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Sun Y, Han X, Li Z, Qiu Y, Hu Y, Zhang Y, Dai Y, Wei H, Xu Q, Zhou Y. Quantifying neuroinflammation within deep gray matter in small vessel disease using diffusion tensor based free-water imaging: a longitudinal study. Front Aging Neurosci 2024; 16:1361436. [PMID: 39050988 PMCID: PMC11266054 DOI: 10.3389/fnagi.2024.1361436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 06/25/2024] [Indexed: 07/27/2024] Open
Abstract
Purpose Employing free water (FW) imaging, a cutting-edge diffusion MRI technique, we assessed neuroinflammation within deep gray matter (DGM) in small vessel disease (SVD) over 1-2 years. Method One hundred and seventy SVD patients and 21 healthy controls (HCs) underwent MRI scans and neuropsychological evaluations at baseline. These patients were then categorized into two groups: 67 displayed no cognitive impairment (NCI), while 103 exhibited vascular mild cognitive impairment (VaMCI). A follow-up study 1-2 years later included 23 from the NCI group and 28 from the VaMCI group. Calculation of FW values within DGM facilitated both cross-sectional and longitudinal analysis, revealing partial correlations between FW value changes and cognitive function alternations. Results Baseline examinations disclosed significant differences in DGM FW values among the three participant groups. We found increased mean FW values in the left pulvinar (Pul), bilateral lateral nuclei (LN) and bilateral internal medullary lamina of the thalamus in VaMCI participants compared with their NCI counterparts in longitudinal analysis. Notably, negative associations emerged between the FW value changes in the left Pul and the right LN of the thalamus and MoCA score changes in the VaMCI group over 1-2 years. Conclusions These findings support the hypothesis that increased FW value is present at the preclinical stage of SVD and remains persistent during the early course of the disease, potentially acting as the biomarker for the mechanism of underlying cognitive decline in SVD.
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Affiliation(s)
- Yawen Sun
- 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
| | - Zhenghao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yage Qiu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Hu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Yongming Dai
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Xu
- Department of Health Manage Center, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Neurology, 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
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2
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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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3
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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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4
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Nägele FL, Petersen M, Mayer C, Bönstrup M, Schulz R, Gerloff C, Thomalla G, Cheng B. Longitudinal microstructural alterations surrounding subcortical ischemic stroke lesions detected by free-water imaging. Hum Brain Mapp 2024; 45:e26722. [PMID: 38780442 PMCID: PMC11114091 DOI: 10.1002/hbm.26722] [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: 10/29/2023] [Revised: 03/20/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
In this study we explore the spatio-temporal trajectory and clinical relevance of microstructural white matter changes within and beyond subcortical stroke lesions detected by free-water imaging. Twenty-seven patients with subcortical infarct with mean age of 66.73 (SD 11.57) and median initial NIHSS score of 4 (IQR 3-7) received diffusion MRI 3-5 days, 1 month, 3 months, and 12 months after symptom-onset. Extracellular free-water and fractional anisotropy of the tissue (FAT) were averaged within stroke lesions and the surrounding tissue. Linear models showed increased free-water and decreased FAT in the white matter of patients with subcortical stroke (lesion [free-water/FAT, mean relative difference in %, ipsilesional vs. contralesional hemisphere at 3-5 days, 1 month, 3 months, and 12 months after symptom-onset]: +41/-34, +111/-37, +208/-26, +251/-18; perilesional tissue [range in %]: +[5-24]/-[0.2-7], +[2-20]/-[3-16], +[5-43]/-[2-16], +[10-110]/-[2-12]). Microstructural changes were most prominent within the lesion and gradually became less pronounced with increasing distance from the lesion. While free-water elevations continuously increased over time and peaked after 12 months, FAT decreases were most evident 1 month post-stroke, gradually returning to baseline values thereafter. Higher perilesional free-water and higher lesional FAT at baseline were correlated with greater reductions in lesion size (rho = -0.51, p = .03) in unadjusted analyses only, while there were no associations with clinical measures. In summary, we find a characteristic spatio-temporal pattern of extracellular and cellular alterations beyond subcortical stroke lesions, indicating a dynamic parenchymal response to ischemia characterized by vasogenic edema, cellular damage, and white matter atrophy.
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Affiliation(s)
- Felix L. Nägele
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Marvin Petersen
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Carola Mayer
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Marlene Bönstrup
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurologyUniversity of Leipzig Medical CenterLeipzigGermany
| | - Robert Schulz
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Christian Gerloff
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Götz Thomalla
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Bastian Cheng
- Department of NeurologyUniversity Medical Center Hamburg‐EppendorfHamburgGermany
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5
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Parent O, Bussy A, Devenyi GA, Dai A, Costantino M, Tullo S, Salaciak A, Bedford S, Farzin S, Béland ML, Valiquette V, Villeneuve S, Poirier J, Tardif CL, Dadar M, Chakravarty MM. Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging. Brain Commun 2023; 5:fcad279. [PMID: 37953840 PMCID: PMC10636521 DOI: 10.1093/braincomms/fcad279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/05/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.
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Affiliation(s)
- Olivier Parent
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Aurélie Bussy
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Gabriel Allan Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Dai
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Manuela Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Stephanie Tullo
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Salaciak
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Saashi Bedford
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sarah Farzin
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Marie-Lise Béland
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Vanessa Valiquette
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sylvia Villeneuve
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Judes Poirier
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Molecular Neurobiology Unit, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Medicine, McGill University, Montreal, Quebec H4A 3J1, Canada
| | - Christine Lucas Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
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Brown RB, Tozer DJ, Egle M, Tuladhar AM, de Leeuw FE, Markus HS. How often does white matter hyperintensity volume regress in cerebral small vessel disease? Int J Stroke 2023; 18:937-947. [PMID: 36988075 PMCID: PMC10507994 DOI: 10.1177/17474930231169132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/14/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND AND OBJECTIVES It has been suggested that white matter hyperintensity lesions (WMHs), which typically progress over time, can also regress, and that this might be associated with favorable cognitive performance. We determined the prevalence of WMH regression in patients with cerebral small vessel disease (SVD) and examined which demographic, clinical, and radiological markers were associated with this regression. METHODS We used semi-automated lesion marking methods to quantify WMH volume at multiple timepoints in three cohorts with symptomatic SVD; two with moderate-to-severe symptomatic SVD (the SCANS observational cohort and the control arm of the PRESERVE interventional trial) and one with mild-to-moderate SVD (the RUN DMC observational cohort). Mixed-effects ordered logistic regression models were used to test which factors predicted participants to show WMH regression. RESULTS No participants (0/98) in SCANS, 6/42 (14.3%) participants in PRESERVE, and 6/276 (2.2%) in RUN DMC showed WMH regression. On multivariate analysis, only lower WMH volume (OR: 0.36, 95% CI: 0.23-0.56) and better white matter microstructural integrity assessed by fractional anisotropy using diffusion tensor imaging (OR: 1.55, 95% CI: 1.07-2.24) predicted participant classification as regressor versus stable or progressor. DISCUSSION Only a small proportion of participants demonstrated WMH regression across the three cohorts, when a blinded standardized assessment method was used. Subjects who showed regression had less severe imaging markers of disease at baseline. Our results show that lesion regression is uncommon in SVD and unlikely to be a major factor affecting the use of WMH quantification as an outcome for clinical trials.
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Affiliation(s)
- Robin B Brown
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Daniel J Tozer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Marco Egle
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Anil M Tuladhar
- Department of Neurology, Centre for Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Centre for Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Hugh S Markus
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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7
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Kern KC, Zagzoug MS, Gottesman RF, Wright CB, Leigh R. Diffusion tensor free water MRI predicts progression of FLAIR white matter hyperintensities after ischemic stroke. Front Neurol 2023; 14:1172031. [PMID: 37808483 PMCID: PMC10559725 DOI: 10.3389/fneur.2023.1172031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 08/23/2023] [Indexed: 10/10/2023] Open
Abstract
Background The progression of FLAIR white matter hyperintensities (WMHs) on MRI heralds vascular-mediated cognitive decline. Even before FLAIR WMH progression, adjacent normal appearing white matter (NAWM) already demonstrates microstructural deterioration on diffusion tensor imaging (DTI). We hypothesized that elevated DTI free water (FW) would precede FLAIR WMH progression, implicating interstitial fluid accumulation as a key pathological step in the progression of cerebral small vessel disease. Methods Participants at least 3 months after an ischemic stroke or TIA with WMH on MRI underwent serial brain MRIs every 3 months over the subsequent year. For each participant, the WMHs were automatically segmented, serial MRIs were aligned, and a region of WMH penumbra tissue at risk was defined by dilating lesions at any time point and subtracting baseline lesions. Penumbra voxels were classified as either stable or progressing to WMH if they were segmented as new lesions and demonstrated increasing FLAIR intensity over time. Aligned DTI images included FW and FW-corrected fractional anisotropy (FATissue) and mean diffusivity (MDTissue). Logistic regression and area under the receiver-operator characteristic curve (AUC) were used to test whether baseline DTI predicted voxel-wise classification of stable penumbra or progression to WMH while covarying for clinical risk factors. Results In the included participants (n = 26, mean age 71 ± 9 years, 31% female), we detected a median annual voxel-wise WMH growth of 2.9 ± 2.6 ml. Each baseline DTI metric was associated with lesion progression in the penumbra, but FW had the greatest AUC of 0.732 (0.730 - 0.733) for predicting voxel-wise WMH progression pooled across participants. Discussion Baseline increased interstitial fluid, estimated as FW on DTI, predicted the progression of NAWM to WMH over the following year. These results implicate the presence of FW in the pathogenesis of cerebral small vessel disease progression.
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Affiliation(s)
- Kyle C. Kern
- Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Marwah S. Zagzoug
- Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Rebecca F. Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Clinton B. Wright
- Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Richard Leigh
- Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
- Department of Neurology, Johns Hopkins Medicine, Baltimore, MD, United States
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8
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Mayer C, Walther C, Borof K, Nägele FL, Petersen M, Schell M, Gerloff C, Kühn S, Heydecke G, Beikler T, Cheng B, Thomalla G, Aarabi G. Association between periodontal disease and microstructural brain alterations in the Hamburg City Health Study. J Clin Periodontol 2023. [PMID: 37263624 DOI: 10.1111/jcpe.13828] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 04/24/2023] [Accepted: 05/07/2023] [Indexed: 06/03/2023]
Abstract
AIM The aim of the PAROBRAIN study was to examine the association of periodontal health with microstructural white matter integrity and cerebral small vessel disease (CSVD) in the Hamburg City Health Study, a large population-based cohort with dental examination and brain magnetic resonance imaging (MRI). MATERIALS AND METHODS Periodontal health was determined by measuring clinical attachment loss (CAL) and plaque index. Additionally, the decayed/missing/filled teeth (DMFT) index was quantified. 3D-FLAIR and 3D-T1-weighted images were used for white matter hyperintensity (WMH) segmentation. Diffusion-weighted MRI was used to quantify peak width of skeletonized mean diffusivity (PSMD). RESULTS Data from 2030 participants were included in the analysis. Median age was 65 years, with 43% female participants. After adjusting for age and sex, an increase in WMH load was significantly associated with more CAL, higher plaque index and higher DMFT index. PSMD was significantly associated with the plaque index and DMFT. Additional adjustment for education and cardiovascular risk factors revealed a significant association of PSMD with plaque index (p < .001) and DMFT (p < .01), whereas effects of WMH load were attenuated (p > .05). CONCLUSIONS These findings suggest an adverse effect of periodontal health on CSVD and white matter integrity. Further research is necessary to examine whether early treatment of periodontal disease can prevent microstructural brain damage.
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Affiliation(s)
- Carola Mayer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carolin Walther
- Department of Periodontics, Preventive and Restorative Dentistry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Prosthetic Dentistry, Center for Dental and Oral Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katrin Borof
- Department of Periodontics, Preventive and Restorative Dentistry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Felix L Nägele
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Schell
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Simone Kühn
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Guido Heydecke
- Department of Prosthetic Dentistry, Center for Dental and Oral Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thomas Beikler
- Department of Periodontics, Preventive and Restorative Dentistry, 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
| | - Ghazal Aarabi
- Department of Periodontics, Preventive and Restorative Dentistry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Prosthetic Dentistry, Center for Dental and Oral Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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9
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Tian Y, Yao D, Pan Y, Wang M, Meng X, Zhao X, Liu L, Wang Y, Wang Y. Implication of heart rate variability on cerebral small vessel disease: A potential therapeutic target. CNS Neurosci Ther 2023; 29:1379-1391. [PMID: 36786131 PMCID: PMC10068455 DOI: 10.1111/cns.14111] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/19/2022] [Accepted: 01/15/2023] [Indexed: 02/15/2023] Open
Abstract
OBJECTIVE This study aimed to investigate the relationships of heart rate variability (HRV) with the presence, severity, and individual neuroimaging markers of cerebral small vessel disease (CSVD). METHOD A total of 4676 participants from the Third China National Stroke Registry (CNSR-III) study were included in this cross-sectional analysis. CSVD and its markers, including white matter hyperintensity (WMH), lacunes, enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and brain atrophy (BA), were evaluated. Two common HRV parameters, including the square root of the mean of the sum of the squares of differences between adjacent N-N intervals (RMSSD) and the standard deviation of all N-N intervals (SDNN), were used to evaluate the function of the autonomic nervous system (ANS). Binary or ordinal logistic regression analyses were performed to investigate the association between HRV and CSVD. In addition, two-sample mendelian randomization (MR) analyses were performed to investigate the causality of HRV with CSVD. RESULTS RMSSD was significantly associated with total burden of CSVD (Wardlaw's scale, common odds ratio [cOR] 0.80, 95% confidence interval [CI] 0.67-0.96, p = 0.02; Rothwell's scale, cOR 0.75, 95% CI 0.60-0.93, p = 0.008) and the presence of CSVD (Rothwell, OR 0.75, 95% CI 0.60-0.93, p = 0.008). However, no significant associations between SDNN and the presence or total burden of CSVD were observed. Moreover, RMSSD was related to WMH burden (OR 0.80, 95% CI 0.66-0.96, p = 0.02), modified WMH burden (cOR 0.82, 95% CI 0.69-0.97, p = 0.02), and Deep-WMH (OR 0.75, 95% CI 0.62-0.91, p = 0.003), while SDNN was related to Deep-WMH (OR 0.80, 95% CI 0.66-0.96, p = 0.02) and BA (cOR 0.80, 95% CI 0.68-0.95, p = 0.009). Furthermore, adding HRV to the conventional model based on vascualr risk factors enhanced the predictive performance for CSVD, as validated by the integrated discrimination index (p < 0.05). In addition, no causality between HRV and CSVD was observed in two-sample MR analyses. CONCLUSION Decreased HRV may be a potential risk factor of CSVD, implying the possible role of the ANS in the pathogenesis of CSVD.
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Affiliation(s)
- Yu Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Dongxiao Yao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Mengxing Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Liping Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,National Center for Neurological Diseases, Beijing, China
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10
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Maillard P, Hillmer LJ, Lu H, Arfanakis K, Gold BT, Bauer CE, Kramer JH, Staffaroni AM, Stables L, Wang DJ, Seshadri S, Satizabal CL, Beiser A, Habes M, Fornage M, Mosley TH, Rosenberg GA, Singh B, Singh H, Schwab K, Helmer KG, Greenberg SM, DeCarli C, Caprihan A. MRI free water as a biomarker for cognitive performance: Validation in the MarkVCID consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12362. [PMID: 36523847 PMCID: PMC9745638 DOI: 10.1002/dad2.12362] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/11/2022] [Accepted: 08/29/2022] [Indexed: 12/15/2022]
Abstract
Introduction To evaluate the clinical validity of free water (FW), a diffusion tensor imaging-based biomarker kit proposed by the MarkVCID consortium, by investigating the association between mean FW (mFW) and executive function. Methods Baseline mFW was related to a baseline composite measure of executive function (EFC), adjusting for relevant covariates, in three MarkVCID sub-cohorts, and replicated in five, large, independent legacy cohorts. In addition, we tested whether baseline mFW predicted accelerated EFC score decline (mean follow-up time: 1.29 years). Results Higher mFW was found to be associated with lower EFC scores in MarkVCID legacy and sub-cohorts (p-values < 0.05). In addition, higher baseline mFW was associated significantly with accelerated decline in EFC scores (p = 0.0026). Discussion mFW is a sensitive biomarker of cognitive decline, providing a strong clinical rational for its use as a marker of white matter (WM) injury in multi-site observational studies and clinical trials of vascular cognitive impairment and dementia (VCID).
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Affiliation(s)
- Pauline Maillard
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Laura J. Hillmer
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Hanzhang Lu
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterDepartment of Diagnostic Radiology and Nuclear MedicineRush University Medical CenterChicagoIllinoisUSA
| | - Brian T. Gold
- Department of NeuroscienceUniversity of KentuckyLexingtonKentuckyUSA
| | | | - Joel H. Kramer
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Lara Stables
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Danny J.J. Wang
- Laboratory of FMRI Technology (LOFT)Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sudha Seshadri
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Claudia L. Satizabal
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Alexa Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health San AntonioSan AntonioTexasUSA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular MedicineMcGovern Medical SchoolSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
- Human Genetics CenterSchool of Public HealthThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Thomas H. Mosley
- MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Gary A. Rosenberg
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Baljeet Singh
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Herpreet Singh
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Kristin Schwab
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Karl G. Helmer
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | | | - Charles DeCarli
- Department of NeurologyUniversity of CaliforniaDavisCaliforniaUSA
| | - Arvind Caprihan
- The Mind Research NetworkAlbuquerqueNew MexicoAlbuquerqueNew MexicoUSA
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11
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Lan H, Lei X, Xu Z, Chen S, Gong W, Cai Y. New insights in addressing cerebral small vessel disease: Associated with extracellular fluid in white matter. Front Neurosci 2022; 16:1042824. [PMID: 36340793 PMCID: PMC9631816 DOI: 10.3389/fnins.2022.1042824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/04/2022] [Indexed: 11/13/2022] Open
Abstract
Objective To explore the role of extracellular fluid, assessed by diffusion tensor imaging (DTI) metrics of free water (FW), in the white matter of patients with cerebral small vessel disease (CSVD). Materials and methods The baseline clinical and imaging data of 129 patients with CSVD were collected and reviewed. CSVD MR markers, including periventricular white matter hyperintensity (PWMH), deep white matter hyperintensity (DWMH), cerebral microbleed (CMB), enlarged perivascular space (PVS), and lacunar infarction (LI), were identified, and CSVD burden was calculated. According to total CSVD MR marker score, cases were classified as mild, moderate, or severe. The mean FW and fractional anisotropy (FA) values were calculated using DTI images. Results The mean white matter FW was associated with the CSVD MR markers, including PWMH, DWMH, LI and PVS (P < 0.05). Moreover, age, hypertension, diabetes mellitus, and FW value were associated with total CSVD MR marker score (P < 0.05). Ordinal logistic regression analysis revealed that FW and age were independently associated with CSVD burden (P < 0.05). Finally, FW in white matter was associated with FA (r = –0.334, P < 0.001). Conclusion Extracellular fluid changes, assessed by DTI metrics of FW in white matter, were associated with CSVD markers and burden. An increased extracellular fluid volume in the white matter was associated with lower FA.
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Affiliation(s)
- Haiyuan Lan
- Department of Radiology, Lishui Hospital of Traditional Chinese Medicine affiliated Zhejiang Chinese Medical University, Lishui, China
| | - Xinjun Lei
- Department of Radiology, Lishui Hospital of Traditional Chinese Medicine affiliated Zhejiang Chinese Medical University, Lishui, China
| | - Zhihua Xu
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, China
- *Correspondence: Zhihua Xu,
| | - Songkuan Chen
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, China
| | - Wanfeng Gong
- Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, China
| | - Yunqi Cai
- Department of Radiology, Lishui Hospital of Traditional Chinese Medicine affiliated Zhejiang Chinese Medical University, Lishui, China
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