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      Predictive Model of Dysphagia and Brain Lesion-Symptom Mapping in Acute Ischemic Stroke

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          Abstract

          Background and purpose: Early recognition and management of post-stroke dysphagia (PSD) based on MRI may reduce the incidence of complications. Combining clinical symptoms with applications of MRI, we aimed to identify the risk factors of PSD, develop a prediction scale with high accuracy and map key dysphagia brain areas.

          Methods: A total of 275 acute ischemic stroke patients were enrolled in this study, and 113 (41.1%) patients were diagnosed with PSD. All patients underwent the water-swallowing test (WST) and volume-viscosity swallow test (V-VST) within first 24 h following admission to assess swallowing. Vascular factors were evaluated and MRI brain scans were obtained within 3 days after symptom onset for each participant admitted to the hospital. T-test, chi-squared test and Fisher’s exact test were used to investigate the associations of various patient characteristics with dysphagia, and multivariable logistic regression models were used to construct a prediction scale. Scale accuracy was assessed using receiver operating characteristic (ROC) analysis. We extracted white matter hyperintensities for each patient as potential brain lesions. Voxel-based lesion-symptom mapping (VLSM) was used to identify key brain areas for dysphagia.

          Results: Risk factors related with PSD were older age, history of atrial fibrillation, higher fasting blood glucose, NIH stroke scale, TOAST classification, progressive stroke, middle cerebral artery lesion and anterior cerebral artery lesion. Three variables with most significant associations, including NIH stroke scale, TOAST classification and progressive stroke, combined with age and gender, were used to construct a dysphagia prediction scale with high accuracy (AUC = 0.86). VLSM identified left inferior parietal gyrus as a key brain region for PSD.

          Conclusion: Risk factors of PSD were identified and a predictive model of dysphagia was constructed intelligently and automatically. The left inferior parietal gyrus was identified as a key brain area for dysphagia, which provides a new symptom-based treatment target for early rehabilitation in the future.

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          Most cited references49

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          The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis

          Objectives To review the evidence for an association of white matter hyperintensities with risk of stroke, cognitive decline, dementia, and death. Design Systematic review and meta-analysis. Data sources PubMed from 1966 to 23 November 2009. Study selection Prospective longitudinal studies that used magnetic resonance imaging and assessed the impact of white matter hyperintensities on risk of incident stroke, cognitive decline, dementia, and death, and, for the meta-analysis, studies that provided risk estimates for a categorical measure of white matter hyperintensities, assessing the impact of these lesions on risk of stroke, dementia, and death. Data extraction Population studied, duration of follow-up, method used to measure white matter hyperintensities, definition of the outcome, and measure of the association of white matter hyperintensities with the outcome. Data synthesis 46 longitudinal studies evaluated the association of white matter hyperintensities with risk of stroke (n=12), cognitive decline (n=19), dementia (n=17), and death (n=10). 22 studies could be included in a meta-analysis (nine of stroke, nine of dementia, eight of death). White matter hyperintensities were associated with an increased risk of stroke (hazard ratio 3.3, 95% confidence interval 2.6 to 4.4), dementia (1.9, 1.3 to 2.8), and death (2.0, 1.6 to 2.7). An association of white matter hyperintensities with a faster decline in global cognitive performance, executive function, and processing speed was also suggested. Conclusion White matter hyperintensities predict an increased risk of stroke, dementia, and death. Therefore white matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting. Their discovery should prompt detailed screening for risk factors of stroke and dementia.
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            An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis.

            In Multiple Sclerosis (MS), detection of T2-hyperintense white matter (WM) lesions on magnetic resonance imaging (MRI) has become a crucial criterion for diagnosis and predicting prognosis in early disease. Automated lesion detection is not only desirable with regard to time and cost effectiveness but also constitutes a prerequisite to minimize user bias. Here, we developed and evaluated an algorithm for automated lesion detection requiring a three-dimensional (3D) gradient echo (GRE) T1-weighted and a FLAIR image at 3 Tesla (T). Our tool determines the three tissue classes of gray matter (GM) and WM as well as cerebrospinal fluid (CSF) from the T1-weighted image, and, then, the FLAIR intensity distribution of each tissue class in order to detect outliers, which are interpreted as lesion beliefs. Next, a conservative lesion belief is expanded toward a liberal lesion belief. To this end, neighboring voxels are analyzed and assigned to lesions under certain conditions. This is done iteratively until no further voxels are assigned to lesions. Herein, the likelihood of belonging to WM or GM is weighed against the likelihood of belonging to lesions. We evaluated our algorithm in 53 MS patients with different lesion volumes, in 10 patients with posterior fossa lesions, and 18 control subjects that were all scanned at the same 3T scanner (Achieva, Philips, Netherlands). We found good agreement with lesions determined by manual tracing (R2 values of over 0.93 independent of FLAIR slice thickness up to 6mm). These results require validation with data from other protocols based on a conventional FLAIR sequence and a 3D GRE T1-weighted sequence. Yet, we believe that our tool allows fast and reliable segmentation of FLAIR-hyperintense lesions, which might simplify the quantification of lesions in basic research and even clinical trials. Copyright © 2011 Elsevier Inc. All rights reserved.
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              Voxel-based lesion-symptom mapping.

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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                20 October 2021
                2021
                : 13
                : 753364
                Affiliations
                [1] 1Department of Neurology, First Affiliated Hospital of Soochow University , Suzhou, China
                [2] 2Shanghai Zhiyu Software Technology Co., Ltd. , Shanghai, China
                [3] 3Department of Biostatistics, School of Public Health, Fudan University , Shanghai, China
                [4] 4National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University , Shanghai, China
                [5] 5Key Laboratory of Public Health Safety of Ministry of Education, Fudan University , Shanghai, China
                Author notes

                Edited by: Aurel Popa-Wagner, University of Medicine and Pharmacy of Craiova, Romania

                Reviewed by: Paul Muhle, Universitätsklinikum Münster, Germany; Jiyang Jiang, University of New South Wales, Australia

                *Correspondence: Ye Yao, yyao@ 123456fudan.edu.cn

                These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fnagi.2021.753364
                8564389
                34744695
                c6faeeff-fbb7-4f06-8838-b4ef4383cad1
                Copyright © 2021 Zhang, Tang, Wang, Ding, Zhu, Zhou, Diao, Kong, Cai, Li, Yao and Fang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 August 2021
                : 29 September 2021
                Page count
                Figures: 3, Tables: 2, Equations: 0, References: 49, Pages: 11, Words: 9021
                Categories
                Neuroscience
                Original Research

                Neurosciences
                post-stroke dysphagia,mri,water-swallowing test,volume-viscosity swallow test,voxel-based lesion-symptom mapping

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