCID: PMC8657987 DOI: 10.3390/ijms222312768] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 11/18/2021] [Accepted: 11/23/2021] [Indexed: 02/07/2023] Open
Abstract
Amyloid-beta (Aβ) plays an important role in the pathogenesis of Alzheimer's disease. Aberrant Aβ accumulation induces neuroinflammation, cerebrovascular alterations, and synaptic deficits, leading to cognitive impairment. Animal models recapitulating the Aβ pathology, such as transgenic, knock-in mouse and rat models, have facilitated the understanding of disease mechanisms and the development of therapeutics targeting Aβ. There is a rapid advance in high-field MRI in small animals. Versatile high-field magnetic resonance imaging (MRI) sequences, such as diffusion tensor imaging, arterial spin labeling, resting-state functional MRI, anatomical MRI, and MR spectroscopy, as well as contrast agents, have been developed for preclinical imaging in animal models. These tools have enabled high-resolution in vivo structural, functional, and molecular readouts with a whole-brain field of view. MRI has been used to visualize non-invasively the Aβ deposits, synaptic deficits, regional brain atrophy, impairment in white matter integrity, functional connectivity, and cerebrovascular and glymphatic system in animal models of Alzheimer's disease amyloidosis. Many of the readouts are translational toward clinical MRI applications in patients with Alzheimer's disease. In this review, we summarize the recent advances in MRI for visualizing the pathophysiology in amyloidosis animal models. We discuss the outstanding challenges in brain imaging using MRI in small animals and propose future outlook in visualizing Aβ-related alterations in the brains of animal models.
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Affiliation(s)
- Ruiqing Ni
- Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland;
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
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Müller HP, Roselli F, Rasche V, Kassubek J. Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases. Front Neurosci 2020; 14:734. [PMID: 32982659 PMCID: PMC7487414 DOI: 10.3389/fnins.2020.00734] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/22/2020] [Indexed: 12/11/2022] Open
Abstract
The understanding of human and non-human microstructural brain alterations in the course of neurodegenerative diseases has substantially improved by the non-invasive magnetic resonance imaging (MRI) technique of diffusion tensor imaging (DTI). Animal models (including disease or knockout models) allow for a variety of experimental manipulations, which are not applicable to humans. Thus, the DTI approach provides a promising tool for cross-species cross-sectional and longitudinal investigations of the neurobiological targets and mechanisms of neurodegeneration. This overview with a systematic review focuses on the principles of DTI analysis as used in studies at the group level in living preclinical models of neurodegeneration. The translational aspect from in-vivo animal models toward (clinical) applications in humans is covered as well as the DTI-based research of the non-human brains' microstructure, the methodological aspects in data processing and analysis, and data interpretation at different abstraction levels. The aim of integrating DTI in multiparametric or multimodal imaging protocols will allow the interrogation of DTI data in terms of directional flow of information and may identify the microstructural underpinnings of neurodegeneration-related patterns.
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Affiliation(s)
| | - Francesco Roselli
- Department of Neurology, University of Ulm, Ulm, Germany.,German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Volker Rasche
- Core Facility Small Animal MRI, University of Ulm, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
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Xue Y, Zhang Z, Wen C, Liu H, Wang S, Li J, Zhuge Q, Chen W, Ye Q. Characterization of Alzheimer's Disease Using Ultra-high b-values Apparent Diffusion Coefficient and Diffusion Kurtosis Imaging. Aging Dis 2019; 10:1026-1036. [PMID: 31595200 PMCID: PMC6764724 DOI: 10.14336/ad.2018.1129] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 11/29/2018] [Indexed: 12/13/2022] Open
Abstract
The aim of the study is to investigate the diffusion characteristics of Alzheimer’s disease (AD) patients using an ultra-high b-values apparent diffusion coefficient (ADC_uh) and diffusion kurtosis imaging (DKI). A total of 31 AD patients and 20 healthy controls (HC) who underwent both MRI examination and clinical assessment were included in this study. Diffusion weighted imaging (DWI) was acquired with 14 b-values in the range of 0 and 5000 s/mm2. Diffusivity was analyzed in selected regions, including the amygdala (AMY), hippocampus (HIP), thalamus (THA), caudate (CAU), globus pallidus (GPA), lateral ventricles (LVe), white matter (WM) of the frontal lobe (FL), WM of the temporal lobe (TL), WM of the parietal lobe (PL) and centrum semiovale (CS). The mean, median, skewness and kurtosis of the conventional apparent diffusion coefficient (ADC), DKI (including two variables, Dapp and Kapp) and ADC_uh values were calculated for these selected regions. Compared to the HC group, the ADC values of AD group were significantly higher in the right HIP and right PL (WM), while the ADC_uh values of the AD group increased significantly in the WM of the bilateral TL and right CS. In the AD group, the Kapp values in the bilateral LVe, bilateral PL/left TL (WM) and right CS were lower than those in the HC group, while the Dapp value of the right PL (WM) increased. The ADC_uh value of the right TL was negatively correlated with MMSE (mean, r=-0.420, p=0.019). The ADC value and Dapp value have the same regions correlated with MMSE. Compared with the ADC_uh, combining ADC_uh and ADC parameters will result in a higher AUC (0.894, 95%CI=0.803-0.984, p=0.022). Comparing to ADC or DKI, ADC_uh has no significant difference in the detectability of AD, but ADC_uh can better reflect characteristic alternation in unconventional brain regions of AD patients.
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Affiliation(s)
- Yingnan Xue
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhenhua Zhang
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Caiyun Wen
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Huiru Liu
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Suyuan Wang
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiance Li
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qichuan Zhuge
- 2Zhejiang Provincial Key Laboratory of Aging and Neurological Disorder Research, Department of Neurosurgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Weijian Chen
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qiong Ye
- 1Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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White matter lesions, cerebral inflammation and cognitive function in a mouse model of cerebral hypoperfusion. Brain Res 2019; 1711:193-201. [DOI: 10.1016/j.brainres.2019.01.017] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 01/11/2019] [Accepted: 01/12/2019] [Indexed: 01/05/2023]
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