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Jiaxuan Peng, Zheng G, Hu M, Zhang Z, Yuan Z, Xu Y, Shao Y, Zhang Y, Sun X, Han L, Gu X, Zhenyu Shu. White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer's disease. BMC Geriatr 2024; 24:691. [PMID: 39160467 PMCID: PMC11331623 DOI: 10.1186/s12877-024-05293-7] [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: 06/23/2023] [Accepted: 08/08/2024] [Indexed: 08/21/2024] Open
Abstract
OBJECTIVE To identify white matter fiber injury and network changes that may lead to mild cognitive impairment (MCI) progression, then a joint model was constructed based on neuropsychological scales to predict high-risk individuals for Alzheimer's disease (AD) progression among older adults with MCI. METHODS A total of 173 MCI patients were included from the Alzheimer's Disease Neuroimaging Initiative(ADNI) database and randomly divided into training and testing cohorts. Forty-five progressed to AD during a 4-year follow-up period. Diffusion tensor imaging (DTI) techniques extracted relevant DTI quantitative features for each patient. In addition, brain networks were constructed based on white matter fiber bundles to extract network property features. Ensemble dimensionality reduction was applied to reduce both DTI quantitative features and network features from the training cohort, and machine learning algorithms were added to construct white matter signature. In addition, 52 patients from the National Alzheimer's Coordinating Center (NACC) database were used for external validation of white matter signature. A joint model was subsequently generated by combining with scale scores, and its performance was evaluated using data from the testing cohort. RESULTS Based on multivariate logistic regression, clinical dementia rating and Alzheimer's disease assessment scales (CDRS and ADAS, respectively) were selected as independent predictive factors. A joint model was constructed in combination with the white matter signature. The AUC, sensitivity, and specificity in the training cohort were 0.938, 0.937, and 0.91, respectively, and the AUC, sensitivity, and specificity in the test cohort were 0.905, 0.923, and 0.872, respectively. The Delong test showed a statistically significant difference between the joint model and CDRS or ADAS scores (P < 0.05), yet no significant difference between the joint model and the white matter signature (P = 0.341). CONCLUSION The present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.
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Affiliation(s)
- Jiaxuan Peng
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Guangying Zheng
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Mengmeng Hu
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Zihan Zhang
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Zhongyu Yuan
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Yuyun Xu
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Yuan Shao
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Yang Zhang
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Xiaojun Sun
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Lu Han
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
- Jinzhou Medical University, Jinzhou, Liaoning Province, China
| | - Xiaokai Gu
- Zhejiang University of Technology, Zhejiang Province, Hangzhou, China
| | - Zhenyu Shu
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
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Bougea A, Gourzis P. Biomarker-Based Precision Therapy for Alzheimer's Disease: Multidimensional Evidence Leading a New Breakthrough in Personalized Medicine. J Clin Med 2024; 13:4661. [PMID: 39200803 PMCID: PMC11355840 DOI: 10.3390/jcm13164661] [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: 06/22/2024] [Revised: 07/25/2024] [Accepted: 08/05/2024] [Indexed: 09/02/2024] Open
Abstract
(1) Background: Alzheimer's disease (AD) is a worldwide neurodegenerative disorder characterized by the buildup of abnormal proteins in the central nervous system and cognitive decline. Since no radical therapy exists, only symptomatic treatments alleviate symptoms temporarily. In this review, we will explore the latest advancements in precision medicine and biomarkers for AD, including their potential to revolutionize the way we diagnose and treat this devastating condition. (2) Methods: A literature search was performed combining the following Medical Subject Heading (MeSH) terms on PubMed: "Alzheimer's disease", "biomarkers", "APOE", "APP", "GWAS", "cerebrospinal fluid", "polygenic risk score", "Aβ42", "τP-181", " p-tau217", "ptau231", "proteomics", "total tau protein", and "precision medicine" using Boolean operators. (3) Results: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with AD risk, while a transcriptomic analysis has revealed dysregulated gene expression patterns in the brains of individuals with AD. The proteomic and metabolomic profiling of biological fluids, such as blood, urine, and CSF, and neuroimaging biomarkers have also yielded potential biomarkers of AD that could be used for the early diagnosis and monitoring of disease progression. (4) Conclusion: By leveraging a combination of the above biomarkers, novel ultrasensitive immunoassays, mass spectrometry methods, and metabolomics, researchers are making significant strides towards personalized healthcare for individuals with AD.
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Affiliation(s)
- Anastasia Bougea
- 1st Department of Neurology, National and Kapodistrian University of Athens, 15772 Athens, Greece
| | - Philippos Gourzis
- 1st Department of Psychiatry, University of Patras, 26504 Rio, Greece;
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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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Sun X, Zhao C, Chen SY, Chang Y, Han YL, Li K, Sun HM, Wang ZF, Liang Y, Jia JJ. Free Water MR Imaging of White Matter Microstructural Changes is a Sensitive Marker of Amyloid Positivity in Alzheimer's Disease. J Magn Reson Imaging 2023. [PMID: 38100518 DOI: 10.1002/jmri.29189] [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: 04/13/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Extracellular free water (FW) resulting from white matter degeneration limits the sensitivity of diffusion tensor imaging (DTI) in predicting Alzheimer's disease (AD). PURPOSE To evaluate the sensitivity of FW-DTI in detecting white matter microstructural changes in AD. To validate the effectiveness of FW-DTI indices to predict amyloid-beta (Aβ) positivity in mild cognitive impairment (MCI) subtypes. STUDY TYPE Retrospective. POPULATION Thirty-eight Aβ-negative cognitively healthy (CH) controls (68.74 ± 8.28 years old, 55% female), 15 Aβ-negative MCI patients (MCI-n) (68.87 ± 8.83 years old, 60% female), 29 Aβ-positive MCI patients (MCI-p) (73.03 ± 7.05 years old, 52% female), and 29 Aβ-positive AD patients (72.93 ± 9.11 years old, 55% female). FIELD STRENGTH/SEQUENCE 3.0T; DTI, T1 -weighted, T2 -weighted, T2 star-weighted angiography, and Aβ PET (18 F-florbetaben or 11 C-PIB). ASSESSMENT FW-corrected and standard diffusion indices were analyzed using trace-based spatial statistics. Area under the curve (AUC) in distinguishing MCI subtypes were compared using support vector machine (SVM). STATISTICAL TESTS Chi-squared test, one-way analysis of covariance, general linear regression analyses, nonparametric permutation tests, partial Pearson's correlation, receiver operating characteristic curve analysis, and linear SVM. A P value <0.05 was considered statistically significant. RESULTS Compared with CH/MCI-n/MCI-p, AD showed significant change in tissue compartment indices of FW-DTI. No difference was found in the FW index among pair-wise group comparisons (the minimum FWE-corrected P = 0.114). There was a significant association between FW-DTI indices and memory and visuospatial function. The SVM classifier with tissue radial diffusivity as an input feature had the best classification performance of MCI subtypes (AUC = 0.91), and the classifying accuracy of FW-DTI was all over 89.89%. DATA CONCLUSION FW-DTI indices prove to be potential biomarkers of AD. The classification of MCI subtypes based on SVM and FW-DTI indices has good accuracy and could help early diagnosis. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Xuan Sun
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Cui Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Si-Yu Chen
- Medical School of Chinese PLA, Beijing, China
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yan Chang
- Department of Nuclear Medicine, The First Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Yu-Liang Han
- Department of Neurology, The 305 Hospital of PLA, Beijing, China
| | - Ke Li
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Hong-Mei Sun
- Medical School of Chinese PLA, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
| | - Zhen-Fu Wang
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ying Liang
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Jian-Jun Jia
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
- Institute of Geriatrics, Chinese PLA General Hospital, Beijing, China
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Sui H, Yang J, Xiang H, Yan C. Combining ADC values in DWI with rCBF values in arterial spin labeling (ASL) for the diagnosis of mild cognitive impairment (MCI). Medicine (Baltimore) 2023; 102:e34979. [PMID: 37713879 PMCID: PMC10508430 DOI: 10.1097/md.0000000000034979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 08/07/2023] [Indexed: 09/17/2023] Open
Abstract
We aimed to investigate the role of combined apparent diffusion coefficient (ADC) values and relative cerebral blood flow (rCBF) values in the diagnosis of mild cognitive impairment (MCI) patients. The present prospective research enrolled 156 MCI patients and 58 healthy elderly people who came to our hospital from January 2021 to February 2023. T1W, T2W, diffusion-weighted imaging, and arterial spin labeling sequences were performed on all subjects, and ADC values and rCBF values were measured at the workstation. Clinical and demographic data of all patients were collected while mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scores were used to assess patients' cognitive abilities. The MCI group had significantly lower rCBF values in the left frontal lobe, left occipital lobe, right frontal lobe, and right occipital lobe than the HC group. The ADC values in the left frontal lobe as well as the right frontal lobe were remarkably elevated in the MCI group than in the HC group. MoCA and MMSE scores were positively correlated with rCBF values in the left frontal, right frontal, left occipital, and right occipital lobes and negatively correlated with ADC values in the left and right frontal lobes. Combined ADC values and rCBF values from the left frontal lobe for the diagnosis of MCI had a higher sensitivity and specificity with the AUC was 0.877, sensitivity 81.0%, specificity 82.7%. Additionally, pressure fasting plasma glucose, ADC of the left frontal lobe, right frontal lobe, rCBF of left frontal lobe and rCBF of left frontal lobe were the risk factors of patients with MCI. In summary, our results indicated that the ADC values and rCBF values were changed in MCI group compared to HC group and correlated with MMSE and MoCA scores.
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Affiliation(s)
- Haijing Sui
- Department of Radiology, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Juan Yang
- Department of Neurology, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Honggang Xiang
- Department of Surgery, Shanghai Pudong New Area People’s Hospital, Shanghai, China
| | - Chenggong Yan
- Department of Radiology, Shanghai Pudong New Area Hospital of Traditional Chinese Medicine, Shanghai, China
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Wang A, Wei T, Wu H, Yang Y, Ding Y, Wang Y, Zhang C, Yang W. Lesions in White Matter in Wilson's Disease and Correlation with Clinical Characteristics. Can J Neurol Sci 2023; 50:710-718. [PMID: 35959686 DOI: 10.1017/cjn.2022.286] [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] [Indexed: 11/06/2022]
Abstract
BACKGROUND Neuroimaging studies in Wilson's disease (WD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these alterations are localized to specific regions of fiber tracts, and what diagnostic value they might have. The purpose of this study is to explore the spatial profile of WM abnormalities along defined fiber tracts in WD and its clinical relevance. METHODS Ninety-nine patients with WD (62 men and 37 women) and 91 age- and sex-matched controls (59 men and 32 women) were recruited to take part in experiments of diffusion-weighted imaging with 64 gradient vectors. The data were calculated by FMRIB Software Library (FSL) software and Automated Fiber Quantification (AFQ) software. After registration, patient groups and normal groups were compared by Mann-Whitney U test analysis. RESULTS Compared with the controls, the patients with WD showed widespread fractional anisotropy reduction and mean diffusivity, radial diffusivity elevation of identified fiber tracts. Significant correlations between diffusion tensor imaging (DTI) parameters and the neurological Unified Wilson's Disease Rating Scale (UWDRS-N), serum ceruloplasmin, and 24-h urinary copper excretion were found. CONCLUSIONS The present study has provided evidence that the metrics of DTI could be utilized as a potential biomarker of neuropathological symptoms in WD. Damage to the microstructure of callosum forceps and corticospinal tract may be involved in the pathophysiological process of neurological symptoms in WD patients, such as gait and balance disturbances, involuntary movements, dysphagia, and autonomic dysfunction.
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Affiliation(s)
- Anqin Wang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Taohua Wei
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Hongli Wu
- Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Yulong Yang
- Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Yufeng Ding
- Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Yi Wang
- Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Chuanfeng Zhang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
| | - Wenming Yang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230601, China
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Johnson GA, Tian Y, Ashbrook DG, Cofer GP, Cook JJ, Gee JC, Hall A, Hornburg K, Qi Y, Yeh FC, Wang N, White LE, Williams RW. Merged magnetic resonance and light sheet microscopy of the whole mouse brain. Proc Natl Acad Sci U S A 2023; 120:e2218617120. [PMID: 37068254 PMCID: PMC10151475 DOI: 10.1073/pnas.2218617120] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/10/2023] [Indexed: 04/19/2023] Open
Abstract
We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 μm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 μm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 μm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.
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Affiliation(s)
| | - Yuqi Tian
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - David G. Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN38162
| | - Gary P. Cofer
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - James J. Cook
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - James C. Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA19104
| | - Adam Hall
- LifeCanvas Technology, Cambridge, MA02141
| | | | - Yi Qi
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - Fang-Cheng Yeh
- Department of Neurologic Surgery, University of Pittsburgh, Pittsburgh, PA15260
| | - Nian Wang
- Department of Radiology, Indiana University, Bloomington, IN47401
| | | | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN38162
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Chen Y, Wang Y, Song Z, Fan Y, Gao T, Tang X. Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review. Ageing Res Rev 2023; 87:101911. [PMID: 36931328 DOI: 10.1016/j.arr.2023.101911] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/01/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023]
Abstract
Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.
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Affiliation(s)
- Yu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yifei Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zeyu Song
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianxin Gao
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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Marin-Marin L, Miró-Padilla A, Costumero V. Structural But Not Functional Connectivity Differences within Default Mode Network Indicate Conversion to Dementia. J Alzheimers Dis 2023; 91:1483-1494. [PMID: 36641666 DOI: 10.3233/jad-220603] [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: 01/15/2023]
Abstract
BACKGROUND Malfunctioning of the default mode network (DMN) has been consistently related to mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, evidence on differences in this network between MCI converters (MCI-c) and non-converters (MCI-nc), which could mark progression to AD, is still inconsistent. OBJECTIVE To multimodally investigate the DMN in the AD continuum. METHODS We measured gray matter (GM) volume, white matter (WM) integrity, and functional connectivity (FC) at rest in healthy elderly controls, MCI-c, MCI-nc, and AD patients, matched on sociodemographic variables. RESULTS Significant differences between AD patients and controls were found in the structure of most of the regions of the DMN. MCI-c only differed from MCI-nc in GM volume of the left parahippocampus and bilateral hippocampi and middle frontal gyri, as well as in WM integrity of the parahippocampal cingulum connecting the left hippocampus and precuneus. We found significant correlations between integrity in some of those regions and global neuropsychological status, as well as an excellent discrimination ability between converters and non-converters for the sum of GM volume of left parahippocampus, bilateral hippocampi, and middle frontal gyri, and WM integrity of left parahippocampal cingulum. However, we found no significant differences in FC. CONCLUSION These results further support the relationship between abnormalities in the DMN and AD, and suggest that structural measures could be more accurate than resting-state estimates as markers of conversion from MCI to AD.
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Affiliation(s)
- Lidón Marin-Marin
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - Anna Miró-Padilla
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - Víctor Costumero
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
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Magalhães TNC, Casseb RF, Gerbelli CLB, Pimentel-Siva LR, Nogueira MH, Teixeira CVL, Carletti AFMK, de Rezende TJR, Joaquim HPG, Talib LL, Forlenza OV, Cendes F, Balthazar MLF. Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease. Brain Behav 2023; 13:e2863. [PMID: 36601694 PMCID: PMC9927845 DOI: 10.1002/brb3.2863] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/02/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ42 ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ42 alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ42 , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.
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Affiliation(s)
- Thamires Naela Cardoso Magalhães
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Raphael Fernandes Casseb
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Seaman Family MR Research Center, University of Calgary, Calgary, Canada
| | - Christian Luiz Baptista Gerbelli
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Luciana Ramalho Pimentel-Siva
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Mateus Henrique Nogueira
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Camila Vieira Ligo Teixeira
- Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil.,National Institute on Aging, National Institute of Health, Baltimore, Maryland, USA
| | - Ana Flávia Mac Knight Carletti
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Thiago Junqueira Ribeiro de Rezende
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | | | - Leda Leme Talib
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo (USP), São Paulo, Brazil
| | - Orestes Vicente Forlenza
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo (USP), São Paulo, Brazil
| | - Fernando Cendes
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Marcio Luiz Figueredo Balthazar
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
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11
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Lee LH, Wu SC, Ho CF, Liang WL, Liu YC, Chou CJ. White matter hyperintensities in cholinergic pathways may predict poorer responsiveness to acetylcholinesterase inhibitor treatment for Alzheimer's disease. PLoS One 2023; 18:e0283790. [PMID: 37000849 PMCID: PMC10065432 DOI: 10.1371/journal.pone.0283790] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 03/19/2023] [Indexed: 04/03/2023] Open
Abstract
BACKGROUND Acetylcholinesterase inhibitor (AChEI) drug regimens are the mainstay treatment options for patients with Alzheimer's disease (AD). Herein, We examined the association between clinical response to AChEI and white matter hyperintensities on magnetic resonance imaging (MRI) scan at baseline. METHODS Between 2020 and 2021, we recruited 101 individuals with a clinical diagnosis of probable AD. Each participant underwent complete neuropsychological testing and 3T (Telsa) brain magnetic resonance imaging. Responsiveness to AChEI, as assessed after 12 months, was designated as less than two points of regression in Mini-Mental State Examination scores (MMSE) and stable clinical dementia rating scale. We also evaluated MRI images by examining scores on the Cholinergic Pathways Hyperintensities Scale (CHIPS), Fazekas scale, and medial temporal atrophy (MTA) scale. RESULTS In our cohort, 52 patients (51.4%) were classified as responders. We observed significantly higher CHIPS scores in the nonresponder group (21.1 ± 12.9 vs. 14.9 ± 9.2, P = 0.007). Age at baseline, education level, sex, Clinical Dementia Rating sum of boxes scores, and three neuroimaging parameters were tested in regression models. Only CHIPS scores predicted clinical response to AChEI treatment. CONCLUSION WMHs in the cholinergic pathways, not diffuse white matter lesions or hippocampal atrophy, correlated with poorer responsiveness to AChEI treatment. Therefore, further investigation into the role of the cholinergic pathway in AD is warranted.
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Affiliation(s)
- Li-Hua Lee
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taipei, Taiwan
| | - Shu-Ching Wu
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taipei, Taiwan
| | - Cheng-Feng Ho
- Department of Radiology, Cardinal Tien Hospital, New Taipei City, Taipei, Taiwan
| | - Wan-Lin Liang
- Department of Medical Research, Far Eastern Hospital, New Taipei City, Taipei, Taiwan
| | - Yi-Chien Liu
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taipei, Taiwan
- Department of Education and Research, Medical school of Fu-Jen University, New Taipei City, Taipei, Taiwan
- Geriatric Behavioral Neurology Project, Tohoku University New Industry Hatchery Center (NICHe), Sendai, Japan
- * E-mail:
| | - Chia-Ju Chou
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taipei, Taiwan
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12
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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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13
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Maharjan S, Tsai AP, Lin PB, Ingraham C, Jewett MR, Landreth GE, Oblak AL, Wang N. Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging. Front Neurosci 2022; 16:964654. [PMID: 36061588 PMCID: PMC9428354 DOI: 10.3389/fnins.2022.964654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 07/18/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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Affiliation(s)
- Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Peter B. Lin
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Cynthia Ingraham
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Megan R. Jewett
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- Department of Anatomy, Cell Biology and Physiology, Indiana University, Indianapolis, IN, United States
| | - Adrian L. Oblak
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- *Correspondence: Nian Wang,
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14
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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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15
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Disrupted Value-Directed Strategic Processing in Individuals with Mild Cognitive Impairment: Behavioral and Neural Correlates. Geriatrics (Basel) 2022; 7:geriatrics7030056. [PMID: 35645279 PMCID: PMC9149834 DOI: 10.3390/geriatrics7030056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/09/2022] [Accepted: 05/09/2022] [Indexed: 02/05/2023] Open
Abstract
Value-directed strategic processing involves attending to higher-value information while inhibiting lower-value information. This preferential processing is relatively preserved in cognitively normal older adults but is impaired in individuals with dementia. No studies have investigated whether value-directed strategic processing is disrupted in earlier stages of cognitive decline, namely, mild cognitive impairment (MCI). The current study examined behavioral and EEG differences in value-directed strategic processing between 18 individuals with MCI and 18 cognitively normal older controls using a value-directed list learning task. Behaviorally, individuals with MCI recalled fewer total and high-value words compared to controls, but no group differences were observed in low-value word recall. Neurally, individuals with MCI had reduced theta synchronization relative to controls between 100 and 200 ms post-stimulus. Greater alpha desynchronization was observed for high- versus low-value words between 300 and 400 ms in controls but not in the MCI group. The groups showed some processing similarities, with greater theta synchronization for low-value words between 700 and 800 ms and greater alpha desynchronization for high-value words between 500 and 1100 ms. Overall, value-directed strategic processing was compromised in individuals with MCI on both behavioral and neural measures relative to controls. These findings add to the growing body of literature on differences between typical cognitive aging and MCI.
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16
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Neuroimaging of Mouse Models of Alzheimer’s Disease. Biomedicines 2022; 10:biomedicines10020305. [PMID: 35203515 PMCID: PMC8869427 DOI: 10.3390/biomedicines10020305] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/25/2022] [Accepted: 01/25/2022] [Indexed: 12/23/2022] Open
Abstract
Magnetic resonance imaging (MRI) and positron emission tomography (PET) have made great strides in the diagnosis and our understanding of Alzheimer’s Disease (AD). Despite the knowledge gained from human studies, mouse models have and continue to play an important role in deciphering the cellular and molecular evolution of AD. MRI and PET are now being increasingly used to investigate neuroimaging features in mouse models and provide the basis for rapid translation to the clinical setting. Here, we provide an overview of the human MRI and PET imaging landscape as a prelude to an in-depth review of preclinical imaging in mice. A broad range of mouse models recapitulate certain aspects of the human AD, but no single model simulates the human disease spectrum. We focused on the two of the most popular mouse models, the 3xTg-AD and the 5xFAD models, and we summarized all known published MRI and PET imaging data, including contrasting findings. The goal of this review is to provide the reader with broad framework to guide future studies in existing and future mouse models of AD. We also highlight aspects of MRI and PET imaging that could be improved to increase rigor and reproducibility in future imaging studies.
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