Biomechanical Prediction of Middle Cerebral artery Aneurysm Rupture Location using CFD Modelling and HOLMES Index

Biomechanical Prediction of Middle Cerebral artery Aneurysm Rupture Location using CFD Modelling and HOLMES Index | 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 Biomechanical Prediction of Middle Cerebral artery Aneurysm Rupture Location using CFD Modelling and HOLMES Index Nadia Shaira Shafii, Ryuhei Yamaguchi, Kahar Osman, Ahmad Zahran, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8945070/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 The growing fatality rate of intracranial aneurysm (IA) have driven the research trend towards aneurysm rupture risk. Rupture of the middle cerebral artery (MCA) aneurysm is one of the most severe cases of intracranial aneurysms. Predicting aneurysm rupture frequently requires medical knowledge and proficiency for early treatment decisions. In many cases, an aneurysm which is a bulging artery can cause sudden death or paralyzed for a lifetime once ruptured. Sudden rupture is unforeseen due to the difficulty and challenges in accurately anticipating each patient's risk of aneurysm rupture. Hence, there is a need to establish a predictive technique to measure the aneurysm severity, the potential rupture location, and rupture risk according to the aneurysm morphologies and the patient’s blood pressure condition. Thus, this thesis proposed a correlation of biomechanical parameters that relates to the conditions explained. The patient-specific images of MCAs with aneurysms were remodeled with varied aspect ratio (AR) sizes in different blood pressure conditions and were numerically investigated. The hemodynamic and structural effects of healthy MCAs and MCAs with aneurysms were analyzed using computational fluid dynamic (CFD) using ANSYS software. Experimental validation using particle image velocimetry (PIV) analysis was also performed. The HOLMES index was evaluated across MCA aneurysm models with varying AR. Results show that high HOLMES regions expand significantly with increasing AR and blood pressure. The percentage of area exposed to high HOLMES increased approximately fourfold from low-AR normotensive to high-AR hypertensive cases, indicating a strong synergistic effect between morphology and hemodynamic loading. Validation using a clinical MCA case (AR = 0.917) based on Park et al. demonstrated good agreement between predicted and reported rupture locations, supporting HOLMES as a reliable rupture-location estimation tool. Middle Cerebral Artery (MCA) Aneurysm Rupture Risk Computational Fluid Dynamics (CFD) Fluid-Structure Interaction (FSI) Particle Image Velocimetry (PIV) HOLMES 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-8945070","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595499172,"identity":"46e9f408-a8a4-4636-83a6-2272ffa143e2","order_by":0,"name":"Nadia Shaira Shafii","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYHACgwMMDAcY2BgYGB+QrIXZgCGBSC0MIC1AwCZBlBZz9sMbD/z4c0eeT/rws2reH9sYdGcQ0GfZk1ZwsLftmWEbX5rZbZ6E2wxmNwhoMTiQY3CAt+EwYxsPA7Fazr8xOPjnz2H7Nh72b8XEabmRY3CYh+1wYhsPjxkzkVqeFRyWbTucDNRSLDkn7TaP2ZkHhByWvPnjmz+Hbef3sG/88MbmtpzZcQK2YAAeBgFStTAw8B8gWcsoGAWjYBQMbwAAc7lLN35KnDAAAAAASUVORK5CYII=","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Nadia","middleName":"Shaira","lastName":"Shafii","suffix":""},{"id":595499173,"identity":"5a473fb1-6aa4-45ee-a562-0c2a0e55e582","order_by":1,"name":"Ryuhei Yamaguchi","email":"","orcid":"","institution":"Tohoku University","correspondingAuthor":false,"prefix":"","firstName":"Ryuhei","middleName":"","lastName":"Yamaguchi","suffix":""},{"id":595499174,"identity":"e99d5994-5807-4ac0-a12c-6135be6334ed","order_by":2,"name":"Kahar Osman","email":"","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Kahar","middleName":"","lastName":"Osman","suffix":""},{"id":595499175,"identity":"e66b5a33-f3f9-4d01-a58c-1415aa17a658","order_by":3,"name":"Ahmad Zahran","email":"","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Zahran","suffix":""},{"id":595499176,"identity":"2dd93aaf-8238-42bb-b3fd-d786cbfd06e6","order_by":4,"name":"Makoto Ohta","email":"","orcid":"","institution":"Tohoku University","correspondingAuthor":false,"prefix":"","firstName":"Makoto","middleName":"","lastName":"Ohta","suffix":""}],"badges":[],"createdAt":"2026-02-23 09:09:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8945070/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8945070/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109386696,"identity":"9cffbb0f-e82d-4d2b-80a5-855b4736756d","added_by":"auto","created_at":"2026-05-16 23:08:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1386677,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptJournalBiomechanicsandModellinginMechanobiology.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8945070/v1_covered_23dce61d-6bb0-4af6-b990-d6d42045bfa8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biomechanical Prediction of Middle Cerebral artery Aneurysm Rupture Location using CFD Modelling and HOLMES Index","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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 Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Middle Cerebral Artery (MCA), Aneurysm Rupture Risk, Computational Fluid Dynamics (CFD), Fluid-Structure Interaction (FSI), Particle Image Velocimetry (PIV), HOLMES","lastPublishedDoi":"10.21203/rs.3.rs-8945070/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8945070/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe growing fatality rate of intracranial aneurysm (IA) have driven the research trend towards aneurysm rupture risk. Rupture of the middle cerebral artery (MCA) aneurysm is one of the most severe cases of intracranial aneurysms. Predicting aneurysm rupture frequently requires medical knowledge and proficiency for early treatment decisions. In many cases, an aneurysm which is a bulging artery can cause sudden death or paralyzed for a lifetime once ruptured. Sudden rupture is unforeseen due to the difficulty and challenges in accurately anticipating each patient's risk of aneurysm rupture. Hence, there is a need to establish a predictive technique to measure the aneurysm severity, the potential rupture location, and rupture risk according to the aneurysm morphologies and the patient\u0026rsquo;s blood pressure condition. Thus, this thesis proposed a correlation of biomechanical parameters that relates to the conditions explained. The patient-specific images of MCAs with aneurysms were remodeled with varied aspect ratio (AR) sizes in different blood pressure conditions and were numerically investigated. The hemodynamic and structural effects of healthy MCAs and MCAs with aneurysms were analyzed using computational fluid dynamic (CFD) using ANSYS software. Experimental validation using particle image velocimetry (PIV) analysis was also performed. The HOLMES index was evaluated across MCA aneurysm models with varying AR. Results show that high HOLMES regions expand significantly with increasing AR and blood pressure. The percentage of area exposed to high HOLMES increased approximately fourfold from low-AR normotensive to high-AR hypertensive cases, indicating a strong synergistic effect between morphology and hemodynamic loading. Validation using a clinical MCA case (AR\u0026thinsp;=\u0026thinsp;0.917) based on Park et al. demonstrated good agreement between predicted and reported rupture locations, supporting HOLMES as a reliable rupture-location estimation tool.\u003c/p\u003e","manuscriptTitle":"Biomechanical Prediction of Middle Cerebral artery Aneurysm Rupture Location using CFD Modelling and HOLMES Index","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 10:52:32","doi":"10.21203/rs.3.rs-8945070/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":"fde6b3d7-a1cd-411e-aa25-65a40704b2dd","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-16T22:53:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-16T16:56:02+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T23:08:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 10:52:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8945070","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8945070","identity":"rs-8945070","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}