Imaging-Based Prediction Model for TOAST Classification in Acute Ischemic Stroke Using Cerebral Edema Progression Patterns

Imaging-Based Prediction Model for TOAST Classification in Acute Ischemic Stroke Using Cerebral Edema Progression Patterns | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Imaging-Based Prediction Model for TOAST Classification in Acute Ischemic Stroke Using Cerebral Edema Progression Patterns Lingbin Xu, Feng Shi, Peiyu Huang, Ruiting Zhang, Xinfeng Yu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7132920/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The etiology of acute ischemic stroke (AIS) significantly influences therapeutic decision-making, yet rapid TOAST classification in the hyperacute phase remains challenging. The spatiotemporal dynamics of cerebral edema development are associated with TOAST subtypes. Objective This study aimed to construct a predictive model by analyzing early cerebrospinal fluid (CSF) spatiotemporal characteristics in AIS patients, integrating clinical and imaging data, and evaluating its discriminative value for TOAST etiological classification, thereby providing a basis for early precision treatment. Methods A retrospective study was conducted on 271 AIS patients with anterior circulation stroke who underwent baseline CT within 24 hours of onset and follow-up NCCT within 24 hours. Artificial intelligence-based measurements were used to quantify CSF volumes in different regions. Multivariate logistic regression and LASSO were employed to construct clinical, imaging, and integrated models. A linear mixed-effects model was applied to analyze the dynamic progression of CSF changes. Results Patients with cardioembolic stroke exhibited a more rapid reduction in CSF volume and higher baseline net water uptake. The integrated model demonstrated superior discriminative performance (AUC = 0.854, 95% CI: 0.810–0.900) compared to the clinical model (AUC = 0.798) and imaging model (AUC = 0.734). Furthermore, cardioembolic stroke patients showed a faster CSF volume decline within the first 12 hours than non-cardioembolic stroke patients. Conclusion CSF dynamics may serve as an early biomarker for TOAST classification, potentially guiding acute stroke treatment stratification. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7132920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531827278,"identity":"77bebd2e-43f0-4a71-b35b-2ea91a7fb4b7","order_by":0,"name":"Lingbin Xu","email":"","orcid":"","institution":"The Second Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Lingbin","middleName":"","lastName":"Xu","suffix":""},{"id":531827281,"identity":"942fa9e0-0578-47eb-ac29-9911f60ba2a4","order_by":1,"name":"Feng Shi","email":"","orcid":"","institution":"Unite Imaging 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Patterns","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research 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The spatiotemporal dynamics of cerebral edema development are associated with TOAST subtypes.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aimed to construct a predictive model by analyzing early cerebrospinal fluid (CSF) spatiotemporal characteristics in AIS patients, integrating clinical and imaging data, and evaluating its discriminative value for TOAST etiological classification, thereby providing a basis for early precision treatment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective study was conducted on 271 AIS patients with anterior circulation stroke who underwent baseline CT within 24 hours of onset and follow-up NCCT within 24 hours. Artificial intelligence-based measurements were used to quantify CSF volumes in different regions. Multivariate logistic regression and LASSO were employed to construct clinical, imaging, and integrated models. A linear mixed-effects model was applied to analyze the dynamic progression of CSF changes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePatients with cardioembolic stroke exhibited a more rapid reduction in CSF volume and higher baseline net water uptake. The integrated model demonstrated superior discriminative performance (AUC\u0026thinsp;=\u0026thinsp;0.854, 95% CI: 0.810\u0026ndash;0.900) compared to the clinical model (AUC\u0026thinsp;=\u0026thinsp;0.798) and imaging model (AUC\u0026thinsp;=\u0026thinsp;0.734). Furthermore, cardioembolic stroke patients showed a faster CSF volume decline within the first 12 hours than non-cardioembolic stroke patients.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCSF dynamics may serve as an early biomarker for TOAST classification, potentially guiding acute stroke treatment stratification.\u003c/p\u003e","manuscriptTitle":"Imaging-Based Prediction Model for TOAST Classification in Acute Ischemic Stroke Using Cerebral Edema Progression Patterns","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 08:12:50","doi":"10.21203/rs.3.rs-7132920/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f0e707a0-c876-41e7-88f7-8c7737294ac2","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T08:44:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-27 08:12:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7132920","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7132920","identity":"rs-7132920","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}