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Siow I, Narasimhalu K, Lee KS, Tan HK, Ting SKS, Hameed S, Chang HM, De Silva DA, Chen CLH, Tan EK. Predictors of post stroke cognitive impairment: VITATOPS cognition substudy. J Stroke Cerebrovasc Dis 2024; 33:107718. [PMID: 38604352 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 01/31/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024] Open
Abstract
INTRODUCTION Post stroke cognitive impairment (PSCI) is a common complication of ischemic stroke. PSCI can involve different depending on clinical and stroke related characteristics. The aim of this study is to determine the factors associated with impairments in specific cognitive domains. METHODS The Vitamins to Prevent Stroke (VITATOPS) trial is a large, multinational randomised controlled trial. In this substudy, consecutive patients admitted for ischaemic stroke or transient ischaemic attack (TIA) at a tertiary hospital in Singapore were included. PSCI was defined as impairment of any of the six cognitive subgroups - visuoconstruction, attention, verbal memory, language, visual memory and visuomotor function - that were assessed annually for up to five years. Univariate and multivariate Cox proportional hazard models were used to determine factors associated with impairments in each of these cognitive domains. RESULTS A total of 736 patients were included in this study, of which 173 (23.5 %) developed cognitive impairment. Out of the six cognitive domains, the greatest proportion of patients had an impairment in visuoconstruction (26.4 %) followed by attention (19.8 %), verbal memory (18.3 %), language (17.5 %), visual memory (17.3 %) and visuomotor function (14.8 %). Patients with posterior circulation cerebral infarction (POCI) as the index stroke subtype had higher rates of cognitive impairment. Further subgroup analyses show that Indian race and advanced age were predictive of language impairment, whilst fewer years of education and POCI were predictive of verbal memory impairment. POCI was predictive of visual memory impairment, and advanced age and POCI were predictive of visuomotor function impairment. CONCLUSION We identified visuoconstruction and attention domains to be the most affected in our Asian cohort of PSCI. Advanced age, lower levels of education, posterior circulation strokes and concomitant comorbidities such as peripheral artery disease are independent predictors of PSCI.
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Affiliation(s)
- Isabel Siow
- Ministry of Health Holdings Singapore, Singapore
| | - Kaavya Narasimhalu
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore.
| | - Keng Siang Lee
- Department of Neurosurgery, King's College Hospital, London, UK; Department of Basic and Clinical Neurosciences, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
| | | | - Simon Kang Seng Ting
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Shahul Hameed
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Hui Meng Chang
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Deidre Anne De Silva
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
| | - Christopher Li Hsian Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Eng King Tan
- Department of Neurology, National Neuroscience Institute (Singapore General Hospital Campus), Singapore
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Zhang J, Chen H, Wang J, Huang Q, Xu X, Wang W, Xu W, Guan Y, Liu J, Wardlaw JM, Deng Y, Xie F, Li B. Linking white matter hyperintensities to regional cortical thinning, amyloid deposition, and synaptic density loss in Alzheimer's disease. Alzheimers Dement 2024. [PMID: 38648354 DOI: 10.1002/alz.13845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 02/16/2024] [Accepted: 03/21/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION We investigated the association between white matter hyperintensities (WMH) and regional cortical thickness, amyloid and tau deposition, and synaptic density in the WMH-connected cortex using multimodal images. METHODS We included 107 participants (59 with Alzheimer's disease [AD]; 27 with mild cognitive impairment; 21 cognitively normal controls) with amyloid beta (Aβ) positivity on amyloid positron emission tomography (PET). The cortex connected to WMH was identified using probabilistic tractography. RESULTS We found that WMH connected to the cortex with more severe regional degeneration as measured by cortical thickness, Aβ and tau deposition, and synaptic vesicle glycoprotein 2 A (SV2A) density using 18F-SynVesT-1 PET. In addition, higher ratios of Aβ in the deep WMH-connected versus WMH-unconnected cortex were significantly related to lower cognitive scores. Last, the cortical thickness of WMH-connected cortex reduced more than WMH-unconnected cortex over 12 months. DISCUSSION Our results suggest that WMH may be associated with AD-intrinsic processes of degeneration, in addition to vascular mechanisms. HIGHLIGHTS We studied white matter hyperintensities (WMHs) and WMH-connected cortical changes. WMHs are associated with more severe regional cortical degeneration. Findings suggest WMHs may be associated with Alzheimer's disease-intrinsic processes of degeneration.
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Affiliation(s)
- Junfang Zhang
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital LuWan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haijuan Chen
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital LuWan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Wang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qi Huang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaomeng Xu
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenjing Wang
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Xu
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Liu
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Yulei Deng
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital LuWan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fang Xie
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Binyin Li
- Department of Neurology & Institute of Neurology, Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital LuWan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Wang Y, Zhang G, Shen Y, Zhao P, Sun H, Ji Y, Sun L. Relationship between prognostic nutritional index and post-stroke cognitive impairment. Nutr Neurosci 2024:1-11. [PMID: 38564411 DOI: 10.1080/1028415x.2024.2330786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND The Prognostic Nutritional Index (PNI) has been described as a useful screening tool for patient prognosis in several diseases. As a potential diagnostic index, it has attracted the interest of many physicians. However, the correlation between the PNI and post-stroke cognitive impairment (PSCI) remains unclear. METHODS A total of 285 patients with acute ischemic stroke were included. PNI was assessed as serum albumin (g/L) + 5× lymphocyte count (109/L) and was dichotomized according to the prespecified cut-off points 48.43 for the high and low groups. PSCI was defined as Mini-Mental State Examination (MMSE) < 27 at the 6-10 months follow-up. Multiple logistic regression and linear regression analyses were performed to examine the association between PNI and cognitive outcomes. RESULTS A low PNI was independently associated with PSCI after adjusting for age, sex, education, National Institutes of Health Stroke Scale (NIHSS), deep white matter hyperintensity (DWMH), and stroke history (odds ratio [OR]: 2.158; 95% confidence interval [CI]: 1.205-3.863). The PNI scores were significantly associated with MMSE and attention domain (β = 0.113, p = 0.006; β = 0.109, p = 0.041, respectively). The PNI improved the model's discrimination when added to the model with other clinical risk factors. CONCLUSIONS A low PNI was independently associated with the occurrence of PSCI and the PNI scores were specifically associated with the scores of global cognition and attention domain. It can be a promising and straightforward screening indicator to identify the person with impaired immune-nutritional status at higher risk of PSCI.
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Affiliation(s)
- Yongchun Wang
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
- Cognitive Center, Department of Neurology, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Guimei Zhang
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
- Cognitive Center, Department of Neurology, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Yanxin Shen
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
- Cognitive Center, Department of Neurology, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Panpan Zhao
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
- Cognitive Center, Department of Neurology, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Hui Sun
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
| | - Yingshi Ji
- Department of Pharmacology, Physiology and Cell Biology, College of Basic Medical Sciences, Jilin University, People's Republic of China
| | - Li Sun
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
- Cognitive Center, Department of Neurology, The First Hospital of Jilin University, Jilin University, Changchun, People's Republic of China
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Liu R, Berry R, Wang L, Chaudhari K, Winters A, Sun Y, Caballero C, Ampofo H, Shi Y, Thata B, Colon-Perez L, Sumien N, Yang SH. Experimental Ischemic Stroke Induces Secondary Bihemispheric White Matter Degeneration and Long-Term Cognitive Impairment. Transl Stroke Res 2024:10.1007/s12975-024-01241-0. [PMID: 38488999 DOI: 10.1007/s12975-024-01241-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/22/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024]
Abstract
Clinical studies have identified widespread white matter degeneration in ischemic stroke patients. However, contemporary research in stroke has predominately focused on the infarct and periinfarct penumbra regions. The involvement of white matter degeneration after ischemic stroke and its contribution to post-stroke cognitive impairment and dementia (PSCID) has remained less explored in experimental models. In this study, we examined the progression of locomotor and cognitive function up to 4 months after inducing ischemic stroke by middle cerebral artery occlusion in young adult rats. Despite evident ongoing locomotor recovery, long-term cognitive and affective impairments persisted after ischemic stroke, as indicated by Morris water maze, elevated plus maze, and open field performance. At 4 months after stroke, multimodal MRI was conducted to assess white matter degeneration. T2-weighted MRI (T2WI) unveiled bilateral cerebroventricular enlargement after ischemic stroke. Fluid Attenuated Inversion Recovery MRI (FLAIR) revealed white matter hyperintensities in the corpus callosum and fornix across bilateral hemispheres. A positive association between the volume of white matter hyperintensities and total cerebroventricular volume was noted in stroke rats. Further evidence of bilateral white matter degeneration was indicated by the reduction of fractional anisotropy and quantitative anisotropy at bilateral corpus callosum in diffusion-weighted MRI (DWI) analysis. Additionally, microglia and astrocyte activation were identified in the bilateral corpus callosum after stroke. Our study suggests that experimental ischemic stroke induced by MCAO in young rat replicate long-term cognitive impairment and bihemispheric white matter degeneration observed in ischemic stroke patients. This model provides an invaluable tool for unraveling the mechanisms underlying post-stroke secondary white matter degeneration and its contribution to PSCID.
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Affiliation(s)
- Ran Liu
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Raymond Berry
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Linshu Wang
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Kiran Chaudhari
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Ali Winters
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Yuanhong Sun
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Claire Caballero
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Hannah Ampofo
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Yiwei Shi
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Bibek Thata
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Luis Colon-Perez
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Nathalie Sumien
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Shao-Hua Yang
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA.
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Stulberg EL, Sachdev PS, Murray AM, Cramer SC, Sorond FA, Lakshminarayan K, Sabayan B. Post-Stroke Brain Health Monitoring and Optimization: A Narrative Review. J Clin Med 2023; 12:7413. [PMID: 38068464 PMCID: PMC10706919 DOI: 10.3390/jcm12237413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/10/2023] [Accepted: 11/21/2023] [Indexed: 01/22/2024] Open
Abstract
Significant advancements have been made in recent years in the acute treatment and secondary prevention of stroke. However, a large proportion of stroke survivors will go on to have enduring physical, cognitive, and psychological disabilities from suboptimal post-stroke brain health. Impaired brain health following stroke thus warrants increased attention from clinicians and researchers alike. In this narrative review based on an open timeframe search of the PubMed, Scopus, and Web of Science databases, we define post-stroke brain health and appraise the body of research focused on modifiable vascular, lifestyle, and psychosocial factors for optimizing post-stroke brain health. In addition, we make clinical recommendations for the monitoring and management of post-stroke brain health at major post-stroke transition points centered on four key intertwined domains: cognition, psychosocial health, physical functioning, and global vascular health. Finally, we discuss potential future work in the field of post-stroke brain health, including the use of remote monitoring and interventions, neuromodulation, multi-morbidity interventions, enriched environments, and the need to address inequities in post-stroke brain health. As post-stroke brain health is a relatively new, rapidly evolving, and broad clinical and research field, this narrative review aims to identify and summarize the evidence base to help clinicians and researchers tailor their own approach to integrating post-stroke brain health into their practices.
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Affiliation(s)
- Eric L. Stulberg
- Department of Neurology, University of Utah, Salt Lake City, UT 84112, USA;
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, Sydney, NSW 2052, Australia;
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW 2031, Australia
| | - Anne M. Murray
- Berman Center for Outcomes and Clinical Research, Minneapolis, MN 55415, USA;
- Department of Medicine, Geriatrics Division, Hennepin Healthcare Research Institute, Minneapolis, MN 55404, USA
| | - Steven C. Cramer
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA;
- California Rehabilitation Institute, Los Angeles, CA 90067, USA
| | - Farzaneh A. Sorond
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA;
| | - Kamakshi Lakshminarayan
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Behnam Sabayan
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA;
- Department of Neurology, Hennepin Healthcare Research Institute, Minneapolis, MN 55404, USA
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Liu Y, Yuan C, Chen X, Fang X, Hao J, Zhou M, Sun X, Wu M, Wang Z. Association of Plasma Lipids with White Matter Hyperintensities in Patients with Acute Ischemic Stroke. Int J Gen Med 2023; 16:5405-5415. [PMID: 38021054 PMCID: PMC10676100 DOI: 10.2147/ijgm.s440655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 11/13/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose White matter hyperintensities (WMH) are the common marker of cerebral small vessel disease (CSVD). Dyslipidemia plays a notable role in the pathogenesis of CSVD. However, the relationship between dyslipidemia and WMH is poorly elucidated. This study aims to investigate the association between serum lipid fractions and WMH in patients with acute ischemic stroke (AIS). Patients and Methods A total of 901 patients with AIS were included in this study. The burden of WMH, including deep white matter hyperintensities (DWMH), periventricular white matter hyperintensities (PVWMH), and total WMH load, were evaluated on magnetic resonance imaging (MRI) by the Fazekas scale. All the WMH burden were set as dichotomous variables. Serum levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) were collected. The association of serum lipid fractions with WMH burden was analyzed using univariate and multivariate logistic regression models. Results The average age of the participants was 67.6±11.6 years, and 584 cases (64.8%) were male. About 33.5% (n = 302) patients were smoker, and 23.5% (n = 212) patients had a history of alcohol consumption. The proportion of previous diabetes, ischemic cardiomyopathy and hypertension was 39.0% (n = 351), 21.2% (n = 191) and 75.9% (n = 684), respectively. The average of serum HDL-c, TC, TG, LDL-c levels for all participants were 1.26 ± 0.28 mmol/l, 4.54 ± 1.06 mmol/l, 1.67 ± 1.09 mmol/l, 3.08 ± 0.94 mmol/l. There were no statistical associations between HDL-c, TG, TC, LDL-c and each type of WMH burden (P > 0.05) in multivariate logistic regression analysis. Similar findings were found in subgroup analysis based on gender classification. Conclusion Serum lipid levels were not associated with the presence of any type of WMH in patients with AIS.
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Affiliation(s)
- Yongkang Liu
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Cuiping Yuan
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Xiao Chen
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Xiaokun Fang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Jingru Hao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Maodong Zhou
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Xin Sun
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Minghua Wu
- Department of Encephalopathy Center, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, People’s Republic of China
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