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Chen J, Wang J, Duan K, Li X, Pan Z, Zhang J, Qin X, Hu Y, Lyu H. Selective vulnerability of hippocampal sub-regions in patients with subcortical vascular mild cognitive impairment. Brain Imaging Behav 2024; 18:922-929. [PMID: 38642314 PMCID: PMC11364596 DOI: 10.1007/s11682-024-00881-y] [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: 03/21/2024] [Indexed: 04/22/2024]
Abstract
Early diagnosis of subcortical vascular mild cognitive impairment (svMCI) is clinically essential because it is the most reversible subtype of all cognitive impairments. Since structural alterations of hippocampal sub-regions have been well studied in neurodegenerative diseases with pathophysiological cognitive impairments, we were eager to determine whether there is a selective vulnerability of hippocampal sub-fields in patients with svMCI. Our study included 34 svMCI patients and 34 normal controls (NCs), with analysis of T1 images and Montreal Cognitive Assessment (MoCA) scores. Gray matter volume (GMV) of hippocampal sub-regions was quantified and compared between the groups, adjusting for age, sex, and education. Additionally, we explored correlations between altered GMV in hippocampal sub-fields and MoCA scores in svMCI patients. Patients with svMCI exhibited selectively reduced GMV in several left hippocampal sub-regions, such as the hippocampal tail, hippocampal fissure, CA1 head, ML-HP head, CA4 head, and CA3 head, as well as decreased GMV in the right hippocampal tail. Specifically, GMV in the left CA3 head was inversely correlated with MoCA scores in svMCI patients. Our findings indicate that the atrophy pattern of patients with svMCI was predominantly located in the left hippocampal sub-regions. The left CA3 might be a crucial area underlying the distinct pathophysiological mechanisms of cognitive impairments with subcortical vascular origins.
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Affiliation(s)
- Jianxiang Chen
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Jianjun Wang
- Department of Neurology and Psychology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Ke Duan
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xinbei Li
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Zhongxian Pan
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Jinhuan Zhang
- Department of Acupuncture and Moxibustion, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xiude Qin
- Department of Neurology and Psychology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.
| | - Yuanming Hu
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.
| | - Hanqing Lyu
- Department of Radiology, The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.
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Petersen M, Chevalier C, Naegele FL, Ingwersen T, Omidvarnia A, Hoffstaedter F, Patil K, Eickhoff SB, Schnabel RB, Kirchhof P, Schlemm E, Cheng B, Thomalla G, Jensen M. Mapping the interplay of atrial fibrillation, brain structure, and cognitive dysfunction. Alzheimers Dement 2024; 20:4512-4526. [PMID: 38837525 PMCID: PMC11247702 DOI: 10.1002/alz.13870] [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: 12/08/2023] [Revised: 04/09/2024] [Accepted: 04/09/2024] [Indexed: 06/07/2024]
Abstract
INTRODUCTION Atrial fibrillation (AF) is associated with an elevated risk of cognitive impairment and dementia. Understanding the cognitive sequelae and brain structural changes associated with AF is vital for addressing ensuing health care needs. METHODS AND RESULTS We examined 1335 stroke-free individuals with AF and 2683 matched controls using neuropsychological assessments and multimodal neuroimaging. The analysis revealed that individuals with AF exhibited deficits in executive function, processing speed, and reasoning, accompanied by reduced cortical thickness, elevated extracellular free-water content, and widespread white matter abnormalities, indicative of small vessel pathology. Notably, brain structural differences statistically mediated the relationship between AF and cognitive performance. DISCUSSION Integrating a comprehensive analysis approach with extensive clinical and magnetic resonance imaging data, our study highlights small vessel pathology as a possible unifying link among AF, cognitive decline, and abnormal brain structure. These insights can inform diagnostic approaches and motivate the ongoing implementation of effective therapeutic strategies. Highlights We investigated neuropsychological and multimodal neuroimaging data of 1335 individuals with atrial fibrillation (AF) and 2683 matched controls. Our analysis revealed AF-associated deficits in cognitive domains of attention, executive function, processing speed, and reasoning. Cognitive deficits in the AF group were accompanied by structural brain alterations including reduced cortical thickness and gray matter volume, alongside increased extracellular free-water content as well as widespread differences of white matter integrity. Structural brain changes statistically mediated the link between AF and cognitive performance, emphasizing the potential of structural imaging markers as a diagnostic tool in AF-related cognitive decline.
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Affiliation(s)
- Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Céleste Chevalier
- Department of Cardiology, University Heart and Vascular Center, Hamburg, Germany
- DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
| | - Felix L Naegele
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thies Ingwersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Amir Omidvarnia
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - Kaustubh Patil
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - Renate B Schnabel
- Department of Cardiology, University Heart and Vascular Center, Hamburg, Germany
- DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
| | - Paulus Kirchhof
- Department of Cardiology, University Heart and Vascular Center, Hamburg, Germany
- DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
| | - Eckhard Schlemm
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Märit Jensen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Lim YA, Tan LS, Lee WT, Sim WL, Lv Y, Takakuni M, Saito S, Ihara M, Arumugam TV, Chen C, Wong FWS, Dawe GS. Hope for vascular cognitive impairment: Ac-YVAD-cmk as a novel treatment against white matter rarefaction. PLoS One 2024; 19:e0299703. [PMID: 38630707 PMCID: PMC11023579 DOI: 10.1371/journal.pone.0299703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/14/2024] [Indexed: 04/19/2024] Open
Abstract
Vascular cognitive impairment (VCI) is the second leading cause of dementia with limited treatment options, characterised by cerebral hypoperfusion-induced white matter rarefaction (WMR). Subcortical VCI is the most common form of VCI, but the underlying reasons for region susceptibility remain elusive. Recent studies employing the bilateral cortical artery stenosis (BCAS) method demonstrate that various inflammasomes regulate white matter injury and blood-brain barrier dysfunction but whether caspase-1 inhibition will be beneficial remains unclear. To address this, we performed BCAS on C57/BL6 mice to study the effects of Ac-YVAD-cmk, a caspase-1 inhibitor, on the subcortical and cortical regions. Cerebral blood flow (CBF), WMR, neuroinflammation and the expression of tight junction-related proteins associated with blood-brain barrier integrity were assessed 15 days post BCAS. We observed that Ac-YVAD-cmk restored CBF, attenuated BCAS-induced WMR and restored subcortical myelin expression. Within the subcortical region, BCAS activated the NLRP3/caspase-1/interleukin-1beta axis only within the subcortical region, which was attenuated by Ac-YVAD-cmk. Although we observed that BCAS induced significant increases in VCAM-1 expression in both brain regions that were attenuated with Ac-YVAD-cmk, only ZO-1 and occludin were observed to be significantly altered in the subcortical region. Here we show that caspase-1 may contribute to subcortical regional susceptibility in a mouse model of VCI. In addition, our results support further investigations into the potential of Ac-YVAD-cmk as a novel treatment strategy against subcortical VCI and other conditions exhibiting cerebral hypoperfusion-induced WMR.
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Affiliation(s)
- Yun-An Lim
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Li Si Tan
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei Thye Lee
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Wei Liang Sim
- Department of Physiology, National University of Singapore, Singapore, Singapore
| | - Yang Lv
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Maki Takakuni
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Saito
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
- Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | | | - Christopher Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Fred Wai-Shiu Wong
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Gavin Stewart Dawe
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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Liu Q, Zhang X. Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence. Front Aging Neurosci 2023; 15:1073039. [PMID: 37009448 PMCID: PMC10050753 DOI: 10.3389/fnagi.2023.1073039] [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: 10/18/2022] [Accepted: 02/24/2023] [Indexed: 03/17/2023] Open
Abstract
The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients' cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted,and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.
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Affiliation(s)
- Qiuping Liu
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xuezhu Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
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Tan L, Xing J, Wang Z, Du X, Luo R, Wang J, Zhao J, Zhao W, Yin C. Study of gray matter atrophy pattern with subcortical ischemic vascular disease-vascular cognitive impairment no dementia based on structural magnetic resonance imaging. Front Aging Neurosci 2023; 15:1051177. [PMID: 36815175 PMCID: PMC9939744 DOI: 10.3389/fnagi.2023.1051177] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/16/2023] [Indexed: 02/08/2023] Open
Abstract
Objective This study explored the structural imaging changes in patients with subcortical ischemic vascular disease (SIVD)-vascular cognitive impairment no dementia (VCIND) and the correlation between the changes in gray matter volume and the field of cognitive impairment to provide new targets for early diagnosis and treatment. Methods Our study included 15 patients with SIVD-normal cognitive impairment (SIVD-NCI), 63 with SIVD-VCIND, 26 with SIVD-vascular dementia (SIVD-VD), and 14 normal controls (NC). T1-weighted images of all participants were collected, and DPABI and SPM12 software were used to process the gray matter of the four groups based on voxels. Fisher's exact test, one-way ANOVA and Kruskal-Wallis H test were used to evaluate all clinical and demographic data and compare the characteristics of diencephalic gray matter atrophy in each group. Finally, the region of interest (ROI) of the SIVD-VCIND was extracted, and Pearson correlation analysis was performed between the ROI and the results of the neuropsychological scale. Results Compared to the NC, changes in gray matter atrophy were observed in the bilateral orbitofrontal gyrus, right middle temporal gyrus, superior temporal gyrus, and precuneus in the SIVD-VCIND. Gray matter atrophy was observed in the left cerebellar region 6, cerebellar crural region 1, bilateral thalamus, right precuneus, and calcarine in the SIVD-VD. Compared with the SIVD-VCIND, gray matter atrophy changes were observed in the bilateral thalamus in the SIVD-VD (p < 0.05, family-wise error corrected). In the SIVD-VCIND, the total gray matter volume, bilateral medial orbital superior frontal gyrus, right superior temporal gyrus, middle temporal gyrus, and precuneus were positively correlated with Boston Naming Test score, whereas the total gray matter volume, right superior temporal gyrus, and middle temporal gyrus were positively correlated with overall cognition. Conclusion Structural magnetic resonance imaging can detect extensive and subtle structural changes in the gray matter of patients with SIVD-VCIND and SIVD-VD, providing valuable evidences to explain the pathogenesis of subcortical vascular cognitive impairment and contributing to the early diagnosis of SIVD-VCIND and early warning of SIVD-VD.
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Affiliation(s)
- Lin Tan
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China,Department of Rehabilitation, The Sixth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jian Xing
- Department of Imaging, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Zhenqi Wang
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Xiao Du
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Ruidi Luo
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Jianhang Wang
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Jinyi Zhao
- Department of Imaging, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China
| | - Weina Zhao
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China,Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Mudanjiang, China,*Correspondence: Weina Zhao, ; Changhao Yin,
| | - Changhao Yin
- Department of Neurology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, China,Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Mudanjiang, China,*Correspondence: Weina Zhao, ; Changhao Yin,
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Liu C, Huang F, Qiu A. Monte Carlo Ensemble Neural Network for the diagnosis of Alzheimer's disease. Neural Netw 2023; 159:14-24. [PMID: 36525914 DOI: 10.1016/j.neunet.2022.10.032] [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: 06/07/2022] [Revised: 10/13/2022] [Accepted: 10/31/2022] [Indexed: 11/25/2022]
Abstract
Convolutional neural networks (CNNs) have been increasingly used in the computer-aided diagnosis of Alzheimer's Disease (AD). This study takes the advantage of the 2D-slice CNN fast computation and ensemble approaches to develop a Monte Carlo Ensemble Neural Network (MCENN) by introducing Monte Carlo sampling and an ensemble neural network in the integration with ResNet50. Our goals are to improve the 2D-slice CNN performance and to design the MCENN model insensitive to image resolution. Unlike traditional ensemble approaches with multiple base learners, our MCENN model incorporates one neural network learner and generates a large number of possible classification decisions via Monte Carlo sampling of feature importance within the combined slices. This can overcome the main weakness of the lack of 3D brain anatomical information in 2D-slice CNNs and develop a neural network to learn the 3D relevance of the features across multiple slices. Brain images from Alzheimer's Disease Neuroimaging Initiative (ADNI, 7199 scans), the Open Access Series of Imaging Studies-3 (OASIS-3, 1992 scans), and a clinical sample (239 scans) are used to evaluate the performance of the MCENN model for the classification of cognitively normal (CN), patients with mild cognitive impairment (MCI) and AD. Our MCENN with a small number of slices and minimal image processing (rigid transformation, intensity normalization, skull stripping) achieves the AD classification accuracy of 90%, better than existing 2D-slice CNNs (accuracy: 63%∼84%) and 3D CNNs (accuracy: 74%∼88%). Furthermore, the MCENN is robust to be trained in the ADNI dataset and applied to the OASIS-3 dataset and the clinical sample. Our experiments show that the AD classification accuracy of the MCENN model is comparable when using high- and low-resolution brain images, suggesting the insensitivity of the MCENN to image resolution. Hence, the MCENN does not require high-resolution 3D brain structural images and comprehensive image processing, which supports its potential use in a clinical setting.
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Affiliation(s)
- Chaoqiang Liu
- Department of Biomedical Engineering, National University of Singapore, Singapore
| | - Fei Huang
- School of Computer Engineering and Science, Shanghai University, China
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, Singapore; NUS (Suzhou) Research Institute, National University of Singapore, China; School of Computer Engineering and Science, Shanghai University, China; Institute of Data Science, National University of Singapore, Singapore; The N.1 Institute for Health, National University of Singapore, Singapore; The Johns Hopkins University, MD, USA.
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Ma J, Liu F, Wang Y, Ma L, Niu Y, Wang J, Ye Z, Zhang J. Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment. Neuroimage Clin 2022; 36:103245. [PMID: 36451351 PMCID: PMC9668649 DOI: 10.1016/j.nicl.2022.103245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/07/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022]
Abstract
Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.
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Affiliation(s)
- Juanwei Ma
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China; Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yang Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yali Niu
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jing Wang
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China.
| | - Jing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
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Shi Y, Mao H, Gao Q, Xi G, Zeng S, Ma L, Zhang X, Li L, Wang Z, Ji W, He P, You Y, Chen K, Shao J, Mao X, Fang X, Wang F. Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients. Front Aging Neurosci 2022; 14:973054. [PMID: 36118707 PMCID: PMC9475066 DOI: 10.3389/fnagi.2022.973054] [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: 06/19/2022] [Accepted: 08/16/2022] [Indexed: 12/04/2022] Open
Abstract
Background Reliable and individualized biomarkers are crucial for identifying early cognitive impairment in subcortical small-vessel disease (SSVD) patients. Personalized brain age prediction can effectively reflect cognitive impairment. Thus, the present study aimed to investigate the association of brain age with cognitive function in SSVD patients and assess the potential value of brain age in clinical assessment of SSVD. Materials and methods A prediction model for brain age using the relevance vector regression algorithm was developed using 35 healthy controls. Subsequently, the prediction model was tested using 51 SSVD patients [24 subjective cognitive impairment (SCI) patients and 27 mild cognitive impairment (MCI) patients] to identify brain age-related imaging features. A support vector machine (SVM)-based classification model was constructed to differentiate MCI from SCI patients. The neurobiological basis of brain age-related imaging features was also investigated based on cognitive assessments and oxidative stress biomarkers. Results The gray matter volume (GMV) imaging features accurately predicted brain age in individual patients with SSVD (R2 = 0.535, p < 0.001). The GMV features were primarily distributed across the subcortical system (e.g., thalamus) and dorsal attention network. SSVD patients with age acceleration showed significantly poorer Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores. The classification model based on GMV features could accurately distinguish MCI patients from SCI patients (area under the curve = 0.883). The classification outputs of the classification model exhibited significant associations with MoCA scores, Trail Making Tests A and B scores, Stroop Color and Word Test C scores, information processing speed total scores, and plasma levels of total antioxidant capacity in SSVD patients. Conclusion Brain age can be accurately quantified using GMV imaging data and shows potential clinical value for identifying early cognitive impairment in SSVD patients.
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Affiliation(s)
- Yachen Shi
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Interventional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Functional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- *Correspondence: Yachen Shi,
| | - Haixia Mao
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Qianqian Gao
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Guangjun Xi
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Interventional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Siyuan Zeng
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Lin Ma
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Xiuping Zhang
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Lei Li
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Interventional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Zhuoyi Wang
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Interventional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Wei Ji
- Department of Functional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Neurosurgery, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Ping He
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Yiping You
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Functional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Kefei Chen
- Department of Functional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Neurosurgery, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Junfei Shao
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Xuqiang Mao
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
| | - Xiangming Fang
- Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Xiangming Fang,
| | - Feng Wang
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Department of Interventional Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, China
- Feng Wang,
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He C, Gong M, Li G, Shen Y, Han L, Han B, Lou M. Evaluation of White Matter Microstructural Alterations in Patients with Post-Stroke Cognitive Impairment at the Sub-Acute Stage. Neuropsychiatr Dis Treat 2022; 18:563-573. [PMID: 35313564 PMCID: PMC8933623 DOI: 10.2147/ndt.s343906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/06/2022] [Indexed: 11/23/2022] Open
Abstract
PURPOSE To investigate white matter alterations in post-stroke cognitive impairment (PSCI) patients at the subacute stage employing diffusion kurtosis and tensor imaging. METHODS Thirty PSCI patients at the subacute phase and 30 healthy controls (HC) underwent diffusion kurtosis imaging (DKI) scans and neuropsychological assessments. Based on the tract-based spatial statistics and atlas-based ROI analysis, fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), kurtosis fractional anisotropy (KFA), axial kurtosis (AK), and radial kurtosis (RK) were compared in specific white matter fiber bundles between the groups (with family-wise error correction). Adjusting for age and gender, a partial correlation was conducted between neurocognitive assessments and DKI metrics in the PSCI group. RESULTS In comparison with the HC, PSCI patients significantly showed decreased MK, RK, and FA and increased MD values in the genu of corpus callosum, anterior limb internal capsule, and left superior corona radiata. In addition, DKI detected more white matter region changes in MK (31/48), KFA (40/48), and RK (25/48) than DTI with FA (28/48) and MD (21/48), which primarily consisted of the right cingulum, right superior longitudinal fasciculus, and left posterior limb of internal capsule. In the left anterior limb of internal capsule, MK and RK values were significantly negatively correlated with TMT-B (r = -0.435 and -0.414, P < 0.05), and KFA values (r = -0.385, P < 0.05) of corpus callosum negatively associated with TMT-B. CONCLUSION Combing DTI, DKI, and neuropsychological tests, we found extensive damaged white matter microstructure and poor execution performance in subacute PSCI patients. DKI could detect more subtle white matter changes than DTI metrics. Our findings provide added information for exploring the mechanisms of PSCI and conducting cognitive rehabilitation in the subacute stage.
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Affiliation(s)
- Chunxue He
- Shenzhen Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, People's Republic of China.,Department of Radiology, Longgang District Central Hospital of Shenzhen, Shenzhen, People's Republic of China
| | - Mingqiang Gong
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, People's Republic of China.,Department of Acupuncture, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, People's Republic of China
| | - Gengxiao Li
- Shenzhen Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, People's Republic of China.,Department of Radiology, Longgang District Central Hospital of Shenzhen, Shenzhen, People's Republic of China
| | - Yunxia Shen
- Department of Radiology, Longgang District Central Hospital of Shenzhen, Shenzhen, People's Republic of China
| | - Longyin Han
- Department of Neurology, Beijing Longfu Hospital, Beijing, People's Republic of China
| | - Bin Han
- Department of Rehabilitation Medicine, Longgang District Central Hospital of Shenzhen, Guangdong, People's Republic of China
| | - Mingwu Lou
- Department of Radiology, Longgang District Central Hospital of Shenzhen, Shenzhen, People's Republic of China
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10
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Zhu J, Zhang H, Chong YS, Shek LP, Gluckman PD, Meaney MJ, Fortier MV, Qiu A. Integrated structural and functional atlases of Asian children from infancy to childhood. Neuroimage 2021; 245:118716. [PMID: 34767941 DOI: 10.1016/j.neuroimage.2021.118716] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/06/2021] [Accepted: 11/08/2021] [Indexed: 12/21/2022] Open
Abstract
The developing brain grows exponentially in the first few years of life. There is a need to have age-appropriate brain atlases that coherently characterize the geometry of the cerebral cortex, white matter tracts, and functional organization. This study employed multi-modal brain images of an Asian cohort and constructed brain structural and functional atlases for 6-month-old infants, 4.5-, 6-, and 7.5-year-old children. We exploited large deformation diffeomorphic metric mapping and probabilistic atlas generation approaches to integrate structural MRI and diffusion weighted images (DWIs) and to create the atlas where white matter tracts well fit into the cortical folding pattern. Based on this structural atlas, we then employed spectral clustering to parcellate the brain into functional networks from resting-state fMRI (rs-fMRI). Our results provided the atlas that characterizes the cortical folding geometry, subcortical regions, deep white matter tracts, as well as functional networks in a stereotaxic coordinate space for the four different age groups. The functional networks consisting of the primary cortex were well established in infancy and remained stable to childhood, while specific higher-order functional networks showed specific patterns of hemispherical, subcortical-cerebellar, and cortical-cortical integration and segregation from infancy to childhood. Our multi-modal fusion analysis demonstrated the use of the integrated structural and functional atlas for understanding coherent patterns of brain anatomical and functional development during childhood. Hence, our atlases can be potentially used to study coherent patterns of brain anatomical and functional development.
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Affiliation(s)
- Jingwen Zhu
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Block E4 #04-08, 11758, Singapore
| | - Han Zhang
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Block E4 #04-08, 11758, Singapore
| | - Yap-Seng Chong
- Singapore Institute for Clinical Sciences, Singapore; Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lynette P Shek
- Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | | | - Michael J Meaney
- Singapore Institute for Clinical Sciences, Singapore; Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Marielle V Fortier
- Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Block E4 #04-08, 11758, Singapore; The N.1 Institute for Health, National University of Singapore, Singapore; Institute of Data Science, National University of Singapore, Singapore; NUS (Suzhou) Research Institute, National University of Singapore, China; Department of Biomedical Engineering, The Johns Hopkins University, USA.
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11
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Du J, Zhu H, Yu L, Lu P, Qiu Y, Zhou Y, Cao W, Lu D, Zhao W, Yang J, Sun J, Xu Q. Multi-Dimensional Diffusion Tensor Imaging Biomarkers for Cognitive Decline From the Preclinical Stage: A Study of Post-stroke Small Vessel Disease. Front Neurol 2021; 12:687959. [PMID: 34322083 PMCID: PMC8311001 DOI: 10.3389/fneur.2021.687959] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/14/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: We aim to investigate whether multi-dimensional diffusion tensor imaging (DTI) measures can sensitively identify different cognitive status of cerebral small vessel disease (CSVD) and to explore the underlying pattern of white matter disruption in CSVD. Methods: Two hundred and two participants were recruited, composed of 99 CSVD patients with mild cognitive impairment (VaMCI) and 60 with no cognitive impairment (NCI) and 43 healthy subjects as normal controls (NC). Full domain neuropsychological tests and diffusion-weighted imaging were performed on each subject. DTI metrics such as fractional anisotropy (FA), mean diffusivity (MD), the skeletonized mean diffusivity (PSMD), and structural brain network measures including network strength, global efficiency (EGlobal), and local efficiency (ELocal) were calculated. Region of interest (ROI) analysis of 42 white matter tracts was performed to examine the regional anatomical white matter disruption for each group. Results: Significant differences of multiple cognitive test scores across all cognitive domains especially processing and executive function existed among the three groups. DTI measures (FA, MD, and PSMD) showed significant group difference with the cognitive status changing. FA and EGlobal showed significant correlation with processing speed, executive function, and memory. ROI analysis found that white matter integrity impairment occurred from the preclinical stage of vascular cognitive impairment (VCI) due to CSVD. These lesions in the NCI group mainly involved some longitudinal fibers such as right superior longitudinal fasciculus (SLF-R), right superior fronto-occipital fasciculus (SFO-R), and right uncinate fasciculus (UNC-R), which might be more vulnerable to the cerebrovascular aging and disease process. Conclusions: DTI measures are sensitive neuroimaging markers in detecting the early cognitive impairment and able to differentiate the different cognitive status due to CSVD. Subtle changes of some vulnerable white matter tracts may be observed from the preclinical stage of VCI and have a local to general spreading pattern during the disease progression.
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Affiliation(s)
- Jing Du
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Health Management Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Hong Zhu
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ling Yu
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Peiwen Lu
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Health Management Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Yage Qiu
- Department of Radiology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Wenwei Cao
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Dong Lu
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Wei Zhao
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Jie Yang
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
| | - Junfeng Sun
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Xu
- Renji-UNSW CHeBA (Centre for Healthy Brain Ageing of University of New South Wales) Neurocognitive Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Neurology, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China.,Department of Health Management Center, Renji Hospital, Medical School of Shanghai Jiao Tong University, Shanghai, China
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12
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Liu Y, Hu A, Chen L, Li B, Zhang M, Xi P, Yang Q, Tang R, Huang Q, He J, Lang Y, Zhang Y. Association between cortical thickness and distinct vascular cognitive impairment and dementia in patients with white matter lesions. Exp Physiol 2021; 106:1612-1620. [PMID: 33866642 DOI: 10.1113/ep089419] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 04/08/2021] [Indexed: 12/29/2022]
Abstract
NEW FINDINGS What is the central question of this study? White matter lesions (WMLs) are a brain disease characterized by altered brain structural and functional connectivity, but findings have shown an inconsistent pattern: are there distinct cortical thickness changes in patients with WMLs subtypes? What is the main finding and its importance? Patients with WMLs with non-dementia vascular cognitive impairment and WMLs with vascular dementia showed distinct pathophysiology in cortical thickness. These neural correlates of WMLs should be considered in future treatment. ABSTRACT The effect of cortical thickness on white matter lesions (WMLs) in patients with distinct vascular cognitive impairments is relatively unknown. This study investigated the correlation between cortical thickness and vascular cognitive manifestations. WML patients and healthy controls from Beijing Tiantan Hospital between 2014 and 2018 were included. The patients were further divided into two subgroups, namely WMLs with non-dementia vascular cognitive impairment (WML-VCIND) and WMLs with vascular dementia (WML-VaD) according to the Clinical Dementia Rating (CDR) scale and the Beijing version of the Montreal Cognitive Assessment (MoCA). Changes in cortical thickness were calculated using FreeSurfer. Pearson's correlation analysis was performed to explore the relationship between cognitive manifestations and cortical thickness in WML patients. Forty-five WML patients and 23 healthy controls were recruited. The WML group exhibited significant difference in cortical thickness compared to the control group. Significantly decreased cortical thickness in the middle and superior frontal gyri, middle temporal gyrus, angular gyrus and insula was found in the WML-VaD versus WML-VCIND subgroup. Cortical thickness deficits of the left caudal middle frontal gyrus (r = 0.451, P = 0.002), left rostral middle frontal gyrus (r = 0.514, P < 0.001), left superior frontal gyrus (r = 0.410, P = 0.006), right middle temporal gyrus (r = 0.440, P = 0.003), right pars triangularis (r = 0.462, P = 0.002), right superior frontal gyrus (r = 0.434, P = 0.004) and right insula (r = 0.499, P = 0.001) were positively correlated with the MoCA score in WML patients. The specific pattern of cortical thickness deficits in the WML-VaD subgroup revealed the pathophysiology of WMLs, which should be considered in future treatment of WMLs.
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Affiliation(s)
- Yafei Liu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Anming Hu
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Luyao Chen
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Bo Li
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Minjian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Pengcheng Xi
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Qinghu Yang
- College of Life Sciences & Research Center for Resource Peptide Drugs, Shaanxi Engineering & Technological Research Center for Conversation & Utilization of Regional Biological Resources, Yanan University, Yanan, China
| | - Rongyu Tang
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Qiang Huang
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Jiping He
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Yiran Lang
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Yumei Zhang
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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13
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Qin Q, Tang Y, Dou X, Qu Y, Xing Y, Yang J, Chu T, Liu Y, Jia J. Default mode network integrity changes contribute to cognitive deficits in subcortical vascular cognitive impairment, no dementia. Brain Imaging Behav 2021; 15:255-265. [PMID: 32125614 DOI: 10.1007/s11682-019-00252-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Vascular cognitive impairment, no dementia (VCIND) refers to cognitive deficits associated with underlying vascular causes that are insufficient to confirm a diagnosis of dementia. The default mode network (DMN) is a large-scale brain network of interacting brain regions involved in attention, working memory and executive function. The role of DMN white matter integrity in cognitive deficits of VCIND patients is unclear. Using diffusion tensor imaging (DTI), this study was carried out to investigate white matter microstructural changes in the DMN in VCIND patients and their contributions to cognitive deficits. Thirty-one patients with subcortical VCIND and twenty-two healthy elderly subjects were recruited. All patients underwent neuropsychological assessments and DTI examination. Voxel-based analyses were performed to extract fractional anisotropy (FA) and mean diffusivity (MD) measures in the DMN. Compared with the healthy elderly subjects, patients diagnosed with subcortical VCIND presented with abnormal white matter integrity in several key hubs of the DMN. The severity of damage in the white matter microstructure in the DMN significantly correlated with cognitive dysfunction. Mediation analyses demonstrated that DTI values could account for attention, executive and language impairments, and partly mediated global cognitive dysfunction in the subcortical VCIND patients. DMN integrity is significantly impaired in subcortical VCIND patients. The disrupted DMN connectivity could explain the attention, language and executive dysfunction, which indicates that the white matter integrity of the DMN may be a neuroimaging marker for VCIND.
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Affiliation(s)
- Qi Qin
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, 100053, China
| | - Yi Tang
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, 100053, China.
| | - Xuejiao Dou
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Yida Qu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Xing
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, 100053, China
| | - Jianwei Yang
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, 100053, China
| | - Tianshu Chu
- Center for Data Science, Courant, New York University, New York, NY, USA
| | - Yong Liu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jianping Jia
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, 100053, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China
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14
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Feng M, Zhang Y, Liu Y, Wu Z, Song Z, Ma M, Wang Y, Dai H. White Matter Structural Network Analysis to Differentiate Alzheimer's Disease and Subcortical Ischemic Vascular Dementia. Front Aging Neurosci 2021; 13:650377. [PMID: 33867969 PMCID: PMC8044349 DOI: 10.3389/fnagi.2021.650377] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 02/25/2021] [Indexed: 12/16/2022] Open
Abstract
To explore the evaluation of white matter structural network analysis in the differentiation of Alzheimer's disease (AD) and subcortical ischemic vascular dementia (SIVD), 67 participants [31 AD patients, 19 SIVD patients, and 19 normal control (NC)] were enrolled in this study. Each participant underwent 3.0T MRI scanning. Diffusion tensor imaging (DTI) data were analyzed by graph theory (GRETNA toolbox). Statistical analyses of global parameters [gamma, sigma, lambda, global shortest path length (Lp), global efficiency (Eg), and local efficiency (Eloc)] and nodal parameters [betweenness centrality (BC)] were obtained. Network-based statistical analysis (NBS) was employed to analyze the group differences of structural connections. The diagnosis efficiency of nodal BC in identifying different types of dementia was assessed by receiver operating characteristic (ROC) analysis. There were no significant differences of gender and years of education among the groups. There were no significant differences of sigma and gamma in AD vs. NC and SIVD vs. NC, whereas the Eg values of AD and SIVD were statistically decreased, and the lambda values were increased. The BC of the frontal cortex, left superior parietal gyrus, and left precuneus in AD patients were obviously reduced, while the BC of the prefrontal and subcortical regions were decreased in SIVD patients, compared with NC. SIVD patients had decreased structural connections in the frontal, prefrontal, and subcortical regions, while AD patients had decreased structural connections in the temporal and occipital regions and increased structural connections in the frontal and prefrontal regions. The highest area under curve (AUC) of BC was 0.946 in the right putamen for AD vs. SIVD. White matter structural network analysis may be a potential and promising method, and the topological changes of the network, especially the BC change in the right putamen, were valuable in differentiating AD and SIVD patients.
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Affiliation(s)
- Mengmeng Feng
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yue Zhang
- Department of Geratology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yuanqing Liu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Zhiwei Wu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Ziyang Song
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Mengya Ma
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Yueju Wang
- Department of Geratology, The First Affiliated Hospital of Soochow University, Suzhou City, China
| | - Hui Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou City, China
- Institute of Medical Imaging, Soochow University, Suzhou City, China
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15
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Wang J, Lyu H, Chen J, Lin S, Zheng H, Li J, Kong F, Gao J, Yu H, Hu Y, Guo Z. Cortical Alterations Are Associated with Depression in Subcortical Vascular Mild Cognitive Impairment Revealed by Surface-Based Morphometry. J Alzheimers Dis 2020; 78:673-681. [PMID: 33016903 DOI: 10.3233/jad-200156] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Late-life depression often coexists with vascular cognitive impairment and affects the quality of life for elders. However, little is known about cortical morphometric interactions between subcortical vascular mild cognitive impairment (svMCI) and concomitant mild depressive symptoms at the early stage. OBJECTIVE We aimed to investigate cortical alterations of svMCI with and without depressive symptoms and determine whether these parameters are associated with depression symptoms and/or cognitive impairments. METHODS Surface based morphometry was performed on 18 svMCI patients with depressive symptoms (svMCI + D), 16 svMCI patients without depressive symptoms (svMCI-D), and 23 normal controls (NC). RESULTS Compared to NC, both svMCI + D and svMCI-D patients exhibited significantly decreased surface area (SA) in many cortical areas. Interestingly, svMCI + D patients showed significantly increased rather than decreased SA in right lateral occipital gyrus (LOG.R), and a consistent trend of increased SA in these areas compared to svMCI-D. In addition, the svMCI + D showed increased gray matter volume of left pericalcarine (periCAL.L) than svMCI-D, whereas svMCI-D showed decreased gray matter volume of periCAL.L than NC. Further correlation analyses revealed that the SA of left superior temporal gyrus (STG.L) and right lateral orbital part of frontal gyrus (lorbFG.R) were significantly correlated with Hamilton depression rating scale of svMCI + D. CONCLUSION In conclusion, these results extend our insight into svMCI and add weight to reevaluation of concomitant early stage depressive symptoms. Moreover, we suggest that LOG.R∖periCAL.L∖STG.L∖lorbFG.R might serve as sensitive and trait-dependent biomarkers to detect concomitant depressive symptoms in svMCI patients.
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Affiliation(s)
- Jianjun Wang
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
| | - Hanqing Lyu
- Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China.,Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China
| | - Jianxiang Chen
- Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China.,Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China
| | - Songjun Lin
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
| | - Haotao Zheng
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
| | - Jinfang Li
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
| | - Fanxin Kong
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
| | - Jinyun Gao
- Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China.,Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China
| | - Haibo Yu
- Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China.,Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China
| | - Yuanming Hu
- Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China.,Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China
| | - Zhouke Guo
- Department of Neurology and Psychology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, P. R. China.,Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, P. R. China
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16
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Sang L, Liu C, Wang L, Zhang J, Zhang Y, Li P, Qiao L, Li C, Qiu M. Disrupted Brain Structural Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment With No Dementia. Front Aging Neurosci 2020; 12:6. [PMID: 32063840 PMCID: PMC7000429 DOI: 10.3389/fnagi.2020.00006] [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: 09/10/2019] [Accepted: 01/10/2020] [Indexed: 11/28/2022] Open
Abstract
The alteration of the functional topological organization in subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) patients has been illuminated by previous neuroimaging studies. However, in regard to the changes in the structural connectivity of brain networks, little has been reported. In this study, a total of 27 subjects, consisting of 13 SIVCIND patients, and 14 normal controls, were recruited. Each of the structural connectivity networks was constructed by diffusion tensor tractography. Subsequently, graph theory, and network-based statistics (NBS) were employed to analyze the whole-brain mean factional anisotropy matrix. After removing the factor of age, gender, and duration of formal education, the clustering coefficients (Cp) and global efficiency (Eglob) were significantly decreased and the mean path length (Lp) was significantly increased in SIVCIND patients compared with normal controls. Using the combination of four network topological parameters as the classification feature, a classification accuracy of 78% was obtained by leave-one-out cross-validation for all subjects with a sensitivity of 69% and a specificity of 86%. Moreover, we also found decreased structural connections in the SIVCIND patients, which mainly concerned fronto-occipital, fronto-subcortical, and tempo-occipital connections (NBS corrected, p < 0.01). Additionally, significantly altered nodal centralities were found in several brain regions of the SIVCIND patients, mainly located in the prefrontal, subcortical, and temporal cortices. These results suggest that cognitive impairment in SIVCIND patients is associated with disrupted topological organization and provide structural evidence for developing reliable biomarkers related to cognitive decline in SIVCIND.
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Affiliation(s)
- Linqiong Sang
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Chen Liu
- Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Li Wang
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Jingna Zhang
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Ye Zhang
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Pengyue Li
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Liang Qiao
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Chuanming Li
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Mingguo Qiu
- Department of Medical Imaging, School of Biomedical Engineering, Third Military Medical University, Chongqing, China
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17
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Levman J, Fang Z, Zumwalt K, Cogger L, Vasung L, MacDonald P, Lim A, Takahashi E. Asymmetric Insular Connectomics Revealed by Diffusion Magnetic Resonance Imaging Analysis of Healthy Brain Development. Brain Connect 2019; 9:2-12. [PMID: 30501515 DOI: 10.1089/brain.2018.0582] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The insula has been implicated in playing important roles in various brain functions including consciousness, homeostasis, perception, self-awareness, language processing, and interpersonal experience. Abnormalities of the insula have been observed in patients suffering from addiction, deteriorating language function, anorexia, and emotional dysregulation. We analyzed typical development of insular connections in a large-scale pediatric population using 642 magnetic resonance imaging examinations. Interpreting large quantities of acquired data is one of the major challenges in connectomics. This article focuses its analysis on the connectivity observed between the insula and many other regions throughout the brain and performs a hemispheric asymmetry analysis comparing localized connectome measurements. Results demonstrate asymmetries in the pathways connecting the insula to the superior temporal region, pars opercularis, etc. that may be representative of language lateralization in the brain. Results also demonstrate multiple fiber pathways that exhibit hemispheric dominance in tract length and an inverted hemispheric dominance in tract counts, implying the presence of asymmetric lateralization of some of the brain's insular pathways. This study illustrates the investigative potential of performing connectomics-style analyses in a clinical context across a large population of children as part of routine imaging, demonstrating the feasibility of using current technologies to perform regionally focused clinical connectivity studies.
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Affiliation(s)
- Jacob Levman
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts.,2 Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts.,3 Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,4 Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, Antigonish, Canada
| | - Zihang Fang
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts
| | - Katarina Zumwalt
- 5 OceanPath Fellow, Coady International Institute, St. Francis Xavier University, Antigonish, Canada
| | - Liam Cogger
- 4 Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, Antigonish, Canada
| | - Lana Vasung
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts.,3 Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
| | - Patrick MacDonald
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts
| | - Ashley Lim
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts
| | - Emi Takahashi
- 1 Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts.,2 Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts.,3 Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
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18
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Wee CY, Liu C, Lee A, Poh JS, Ji H, Qiu A. Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations. Neuroimage Clin 2019; 23:101929. [PMID: 31491832 PMCID: PMC6627731 DOI: 10.1016/j.nicl.2019.101929] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/02/2019] [Accepted: 07/02/2019] [Indexed: 01/18/2023]
Abstract
Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/AD diagnosis of other populations. This study aimed to employ a spectral graph convolutional neural network (graph-CNN), that incorporated cortical thickness and geometry, to identify MCI and AD based on 3089 T1-weighted MRI data of the ADNI-2 cohort, and to evaluate its feasibility to predict AD in the ADNI-1 cohort (n = 3602) and an Asian cohort (n = 347). For the ADNI-2 cohort, the graph-CNN showed classification accuracy of controls (CN) vs. AD at 85.8% and early MCI (EMCI) vs. AD at 79.2%, followed by CN vs. late MCI (LMCI) (69.3%), LMCI vs. AD (65.2%), EMCI vs. LMCI (60.9%), and CN vs. EMCI (51.8%). We demonstrated the robustness of the graph-CNN among the existing deep learning approaches, such as Euclidean-domain-based multilayer network and 1D CNN on cortical thickness, and 2D and 3D CNNs on T1-weighted MR images of the ADNI-2 cohort. The graph-CNN also achieved the prediction on the conversion of EMCI to AD at 75% and that of LMCI to AD at 92%. The find-tuned graph-CNN further provided a promising CN vs. AD classification accuracy of 89.4% on the ADNI-1 cohort and >90% on the Asian cohort. Our study demonstrated the feasibility to transfer AD/MCI classifiers learned from one population to the other. Notably, incorporating cortical geometry in CNN has the potential to improve classification performance.
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Affiliation(s)
- Chong-Yaw Wee
- Department of Biomedical Engineering and Clinical Research Center, National University of Singapore, Singapore
| | - Chaoqiang Liu
- Department of Biomedical Engineering and Clinical Research Center, National University of Singapore, Singapore
| | - Annie Lee
- Department of Biomedical Engineering and Clinical Research Center, National University of Singapore, Singapore
| | - Joann S Poh
- Department of Biomedical Engineering and Clinical Research Center, National University of Singapore, Singapore
| | - Hui Ji
- Department of Mathematics, National University of Singapore, Singapore
| | - Anqi Qiu
- Department of Biomedical Engineering and Clinical Research Center, National University of Singapore, Singapore.
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19
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Fu Z, Caprihan A, Chen J, Du Y, Adair JC, Sui J, Rosenberg GA, Calhoun VD. Altered static and dynamic functional network connectivity in Alzheimer's disease and subcortical ischemic vascular disease: shared and specific brain connectivity abnormalities. Hum Brain Mapp 2019; 40:3203-3221. [PMID: 30950567 DOI: 10.1002/hbm.24591] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 03/19/2019] [Accepted: 03/23/2019] [Indexed: 12/16/2022] Open
Abstract
Subcortical ischemic vascular disease (SIVD) is a major subtype of vascular dementia with features that overlap clinically with Alzheimer's disease (AD), confounding diagnosis. Neuroimaging is a more specific and biologically based approach for detecting brain changes and thus may help to distinguish these diseases. There is still a lack of knowledge regarding the shared and specific functional brain abnormalities, especially functional connectivity changes in relation to AD and SIVD. In this study, we investigated both static functional network connectivity (sFNC) and dynamic FNC (dFNC) between 54 intrinsic connectivity networks in 19 AD patients, 19 SIVD patients, and 38 age-matched healthy controls. The results show that both patient groups have increased sFNC between the visual and cerebellar (CB) domains but decreased sFNC between the cognitive-control and CB domains. SIVD has specifically decreased sFNC within the sensorimotor domain while AD has specifically altered sFNC between the default-mode and CB domains. In addition, SIVD has more occurrences and a longer dwell time in the weakly connected dFNC states, but with fewer occurrences and a shorter dwell time in the strongly connected dFNC states. AD has both similar and opposite changes in certain dynamic features. More importantly, the dynamic features are found to be associated with cognitive performance. Our findings highlight similar and distinct functional connectivity alterations in AD and SIVD from both static and dynamic perspectives and indicate dFNC to be a more important biomarker for dementia since its progressively altered patterns can better track cognitive impairment in AD and SIVD.
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Affiliation(s)
- Zening Fu
- The Mind Research Network, Albuquerque, New Mexico
| | | | - Jiayu Chen
- The Mind Research Network, Albuquerque, New Mexico
| | - Yuhui Du
- The Mind Research Network, Albuquerque, New Mexico.,School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - John C Adair
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, New Mexico
| | - Jing Sui
- The Mind Research Network, Albuquerque, New Mexico.,Chinese Academy of Sciences (CAS), Centre for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Gary A Rosenberg
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, New Mexico
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, New Mexico.,Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
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20
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Raja R, Rosenberg G, Caprihan A. Review of diffusion MRI studies in chronic white matter diseases. Neurosci Lett 2019; 694:198-207. [PMID: 30528980 PMCID: PMC6380179 DOI: 10.1016/j.neulet.2018.12.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 12/03/2018] [Accepted: 12/04/2018] [Indexed: 02/07/2023]
Abstract
Diffusion MRI studies characterizing the changes in white matter (WM) due to vascular cognitive impairment, which includes all forms of small vessel disease are reviewed. We reviewed the usefulness of diffusion methods in discriminating the affected WM regions and its relation to cognitive impairment. These studies were categorized based on the diffusion MRI techniques used. The most common method was the diffusion tensor imaging, whereas other methods included diffusion weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and studies based on diffusion tractography. The diffusion measures showed correlation with cognitive scores and disease progression, with mean diffusivity being the most robust parameter. Future studies should focus on incorporating multi-compartment and higher order diffusion models, which can handle the presence of multiple and crossing fibers inside a voxel.
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Affiliation(s)
- Rajikha Raja
- The MIND Research Network, Albuquerque, NM, United States.
| | - Gary Rosenberg
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
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21
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Chen X, Duan H, Xiao L, Gan J. Genetic and Epigenetic Alterations Underlie Oligodendroglia Susceptibility and White Matter Etiology in Psychiatric Disorders. Front Genet 2018; 9:565. [PMID: 30524471 PMCID: PMC6262033 DOI: 10.3389/fgene.2018.00565] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 11/06/2018] [Indexed: 12/19/2022] Open
Abstract
Numerous genetic risk loci are found to associate with major neuropsychiatric disorders represented by schizophrenia. The pathogenic roles of genetic risk loci in psychiatric diseases are further complicated by the association with cell lineage- and/or developmental stage-specific epigenetic alterations. Besides aberrant assembly and malfunction of neuronal circuitry, an increasing volume of discoveries clearly demonstrate impairment of oligodendroglia and disruption of white matter integrity in psychiatric diseases. Nonetheless, whether and how genetic risk factors and epigenetic dysregulations for neuronal susceptibility may affect oligodendroglia is largely unknown. In this mini-review, we will discuss emerging evidence regarding the functional interplay between genetic risk loci and epigenetic factors, which may underlie compromised oligodendroglia and myelin development in neuropsychiatric disorders. Transcriptional and epigenetic factors are the major aspects affected in oligodendroglia. Moreover, multiple disease susceptibility genes are connected by epigenetically modulated transcriptional and post-transcriptional mechanisms. Oligodendroglia specific complex molecular orchestra may explain how distinct risk factors lead to the common clinical expression of white matter pathology of neuropsychiatric disorders.
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Affiliation(s)
- Xianjun Chen
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
| | - Huifeng Duan
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
| | - Lan Xiao
- Department of Histology and Embryology, Chongqing Key Laboratory of Neurobiology, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jingli Gan
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
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22
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Aslaksen PM, Bystad MK, Ørbo MC, Vangberg TR. The relation of hippocampal subfield volumes to verbal episodic memory measured by the California Verbal Learning Test II in healthy adults. Behav Brain Res 2018; 351:131-137. [DOI: 10.1016/j.bbr.2018.06.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 06/04/2018] [Accepted: 06/07/2018] [Indexed: 01/25/2023]
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23
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ten Brinke LF, Hsu CL, Best JR, Barha CK, Liu-Ambrose T. Increased Aerobic Fitness Is Associated with Cortical Thickness in Older Adults with Mild Vascular Cognitive Impairment. JOURNAL OF COGNITIVE ENHANCEMENT 2018. [DOI: 10.1007/s41465-018-0077-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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24
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Sang L, Chen L, Wang L, Zhang J, Zhang Y, Li P, Li C, Qiu M. Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients. Front Neurol 2018. [PMID: 29535678 PMCID: PMC5834750 DOI: 10.3389/fneur.2018.00094] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p < 0.01) mainly involved the orbitofrontal, parietal, and temporal cortices, as well as the basal ganglia. The brain connectivity network was progressively disrupted as cognitive impairment worsened, with an increased number of decreased connections between brain regions. We also observed more reductions in nodal efficiency in the prefrontal and temporal cortices for SIVaD than for SIVCIND. These findings indicated a progressively disrupted pattern of the brain functional connectivity network with increased cognitive impairment and showed promise for the development of reliable biomarkers of network metric changes related to cognitive impairment caused by SIVD.
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Affiliation(s)
- Linqiong Sang
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Lin Chen
- Department of Psychology, Third Military Medical University, Chongqing, China
| | - Li Wang
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Jingna Zhang
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Ye Zhang
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Pengyue Li
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
| | - Chuanming Li
- Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Mingguo Qiu
- Department of Medical Imaging, College of Biomedical Engineering, Third Military Medical University, Chongqing, China
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25
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Alves GS, de Carvalho LDA, Sudo FK, Briand L, Laks J, Engelhardt E. A panel of clinical and neuropathological features of cerebrovascular disease through the novel neuroimaging methods. Dement Neuropsychol 2017; 11:343-355. [PMID: 29354214 PMCID: PMC5769992 DOI: 10.1590/1980-57642016dn11-040003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED The last decade has witnessed substantial progress in acquiring diagnostic biomarkers for the diagnostic workup of cerebrovascular disease (CVD). Advanced neuroimaging methods not only provide a strategic contribution for the differential diagnosis of vascular dementia (VaD) and vascular cognitive impairment (VCI), but also help elucidate the pathophysiological mechanisms ultimately leading to small vessel disease (SVD) throughout its course. OBJECTIVE In this review, the novel imaging methods, both structural and metabolic, were summarized and their impact on the diagnostic workup of age-related CVD was analysed. Methods: An electronic search between January 2010 and 2017 was carried out on PubMed/MEDLINE, Institute for Scientific Information Web of Knowledge and EMBASE. RESULTS The use of full functional multimodality in simultaneous Magnetic Resonance (MR)/Positron emission tomography (PET) may potentially improve the clinical characterization of VCI-VaD; for structural imaging, MRI at 3.0 T enables higher-resolution scanning with greater imaging matrices, thinner slices and more detail on the anatomical structure of vascular lesions. CONCLUSION Although the importance of most of these techniques in the clinical setting has yet to be recognized, there is great expectancy in achieving earlier and more refined therapeutic interventions for the effective management of VCI-VaD.
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Affiliation(s)
| | | | - Felipe Kenji Sudo
- Departamento de Psicologia, Pontifícia Universidade Católica do Rio de Janeiro, RJ, Brazil
- Instituto D'Or de Ensino e Pesquisa, Rio de Janeiro, RJ, Brazil
| | - Lucas Briand
- Departamento de Medicina Interna, Universidade Federal do Ceará, CE, Brazil
| | - Jerson Laks
- Instituto de Psiquiatria, Universidade Federal do Rio de Janeiro, RJ, Brazil
- Programa de Pós-Graduação em Biomedicina Translacional (BIOTRANS), Unigranrio, Duque de Caxias, RJ, Brazil
| | - Eliasz Engelhardt
- Setor de Neurologia Cognitiva e do Comportamento, Instituto de Neurologia Deolindo Couto (INDC-CDA/IPUB), Rio de Janeiro, RJ, Brazil
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26
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A probabilistic atlas of fiber crossings for variability reduction of anisotropy measures. Brain Struct Funct 2017; 223:635-651. [PMID: 28905121 DOI: 10.1007/s00429-017-1508-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Accepted: 08/31/2017] [Indexed: 12/13/2022]
Abstract
Diffusion imaging enables assessment of human brain white matter (WM) in vivo. WM microstructural integrity is routinely quantified via fractional anisotropy (FA). However, FA is also influenced by the number of differentially oriented fiber populations per voxel. To date, the precise statistical relationship between FA and fiber populations has not been characterized, complicating microstructural integrity assessment. Here, we used 630 state-of-the-art diffusion datasets from the Human Connectome Project, which allowed us to infer the number of fiber populations per voxel in a model-free fashion. Beyond the known impact on mean FA, variance of anisotropy distributions was drastically impacted, not only for FA, but also the more recent anisotropy indices generalized FA and multidimensional anisotropy. To ameliorate this bias, we introduce a probabilistic WM atlas delineating the number of distinctly oriented fiber populations per voxel. Our atlas shows that the majority of WM voxels features two differentially directed fiber populations (44.7%) rather than unidirectional fibers (32.9%) and identified WM regions with high numbers of crossing fibers, referred to as crossing pockets. Compartmentalizing anisotropy drastically reduced variance in group comparisons ranging from the whole brain to a few voxels in a single slice. In summary, we demonstrate a systematic effect of intra-voxel diffusion inhomogeneity on anisotropy. Moreover, we introduce a potential solution: The provided probabilistic WM atlas can easily be used with any given diffusion dataset to enhance the statistical robustness of anisotropy measures and increase their neurobiological utility.
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27
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Hirjak D, Wolf RC, Remmele B, Seidl U, Thomann AK, Kubera KM, Schröder J, Maier-Hein KH, Thomann PA. Hippocampal formation alterations differently contribute to autobiographic memory deficits in mild cognitive impairment and Alzheimer's disease. Hippocampus 2017; 27:702-715. [PMID: 28281317 DOI: 10.1002/hipo.22726] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 02/27/2017] [Accepted: 03/01/2017] [Indexed: 12/17/2022]
Abstract
Autobiographical memory (AM) is part of declarative memory and includes both semantic and episodic aspects. AM deficits are among the major complaints of patients with Alzheimer's disease (AD) even in early or preclinical stages. Previous MRI studies in AD patients have showed that deficits in semantic and episodic AM are associated with hippocampal alterations. However, the question which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits of AM in individuals with mild cognitive impairment (MCI) and AD patients has not been investigated so far. Hundred and seven participants (38 AD patients, 38 MCI individuals and 31 healthy controls [HC]) underwent MRI at 3 Tesla. AM was assessed with a semi-structured interview (E-AGI). FreeSurfer 5.3 was used for hippocampal parcellation. Semantic and episodic AM scores were related to the volume of 5 hippocampal subfields and cortical thickness in the parahippocampal and entorhinal cortex. Both semantic and episodic AM deficits were associated with bilateral hippocampal alterations. These associations referred mainly to CA1, CA2-3, presubiculum, and subiculum atrophy. Episodic, but not semantic AM loss was associated with cortical thickness reduction of the bilateral parahippocampal and enthorinal cortex. In MCI individuals, episodic, but not semantic AM deficits were associated with alterations of the CA1, presubiculum and subiculum. Our findings support the crucial role of CA1, presubiculum, and subiculum in episodic memory. The present results implicate that in MCI individuals, semantic and episodic AM deficits are subserved by distinct neuronal systems.
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Affiliation(s)
- Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
| | - Barbara Remmele
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
| | - Ulrich Seidl
- Department of Psychiatry, Center for Mental Health, Stuttgart, Germany
| | - Anne K Thomann
- Department of Internal Medicine II, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
| | | | - Klaus H Maier-Hein
- Medical Image Computing Group, Division Medical and Biological Informatics, German Cancer Research Center (DKFZ), Germany
| | - Philipp A Thomann
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Germany
- Center for Mental Health, Odenwald District Healthcare Center, Albert-Schweitzer-Straße 10-20, Erbach, 64711, Germany
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28
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Re TJ, Levman J, Lim AR, Righini A, Grant PE, Takahashi E. High-angular resolution diffusion imaging tractography of cerebellar pathways from newborns to young adults. Brain Behav 2017; 7:e00589. [PMID: 28127511 PMCID: PMC5256176 DOI: 10.1002/brb3.589] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Revised: 08/22/2016] [Accepted: 08/23/2016] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION Many neurologic and psychiatric disorders are thought to be due to, or result in, developmental errors in neuronal cerebellar connectivity. In this connectivity analysis, we studied the developmental time-course of cerebellar peduncle pathways in pediatric and young adult subjects. METHODS A cohort of 80 subjects, newborns to young adults, was studied on a 3T MR system with 30 diffusion-weighted measurements with high-angular resolution diffusion imaging (HARDI) tractography. RESULTS Qualitative and quantitative results were analyzed for age-based variation. In subjects of all ages, the superior cerebellar peduncle pathway (SCP) and two distinct subpathways of the middle cerebellar peduncle (MCP), as described in previous ex vivo studies, were identified in vivo with this technique: pathways between the rostral pons and inferior-lateral cerebellum (MCP cog), associated predominantly with higher cognitive function, and pathways between the caudal pons and superior-medial cerebellum (MCP mot), associated predominantly with motor function. DISCUSSION Our findings showed that the inferior cerebellar peduncle pathway (ICP), involved primarily in proprioception and balance appears to have a later onset followed by more rapid development than that exhibited in other tracts. We hope that this study may provide an initial point of reference for future studies of normal and pathologic development of cerebellar connectivity.
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Affiliation(s)
- Thomas J. Re
- Department of RadiologyBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Fetal‐Neonatal Brain Imaging and Developmental Science CenterBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Department of RadiologyUniversity of MilanMilanItaly
| | - Jacob Levman
- Fetal‐Neonatal Brain Imaging and Developmental Science CenterBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Division of Newborn MedicineDepartment of MedicineBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
| | - Ashley R. Lim
- Division of Newborn MedicineDepartment of MedicineBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Department of Behavioral NeuroscienceNortheastern UniversityBostonMAUSA
| | - Andrea Righini
- Department of Pediatric Radiology and NeuroradiologyChildren's Hospital V. BuzziMilanItaly
| | - Patricia Ellen Grant
- Department of RadiologyBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Fetal‐Neonatal Brain Imaging and Developmental Science CenterBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Division of Newborn MedicineDepartment of MedicineBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
| | - Emi Takahashi
- Fetal‐Neonatal Brain Imaging and Developmental Science CenterBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
- Division of Newborn MedicineDepartment of MedicineBoston Children's HospitalHarvard Medical SchoolBostonMAUSA
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29
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Sun Y, Cao W, Ding W, Wang Y, Han X, Zhou Y, Xu Q, Zhang Y, Xu J. Cerebral Blood Flow Alterations as Assessed by 3D ASL in Cognitive Impairment in Patients with Subcortical Vascular Cognitive Impairment: A Marker for Disease Severity. Front Aging Neurosci 2016; 8:211. [PMID: 27630562 PMCID: PMC5005930 DOI: 10.3389/fnagi.2016.00211] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2016] [Accepted: 08/22/2016] [Indexed: 01/14/2023] Open
Abstract
Abnormal reductions in cortical cerebral blood flow (CBF) have been identified in subcortical vascular cognitive impairment (SVCI). However, little is known about the pattern of CBF reduction in relation with the degree of cognitive impairment. CBF measured with three-dimensional (3D) Arterial Spin Labeling (ASL) perfusion magnetic resonance imaging (MRI) helps detect functional changes in subjects with SVCI. We aimed to compare CBF maps in subcortical ischemic vascular disease (SIVD) subjects with and without cognitive impairment and to detect the relationship of the regions of CBF reduction in the brain with the degree of cognitive impairment according to the z-score. A total of 53 subjects with SVCI and 23 matched SIVD subjects without cognitive impairment (controls), underwent a whole-brain 3D ASL MRI in the resting state. Regional CBF (rCBF) was compared voxel wise by using an analysis of variance design in a statistical parametric mapping program, with patient age and sex as covariates. Correlations were calculated between the rCBF value in the whole brain and the z-score in the 53 subjects with SVCI. Compared with the control subjects, SVCI group demonstrated diffuse decreased CBF in the brain. Significant positive correlations were determined in the rCBF values in the left hippocampus, left superior temporal pole gyrus, right superior frontal orbital lobe, right medial frontal orbital lobe, right middle temporal lobe, left thalamus and right insula with the z-scores in SVCI group. The noninvasively quantified resting CBF demonstrated altered CBF distributions in the SVCI brain. The deficit brain perfusions in the temporal and frontal lobe, hippocampus, thalamus and insula was related to the degree of cognitive impairment. Its relationship to cognition indicates the clinical relevance of this functional marker. Thus, our results provide further evidence for the mechanisms underlying the cognitive deficit in patients with SVCI.
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Affiliation(s)
- Yawen Sun
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Wenwei Cao
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Weina Ding
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Yao Wang
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Xu Han
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Qun Xu
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
| | - Yong Zhang
- GE Applied Science Laboratory, GE Healthcare Shanghai, China
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China
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30
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Hilal S, Amin SM, Venketasubramanian N, Niessen WJ, Vrooman H, Wong TY, Chen C, Ikram MK. Subcortical Atrophy in Cognitive Impairment and Dementia. J Alzheimers Dis 2016; 48:813-23. [PMID: 26402115 DOI: 10.3233/jad-150473] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND Cortical atrophy is a key neuroimaging feature of dementia. However, the role of subcortical gray matter reduction in cognitive impairment has not been explored extensively. OBJECTIVES We examined the risk factors of subcortical structures on neuroimaging and their association with cognitive impairment and dementia. METHODS Data from two studies were used: a subsample from the Epidemiology of Dementia in Singapore (EDIS) study of non-demented community-dwelling subjects (n = 550) and a case-control study. Subjects underwent similar neuropsychological tests and brain MRI. Subcortical volumes of accumbens, amygdala, caudate, pallidum, putamen, thalamus, hippocampus, and brainstem were measured. Cognitive impairment no dementia (CIND), dementia and its subtypes, vascular cognitive impairment (VCI), were defined using accepted criteria. Cognitive function was also expressed as both composite and domain-specific Z-scores. RESULTS In the EDIS study, age, female gender, Malay ethnicity, diabetes, lacunar-infarcts, and white matter lesions were the most important risk factors for subcortical atrophy. Moreover, smaller volumes of accumbens, amygdala, caudate, thalamus, and brainstem were significantly associated with lower cognitive composite Z-scores. With respect to clinical outcomes in the case-control study, structures such as the accumbens, caudate, putamen, and hippocampus were associated with both CIND and dementia. Smaller caudate and pallidum volumes were related to VCI whereas amygdalar atrophy was only associated with non-VCI. Furthermore, subcortical atrophy was related to both VCI and non-VCI. CONCLUSION Subcortical gray matter atrophy is not only observed in dementia, but also in the preclinical stages of cognitive impairment. Furthermore, besides VCI, subcortical structures were also related to non-VCI.
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Affiliation(s)
- Saima Hilal
- Memory Ageing and Cognition Centre (MACC), National University Health System, Singapore.,Department of Pharmacology, National University of Singapore, Singapore
| | - Shaik Muhammad Amin
- Memory Ageing and Cognition Centre (MACC), National University Health System, Singapore.,Department of Pharmacology, National University of Singapore, Singapore
| | | | - Wiro J Niessen
- Departments of Radiology & Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.,Faculty of Applied Sciences, Delft University of Technology, The Netherlands
| | - Henri Vrooman
- Departments of Radiology & Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore.,Academic Medicine Research Institute, Duke-NUS Graduate Medical School, Singapore
| | - Christopher Chen
- Memory Ageing and Cognition Centre (MACC), National University Health System, Singapore.,Department of Pharmacology, National University of Singapore, Singapore
| | - Mohammad Kamran Ikram
- Memory Ageing and Cognition Centre (MACC), National University Health System, Singapore.,Department of Pharmacology, National University of Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Center, Singapore.,Academic Medicine Research Institute, Duke-NUS Graduate Medical School, Singapore
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31
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Cohen AH, Wang R, Wilkinson M, MacDonald P, Lim AR, Takahashi E. Development of human white matter fiber pathways: From newborn to adult ages. Int J Dev Neurosci 2016; 50:26-38. [PMID: 26948153 DOI: 10.1016/j.ijdevneu.2016.02.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Revised: 02/01/2016] [Accepted: 02/01/2016] [Indexed: 02/08/2023] Open
Abstract
Major long-range white matter pathways (cingulum, fornix, uncinate fasciculus [UF], inferior fronto-occipital fasciculus [IFOF], inferior longitudinal fasciculus [ILF], thalamocortical [TC], and corpus callosal [CC] pathways) were identified in eighty-three healthy humans ranging from newborn to adult ages. We tracked developmental changes using high-angular resolution diffusion MR tractography. Fractional anisotropy (FA), apparent diffusion coefficient, number, length, and volume were measured in pathways in each subject. Newborns had fewer, and more sparse, pathways than those of the older subjects. FA, number, length, and volume of pathways gradually increased with age and reached a plateau between 3 and 5 years of age. Data were further analyzed by normalizing with mean adult values as well as with each subject's whole brain values. Comparing subjects of 3 years old and under to those over 3 years old, the studied pathways showed differential growth patterns. The CC, bilateral cingulum, bilateral TC, and the left IFOF pathways showed significant growth both in volume and length, while the bilateral fornix, bilateral ILF and bilateral UF showed significant growth only in volume. The TC and CC took similar growth patterns with the whole brain. FA values of the cingulum and IFOF, and the length of ILF showed leftward asymmetry. The fornix, ILF and UF occupied decreased space compared to the whole brain during development with higher FA values, likely corresponding to extensive maturation of the pathways compared to the mean whole brain maturation. We believe that the outcome of this study will provide an important database for future reference.
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Affiliation(s)
- Andrew H Cohen
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Rongpin Wang
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Radiology, Guizhou Provincial People's Hospital, 83 Zhong Shan Dong Lu, Guiyang, Guizhou Province 550002, China; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Molly Wilkinson
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Patrick MacDonald
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Ashley R Lim
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Emi Takahashi
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, USA; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
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32
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Li X, Li D, Li Q, Li Y, Li K, Li S, Han Y. Hippocampal subfield volumetry in patients with subcortical vascular mild cognitive impairment. Sci Rep 2016; 6:20873. [PMID: 26876151 PMCID: PMC4753487 DOI: 10.1038/srep20873] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 01/11/2016] [Indexed: 01/19/2023] Open
Abstract
Memory impairment is a typical characteristic of patients with subcortical vascular mild cognitive impairment (svMCI) or with amnestic mild cognitive impairment (aMCI). The hippocampus, which plays an important role in the consolidation of information from short-term memory to long-term memory, is a heterogeneous structure that consists of several anatomically and functionally distinct subfields. However, whether distinct hippocampal subfields are differentially and selectively affected by svMCI pathology and whether these abnormal changes in hippocampal subfields are different between svMCI and aMCI patients are largely unknown. A total of 26 svMCI patients, 26 aMCI patients and 26 healthy controls matched according to age, gender and years of education were enrolled in this study. We utilized an automated hippocampal subfield segmentation method provided by FreeSurfer to estimate the volume of several hippocampal subfields, including the cornu ammonis (CA) areas, the dentate gyrus (DG), the subiculum and the presubiculum. Compared with controls, the left subiculum and presubiculum and the right CA4/DG displayed significant atrophy in patients with svMCI. Interestingly, we also found significant differences in the volume of the right CA1 between the svMCI and aMCI groups. Taken together, our results reveal region-specific vulnerability of hippocampal subfields to svMCI pathology and identify distinct hippocampal subfield atrophy patterns between svMCI and aMCI patients.
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Affiliation(s)
- Xinwei Li
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science &Medical Engineering, Beihang University, Beijing, 100191, China
| | - Deyu Li
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science &Medical Engineering, Beihang University, Beijing, 100191, China
| | - Qiongling Li
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science &Medical Engineering, Beihang University, Beijing, 100191, China
| | - Yuxia Li
- Department of Neurology, Xuan Wu Hospital, Capital Medical University, Beijing, 100053, China.,Department of Neurology, Tangshan Gongren Hospital, Tangshan, 063000, China
| | - Kuncheng Li
- Department of Radiology, Xuan Wu Hospital, Capital Medical University, Beijing, 100053, China
| | - Shuyu Li
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science &Medical Engineering, Beihang University, Beijing, 100191, China
| | - Ying Han
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China.,Department of Neurology, Xuan Wu Hospital, Capital Medical University, Beijing, 100053, China
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33
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Zhou X, Hu X, Zhang C, Wang H, Zhu X, Xu L, Sun Z, Yu Y. Aberrant Functional Connectivity and Structural Atrophy in Subcortical Vascular Cognitive Impairment: Relationship with Cognitive Impairments. Front Aging Neurosci 2016; 8:14. [PMID: 26869922 PMCID: PMC4736471 DOI: 10.3389/fnagi.2016.00014] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Accepted: 01/15/2016] [Indexed: 11/13/2022] Open
Abstract
Abnormal structures in the cortical and subcortical regions have been identified in subcortical vascular cognition impairment (SVCI). However, little is known about the functional alterations in SVCI, and no study refers to the functional connectivity in the prefrontal and subcortical regions in this context. The medial prefrontal cortex (MPFC) is an important region of the executive network and default mode network, and the subcortical thalamus plays vital roles in mediating or modulating these two networks. To investigate both thalamus- and MPFC-related functional connectivity as well as its relationship with cognition in SVCI, 32 SVCI patients and 23 control individuals were administered neuropsychological assessments. They also underwent structural and functional magnetic resonance imaging scans. Voxel-based morphometry and functional connectivity analysis were performed to detect gray matter (GM) atrophy and to characterize the functional alterations in the thalamus and the MPFC. For structural data, we observed that GM atrophy was distributed in both cortical regions and subcortical areas. For functional data, we observed that the thalamus functional connectivity in SVCI was significantly decreased in several cortical regions [i.e., the orbitofrontal lobe (OFL)], which are mainly involved in executive function and memory function. However, connectivity was increased in several frontal regions (i.e., the inferior frontal gyrus), which may be induced by the compensatory recruitment of the decreased functional connectivity. The MPFC functional connectivity was also decreased in executive- and memory-related regions (i.e., the anterior cingulate cortex) along with a motor region (i.e., the supplementary motor area). In addition, the cognitive performance was closely correlated with functional connectivity between the left thalamus and the left OFL in SVCI. The present study, thus, provides evidence for an association between structural and functional alterations, and sheds light on the underlying neural mechanisms of executive dysfunction in SVCI.
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Affiliation(s)
- Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Xiaopeng Hu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Chao Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Haibao Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Xiaoqun Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Liyan Xu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Zhongwu Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University , Anhui , China
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34
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Ding W, Cao W, Wang Y, Sun Y, Chen X, Zhou Y, Xu Q, Xu J. Altered Functional Connectivity in Patients with Subcortical Vascular Cognitive Impairment--A Resting-State Functional Magnetic Resonance Imaging Study. PLoS One 2015; 10:e0138180. [PMID: 26376180 PMCID: PMC4573963 DOI: 10.1371/journal.pone.0138180] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 08/27/2015] [Indexed: 12/28/2022] Open
Abstract
Recent neuroimaging studies have shown that people with subcortical vascular cognitive impairment (sVCI) have structural and functional abnormalities in the frontal lobe and subcortical brain sites. In this study, we used seed-based resting-state functional connectivity (rsFC) analysis and voxel-mirrored homotopic connectivity (VMHC) techniques to investigate the alteration of rsFC in patients with sVCI. rsFC and structural magnetic resonance images were acquired for 51 patients with subcortical cerebrovascular disease. All patients were subdivided based on cognitive status into 29 with sVCI and 22 controls; patient characteristics were matched. rsFC of the posterior cingulate cortex (PCC) and VMHC were calculated separately, and rsFC of the PCC and VMHC between the two groups were compared. The regions showing abnormal rsFC of the PCC or VMHC in sVCI patients were adopted as regions of interest for correlation analyses. Our results are as follows: The patients with sVCI exhibited increases in rsFC in the left middle temporal lobe, right inferior temporal lobe and left superior frontal gyrus, and significant decreases in rsFC of the left thalamus with the PCC. sVCI patients showed a significant deficit in VMHC between the bilateral lingual gyrus, putamen, and precentral gyrus. Additionally, the z-memory score was significantly positively associated with connectivity between the left thalamus and the PCC (r = 0.41, p = 0.03, uncorrected) in the sVCI group. Our findings suggest that the frontal lobe and subcortical brain sites play an important role in the pathogenesis of sVCI. Furthermore, rsFC between the left thalamus and the PCC might indicate the severity of sVCI.
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Affiliation(s)
- Weina Ding
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
| | - Wenwei Cao
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
| | - Yao Wang
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
| | - Yawen Sun
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
| | - Xue Chen
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
- * E-mail: (YZ); (QZ)
| | - Qun Xu
- Department of Neurology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
- * E-mail: (YZ); (QZ)
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P.R. China
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35
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Suri S, Topiwala A, Mackay CE, Ebmeier KP, Filippini N. Using structural and diffusion magnetic resonance imaging to differentiate the dementias. Curr Neurol Neurosci Rep 2015; 14:475. [PMID: 25030502 DOI: 10.1007/s11910-014-0475-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Dementia is one of the major causes of personal, societal and financial dependence in older people and in today's ageing society there is a pressing need for early and accurate markers of cognitive decline. There are several subtypes of dementia but the four most common are Alzheimer's disease, Lewy body dementia, vascular dementia and frontotemporal dementia. These disorders can only be diagnosed at autopsy, and ante-mortem assessments of "probable dementia (e.g. of Alzheimer type)" are traditionally driven by clinical symptoms of cognitive or behavioural deficits. However, owing to the overlapping nature of symptoms and age of onset, a significant proportion of dementia cases remain incorrectly diagnosed. Misdiagnosis can have an extensive impact, both at the level of the individual, who may not be offered the appropriate treatment, and on a wider scale, by influencing the entry of patients into relevant clinical trials. Magnetic resonance imaging (MRI) may help to improve diagnosis by providing non-invasive and detailed disease-specific markers of cognitive decline. MRI-derived measurements of grey and white matter structural integrity are potential surrogate markers of disease progression, and may also provide valuable diagnostic information. This review summarises the latest evidence on the use of structural and diffusion MRI in differentiating between the four major dementia subtypes.
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Affiliation(s)
- Sana Suri
- Department of Psychiatry, Warneford Hospital, Warneford Lane, University of Oxford, Oxford, OX3 7JX, UK
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36
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Deramecourt V, Pasquier F. Neuronal substrate of cognitive impairment in post-stroke dementia. ACTA ACUST UNITED AC 2014; 137:2404-5. [PMID: 25125586 DOI: 10.1093/brain/awu188] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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37
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Park SY, Yoon H, Lee N, Oh JK, Yoo IR, Kim SH, Chung YA. Analysis of Cerebral Blood Flow with Single Photon Emission Computed Tomography in Mild Subcortical Ischemic Vascular Dementia. Nucl Med Mol Imaging 2014; 48:272-7. [PMID: 26396631 DOI: 10.1007/s13139-014-0287-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Revised: 06/26/2014] [Accepted: 07/02/2014] [Indexed: 11/28/2022] Open
Abstract
PURPOSE The mechanism of cognitive dysfunction of subcortical ischemic vascular dementia (SIVaD) is not yet fully understood. The objective of this study was to investigate and compare the distribution of regional cerebral perfusion (CP) change in the mild forms of SIVaD, a relatively homogeneous subtype of vascular dementia, using statistical parametric mapping (SPM) analysis of the technetium-99m hexamethylproplyeneamineoxime (Tc-99m HMPAO) single photon emission computed tomography (SPECT). MATERIALS AND METHODS A total of 28 patients with mild SIVaD and 33 healthy controls were prospectively recruited and underwent SPECT imaging studies between January 2012 and May 2013. SPECT was performed to measure the regional CP, and SPM was applied to the analysis of the SPECT data. RESULTS The regional CP was significantly decreased in the bilateral insula, anterior and posterior cingulated gyrus, precentral gyrus, and subcallosal gyrus as well as the right inferior parietal lobule in the SIVaD patients compared to the controls (corrected p = 0.01). The pattern of CP abnormality correlated well with those previously reported in later forms of SIVaD. CONCLUSIONS Reduction of CP in the brain areas mentioned was present earlier on in the natural course of SIVaD pathophysiology. Our study suggests that cognitive dysfunction of SIVaD may be related to these regional CP deficits.
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Affiliation(s)
- Sonya Youngju Park
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea ; Department of Nuclear Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea
| | - Hyukjin Yoon
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea
| | - Narae Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea
| | - Jin Kyoung Oh
- Department of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 665 Bupyeong-dong, Bupyeong-gu, 403-720 Incheon, South Korea
| | - Ie Ryung Yoo
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea
| | - Sung Hoon Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seochogu Banpodong 505, 137-701 Seoul, South Korea
| | - Yong An Chung
- Department of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 665 Bupyeong-dong, Bupyeong-gu, 403-720 Incheon, South Korea
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