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Drenthen GS, Elschot EP, van der Knaap N, Uher D, Voorter PHM, Backes WH, Jansen JFA, van der Thiel MM. Imaging Interstitial Fluid With MRI: A Narrative Review on the Associations of Altered Interstitial Fluid With Vascular and Neurodegenerative Abnormalities. J Magn Reson Imaging 2024; 60:40-53. [PMID: 37823526 DOI: 10.1002/jmri.29056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023] Open
Abstract
Interstitial fluid (ISF) refers to the fluid between the parenchymal cells and along the perivascular spaces (PVS). ISF plays a crucial role in delivering nutrients and clearing waste products from the brain. This narrative review focuses on the use of MRI techniques to measure various ISF characteristics in humans. The complementary value of contrast-enhanced and noncontrast-enhanced techniques is highlighted. While contrast-enhanced MRI methods allow measurement of ISF transport and flow, they lack quantitative assessment of ISF properties. Noninvasive MRI techniques, including multi-b-value diffusion imaging, free-water-imaging, T2-decay imaging, and DTI along the PVS, offer promising alternatives to derive ISF measures, such as ISF volume and diffusivity. The emerging role of these MRI techniques in investigating ISF alterations in neurodegenerative diseases (eg, Alzheimer's disease and Parkinson's disease) and cerebrovascular diseases (eg, cerebral small vessel disease and stroke) is discussed. This review also emphasizes current challenges of ISF imaging, such as the microscopic scale at which ISF has to be measured, and discusses potential focus points for future research to overcome these challenges, for example, the use of high-resolution imaging techniques. Noninvasive MRI methods for measuring ISF characteristics hold significant potential and may have a high clinical impact in understanding the pathophysiology of neurodegenerative and cerebrovascular disorders, as well as in evaluating the efficacy of ISF-targeted therapies in clinical trials. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gerhard S Drenthen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Elles P Elschot
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Noa van der Knaap
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Daniel Uher
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Paulien H M Voorter
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Walter H Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Merel M van der Thiel
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
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Wright AM, Wu YC, Feng L, Wen Q. Diffusion magnetic resonance imaging of cerebrospinal fluid dynamics: Current techniques and future advancements. NMR IN BIOMEDICINE 2024:e5162. [PMID: 38715420 DOI: 10.1002/nbm.5162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 02/20/2024] [Accepted: 03/30/2024] [Indexed: 05/22/2024]
Abstract
Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para-arterial spaces, interstitial spaces, and para-venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion-based imaging, especially when differentiating between tissue- and fluid-related changes or elucidating structural versus functional alterations.
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Affiliation(s)
- Adam M Wright
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Weldon School of Biomedical Engineering Department, Purdue University, West Lafayette, Indiana, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Weldon School of Biomedical Engineering Department, Purdue University, West Lafayette, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, New York, USA
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Weldon School of Biomedical Engineering Department, Purdue University, West Lafayette, Indiana, USA
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Zhao H, Sun M, Zhang Y, Kong W, Fan L, Wang K, Xu Q, Chen B, Dong J, Shi Y, Wang Z, Wang S, Zhuang X, Li Q, Lin F, Yao X, Zhang W, Kong C, Zhang R, Feng D, Zhao X. Connecting the Dots: The Cerebral Lymphatic System as a Bridge Between the Central Nervous System and Peripheral System in Health and Disease. Aging Dis 2024; 15:115-152. [PMID: 37307828 PMCID: PMC10796102 DOI: 10.14336/ad.2023.0516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 05/16/2023] [Indexed: 06/14/2023] Open
Abstract
As a recently discovered waste removal system in the brain, cerebral lymphatic system is thought to play an important role in regulating the homeostasis of the central nervous system. Currently, more and more attention is being focused on the cerebral lymphatic system. Further understanding of the structural and functional characteristics of cerebral lymphatic system is essential to better understand the pathogenesis of diseases and to explore therapeutic approaches. In this review, we summarize the structural components and functional characteristics of cerebral lymphatic system. More importantly, it is closely associated with peripheral system diseases in the gastrointestinal tract, liver, and kidney. However, there is still a gap in the study of the cerebral lymphatic system. However, we believe that it is a critical mediator of the interactions between the central nervous system and the peripheral system.
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Affiliation(s)
- Hongxiang Zhao
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Meiyan Sun
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Yue Zhang
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Wenwen Kong
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Lulu Fan
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Kaifang Wang
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Qing Xu
- Department of Anesthesiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Baiyan Chen
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Jianxin Dong
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Yanan Shi
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Zhengyan Wang
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - ShiQi Wang
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Xiaoli Zhuang
- Department of Anesthesiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
| | - Qi Li
- Department of Anesthesiology, Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
| | - Feihong Lin
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
| | - Xinyu Yao
- Department of Anesthesiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
| | - WenBo Zhang
- Department of Neurosurgery, The Children’s Hospital of Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
| | - Chang Kong
- Department of Anesthesiology and Critical Care Medicine, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China.
| | - Rui Zhang
- Department of Anesthesiology, Affiliated Hospital of Weifang Medical University, Weifang, China.
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
| | - Dayun Feng
- Department of neurosurgery, Tangdu hospital, Fourth Military Medical University, Xi'an, China.
| | - Xiaoyong Zhao
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
- Department of Anesthesiology, Affiliated Hospital of Weifang Medical University, Weifang, China.
- Shandong Provincial Medicine and Health Key Laboratory of Clinical Anesthesia, School of Anesthesiology, Weifang Medical University, Weifang, China.
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Hu Y, Yu H, Lai Y, Liu J, Tan Y, Lei W, Zhang J, Zhou X, Cao Y, Tang Y, Liu D, Zhang J. Longitudinal trajectory of amplitude of low-frequency fluctuation changes in breast cancer patients during neoadjuvant chemotherapy-A preliminary prospective study. Brain Res Bull 2024; 206:110845. [PMID: 38101650 DOI: 10.1016/j.brainresbull.2023.110845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/15/2023] [Accepted: 12/12/2023] [Indexed: 12/17/2023]
Abstract
There is growing evidence that the amplitude of low-frequency fluctuation (ALFF) changes in breast cancer patients after chemotherapy. However, longitudinal changes in ALFF during chemotherapy are unclear. To assess the trajectory of ALFF changes during chemotherapy, 36 breast cancer patients underwent both resting-state functional magnetic resonance imaging and neuropsychological testing at three time points, including before neoadjuvant chemotherapy (NAC) (time point 0, TP0), after one cycle of NAC (before the second cycle of NAC, TP1), and upon completion of NAC (pre-operation, TP2). Healthy controls (HC) received the same assessments at matching time points. We compared the longitudinal changes of ALFF in the NAC and two HC groups. In the NAC group, compared with TP0, ALFF values in the right orbital part of the inferior frontal gyrus, left medial orbital part of the superior frontal gyrus, right insula, left medial part of the superior frontal gyrus, and right middle frontal gyrus declined significantly at TP1 and TP2. Compared with TP1, there were no significant changes in ALFF values at TP2. In the two HC groups, there were no significant changes in ALFF at corresponding intervals. We concluded that for breast cancer patients receiving NAC, ALFF values declined significantly in some brain regions after one cycle of NAC and then remained stable until the completion of NAC, and most of the brain regions with ALFF changes were located in the frontal lobe.
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Affiliation(s)
- Yixin Hu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Hong Yu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Yong Lai
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Jiang Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Yong Tan
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Weiwei Lei
- Department of Intensive Care, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Jing Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Xiaoyu Zhou
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Ying Cao
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Yu Tang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.
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Luo X, Hong H, Li K, Zeng Q, Liu X, Hong L, Li J, Zhang X, Zhong S, Xu X, Chen Y, Zhang M, Huang P. Association Between Small Vessel Disease and Financial Capacity: A Study Based on Cognitively Normal Older Adults. J Alzheimers Dis 2024; 98:897-906. [PMID: 38461505 DOI: 10.3233/jad-231089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background Financial capacity is vital for the elderly, who possess a substantial share of global wealth but are vulnerable to financial fraud. Objective We explored the link between small vessel disease (SVD) and financial capacity in cognitively unimpaired (CU) older adults via both cross-sectional and longitudinal analyses. Methods 414 CU participants underwent MRI and completed the Financial Capacity Instrument-Short Form (FCI-SF). Subsequent longitudinal FCI-SF data were obtained from 104, 240, and 141 participants at one, two, and four years, respectively. SVD imaging markers, encompassing white matter hyperintensities (WMH), cerebral microbleeds (CMB), and lacune were evaluated. We used linear regression analyses to cross-sectionally explore the association between FCI-SF and SVD severity, and linear mixed models to assess how baseline SVD severity impacted longitudinal FCI-SF change. The false discovery rate method was used to adjust multiple comparisons. Results Cross-sectional analysis revealed a significant association between baseline WMH and Bank Statement (BANK, β=-0.194), as well as between lacune number and Financial Conceptual Knowledge (FC, β= -0.171). These associations were stronger in APOE ɛ4 carriers, with β= -0.282 for WMH and BANK, and β= -0.366 for lacune number and FC. Longitudinally, higher baseline SVD total score was associated with severe FCI-SF total score decrease (β= -0.335). Additionally, baseline WMH burden predicted future decreases in Single Checkbook/Register Task (SNG, β= -0.137) and FC (β= -0.052). Notably, the association between baseline WMH and SNG changes was amplified in APOE ɛ4 carriers (β= -0.187). Conclusions Severe SVD was associated with worse FCI-SF and could predict the decline of financial capacity in CU older adults.
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Affiliation(s)
- Xiao Luo
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Department of Clinical Neurosciences, Cambridge Biomedical Campus, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Kaicheng Li
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jixuan Li
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Siyan Zhong
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology,The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Rowsthorn E, Pham W, Nazem-Zadeh MR, Law M, Pase MP, Harding IH. Imaging the neurovascular unit in health and neurodegeneration: a scoping review of interdependencies between MRI measures. Fluids Barriers CNS 2023; 20:97. [PMID: 38129925 PMCID: PMC10734164 DOI: 10.1186/s12987-023-00499-0] [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: 10/03/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
The neurovascular unit (NVU) is a complex structure that facilitates nutrient delivery and metabolic waste clearance, forms the blood-brain barrier (BBB), and supports fluid homeostasis in the brain. The integrity of NVU subcomponents can be measured in vivo using magnetic resonance imaging (MRI), including quantification of enlarged perivascular spaces (ePVS), BBB permeability, cerebral perfusion and extracellular free water. The breakdown of NVU subparts is individually associated with aging, pathology, and cognition. However, how these subcomponents interact as a system, and how interdependencies are impacted by pathology remains unclear. This systematic scoping review identified 26 studies that investigated the inter-relationships between multiple subcomponents of the NVU in nonclinical and neurodegenerative populations using MRI. A further 112 studies investigated associations between the NVU and white matter hyperintensities (WMH). We identify two putative clusters of NVU interdependencies: a 'vascular' cluster comprising BBB permeability, perfusion and basal ganglia ePVS; and a 'fluid' cluster comprising ePVS, free water and WMH. Emerging evidence suggests that subcomponent coupling within these clusters may be differentially related to aging, neurovascular injury or neurodegenerative pathology.
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Affiliation(s)
- Ella Rowsthorn
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3168, Australia
| | - William Pham
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Mohammad-Reza Nazem-Zadeh
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Department of Radiology, Alfred Health, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, VIC, 3168, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3168, Australia
- Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia.
- Monash Biomedical Imaging, Monash University, 762-772 Blackburn Road, Clayton, VIC, 3168, Australia.
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Dobrynina LA, Kremneva EI, Shamtieva KV, Geints AA, Filatov AS, Trubitsyna VV, Bitsieva ET, Byrochkina AA, Akhmetshina YI, Maksimov II, Krotenkova MV. [Disruption of corpus callosum microstructural integrity by diffusion MRI as a predictor of progression of cerebral microangiopathy]. Zh Nevrol Psikhiatr Im S S Korsakova 2023; 123:95-104. [PMID: 37994894 DOI: 10.17116/jnevro202312311195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
OBJECTIVE To assess the microstructural integrity of the corpus callosum in patients with cerebral small vessel disease (cSVD) using signal and biophysical diffusion MRI models and to identify the most sensitive markers of disease progression. MATERIAL AND METHODS Diffusion MRI (3 Tesla) was performed in 166 patients (51.8% women; mean age 60.4±7.6) with cSVD and cognitive impairment of varying severity and in 44 healthy volunteers (65.9% women; mean age 59.6±6.8), followed by calculation of signal (diffusion tensor and diffusion kurtosis) and biophysical (WMTI, NODDI, MC-SMT) models, from which profiles of three corpus callosum segments were constructed. RESULTS The best results were obtained for metrics in the forceps minor and body of the corpus callosum. Among the metrics of the signal models in the forceps minor, fraction anisotropy (FA) and mean diffusion (MD), which characterize the overall loss of microstructural integrity and increase in extra-axonal water, as well as indirect markers of demyelination when considering transverse diffusion parameters (radial diffusion and radial kurtosis), had the larger area under the curve according to the ROC analysis. Among the metrics of the biophysical models in the forceps minor, a larger area under the curve was found in the MC-SMT model for extra-axonal transverse diffusion (ETR), mean diffusion (EMD), and intra-axonal water fraction (INTRA), and in the WMTI model for intra-axonal water fraction (AWF). ETR had high inverse correlations with INTRA and AWF, while INTRA and AWF had high direct intercorrelations. CONCLUSION Metrics of signaling (FA, MD, RD, RK) and biophysical patterns (ETR, EMD, INTRA, AWF) in the forceps minor and the corpus callosum body can be considered as indicators of cSVD progression. They indicate disease progression, mainly by an increase in extra-axonal water with the development of demyelination and tissue degeneration in the corpus callosum.
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Affiliation(s)
| | | | | | - A A Geints
- Lomonosov Moscow State University, Moscow, Russia
| | - A S Filatov
- Research Center of Neurology, Moscow, Russia
| | | | | | | | | | - I I Maksimov
- West Norwegian University of Applied Sciences (HVL), Bergen, Norway
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Heterogeneity of White Matter Hyperintensity and Cognitive Impairment in Patients with Acute Lacunar Stroke. Brain Sci 2022; 12:brainsci12121674. [PMID: 36552134 PMCID: PMC9776102 DOI: 10.3390/brainsci12121674] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/29/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
Background: The severity of white matter hyperintensity (WMH) in patients with acute lacunar stroke (ALS) may be not completely parallel to cognitive impairment. Controversies persist about the effects of WMH on cognitive dysfunction. It is vital to explore whether the association may be affected by certain factors and whether a subsequent subgroup analysis is necessary. The aim of this study was to evaluate the relationship between WMH and cognitive impairment in acute lacunar stroke patients and the possible causal factors. Methods: We continuously enrolled patients with ALS who were hospitalized at the First Affiliated Hospital of Soochow University between October 2017 and June 2022. The cognitive function of all patients was assessed by using the Montreal Cognitive Assessment (MoCA) scale 14 ± 2 days after the onset of AIS, and the results were adjusted to the education level. The MoCA scale was reevaluated at the 6-month (day 182 ± 7) follow-up by outpatient visit or video. Demographic and clinical data were collected. The manifestations of chronic cerebral small-vessel disease (CSVD), including the total Fazekas score and total CSVD burden score, were assessed with an MRI scan. A mismatch refers to an inconsistency between the severity of WMH and cognitive dysfunction. A Type 1 mismatch refers to cognitive impairment with mild WMH (total Fazekas score = 0−1), and a Type 2 mismatch refers to severe WMH (total Fazekas score = 5−6) in patients with normal cognitive function. Results: Among 213 enrolled ALS patients, 66 patients (31.0%) had cognitive dysfunction, and 40 patients (18.8%) had mismatches. Twenty-seven cases (12.7%) were Type 1 mismatched, and seventeen cases (8.0%) were Type 2 mismatched. Age, gender, fibrinogen and cerebral infarction history were independent risk factors for cognitive impairment in ALS patients. Imaging features, including moderate to severe WMH, deep WMH and the total CSVD burden score, were also independently associated with cognitive impairment. The patients in the mismatched group were older, had more severe deep WMH and had a higher occurrence of depression (p < 0.05). The NIHSS score, depression and microbleeds were significantly different between the Type 1 mismatched group and the matched group (p = 0.018, p = 0.012 and p = 0.047). Patients in the Type 2 mismatched group were male (p = 0.04), had a lower level of fibrinogen (p = 0.005), a lower incidence of CMBs (p = 0.003), a lower total CSVD burden score (p = 0.017), more severe paraventricular WMH (p = 0.035) and milder deep WMH (p = 0.026). Conclusions: Our study examined a homogeneous study cohort of recruited patients with symptomatic ALS. We found heterogeneity between WMH and cognitive function in ALS patients. Despite a similar WMH severity, some baseline clinical features and other conventional CSVD imaging characteristics may account for this heterogeneity phenomenon. Our findings provide data for the early diagnosis and prevention of cognitive impairment in ALS patients and suggest that the severity of WMH is not completely parallel to cognitive impairment. The white matter microstructural injury and remote WMH effects may account for the mismatch phenomenon. More attention should be paid to understanding the underlying mechanisms and finding new imaging markers.
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Wang S, Zhang F, Huang P, Hong H, Jiaerken Y, Yu X, Zhang R, Zeng Q, Zhang Y, Kikinis R, Rathi Y, Makris N, Lou M, Pasternak O, Zhang M, O'Donnell LJ. Superficial white matter microstructure affects processing speed in cerebral small vessel disease. Hum Brain Mapp 2022; 43:5310-5325. [PMID: 35822593 PMCID: PMC9812245 DOI: 10.1002/hbm.26004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/10/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.
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Affiliation(s)
- Shuyue Wang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina,Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Peiyu Huang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Hui Hong
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yeerfan Jiaerken
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Xinfeng Yu
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ruiting Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Qingze Zeng
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yao Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ron Kikinis
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nikos Makris
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA,Center for Morphometric AnalysisMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Min Lou
- Department of Neurologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Minming Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
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10
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Barisano G, Lynch KM, Sibilia F, Lan H, Shih NC, Sepehrband F, Choupan J. Imaging perivascular space structure and function using brain MRI. Neuroimage 2022; 257:119329. [PMID: 35609770 PMCID: PMC9233116 DOI: 10.1016/j.neuroimage.2022.119329] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/04/2022] [Accepted: 05/19/2022] [Indexed: 12/03/2022] Open
Abstract
In this article, we provide an overview of current neuroimaging methods for studying perivascular spaces (PVS) in humans using brain MRI. In recent years, an increasing number of studies highlighted the role of PVS in cerebrospinal/interstial fluid circulation and clearance of cerebral waste products and their association with neurological diseases. Novel strategies and techniques have been introduced to improve the quantification of PVS and to investigate their function and morphological features in physiological and pathological conditions. After a brief introduction on the anatomy and physiology of PVS, we examine the latest technological developments to quantitatively analyze the structure and function of PVS in humans with MRI. We describe the applications, advantages, and limitations of these methods, providing guidance and suggestions on the acquisition protocols and analysis techniques that can be applied to study PVS in vivo. Finally, we review the human neuroimaging studies on PVS across the normative lifespan and in the context of neurological disorders.
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Affiliation(s)
- Giuseppe Barisano
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA..
| | - Kirsten M Lynch
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Francesca Sibilia
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Haoyou Lan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA
| | - Nien-Chu Shih
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Farshid Sepehrband
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
| | - Jeiran Choupan
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, USA
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11
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Liu Z, Ma H, Guo ZN, Wang L, Qu Y, Fan L, Liu X, Liu J, Zhu Y, Yang Y. Impaired dynamic cerebral autoregulation is associated with the severity of neuroimaging features of cerebral small vessel disease. CNS Neurosci Ther 2021; 28:298-306. [PMID: 34894087 PMCID: PMC8739047 DOI: 10.1111/cns.13778] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 12/21/2022] Open
Abstract
Aims Cerebral small vessel disease (CSVD) is characterized by functional and structural changes in small vessels. We aimed to elucidate the relationship between dynamic cerebral autoregulation (dCA) and neuroimaging characteristics of CSVD. Methods A case‐control study was performed. Cerebral blood flow velocity (CBFV) of bilateral middle cerebral arteries and spontaneous arterial blood pressure were simultaneously recorded. Transfer function analysis was used to calculate dCA parameters (phase, gain, and the rate of recovery of CBFV [RoRc]). Neuroimaging characteristics of CSVD patients were evaluated, including lacunes, white matter hyperintensities (WMH), cerebral microbleeds (CMBs), perivascular spaces (PVS), and the total CSVD burden. Results Overall, 113 patients and 83 controls were enrolled. Compared with the control group, the phase at low frequency and the RoRc in CSVD patients were lower, and the gain at very low and low frequencies were higher, indicating bilaterally impaired dCA. Total CSVD burden, WMH (total, periventricular and deep), severe PVS, and lobar CMBs were independently correlated with the phase at low frequency. Conclusions Our findings suggested that dCA was compromised in CSVD patients, and some specific neuroimaging characteristics (the total CSVD burden, WMH, severe PVS and lobar CMBs) might indicate more severe dCA impairment in CSVD patients.
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Affiliation(s)
- Zhaojun Liu
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
| | - Hongyin Ma
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
| | - Zhen-Ni Guo
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
| | - Le Wang
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
| | - Yang Qu
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
| | - Lei Fan
- Department of Neurology, The First Hospital of Hebei North University, Zhangjiakou, China
| | - Xingliang Liu
- Department of Neurology, The First Hospital of Hebei North University, Zhangjiakou, China
| | - Jie Liu
- Department of Neurology, The People's Hospital of Lixin County, Haozhou, China
| | - Yuanyuan Zhu
- Department of Neurology, The People's Hospital of Lixin County, Haozhou, China
| | - Yi Yang
- Stroke Center & Clinical Trial and Research Center for Stroke, Department of Neurology, The First Hospital of Jilin University, Changchun, China.,China National Comprehensive Stroke Center, Changchun, China.,Jilin Provincial Key Laboratory of Cerebrovascular Disease, Changchun, China
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