Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms

Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms | 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 Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms Chen Peng, Wei He, Jingyang Luan, Tong Yuan, Weiguo Fu, Yun Shi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3518210/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Mar, 2024 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted 8 You are reading this latest preprint version Abstract Background Traditional medical imaging studies and biomechanical researches have limitations in analyzing the long-term evolution process of AAA (Abdominal Aortic Aneurysm, AAA). The HCMT (Homogenized Constrained Mixture Theory, HCMT) allows for quantitative analysis of the changes of the three-dimensional morphology and composition of AAA. However, the accuracy of HCMT still requires further clinical verification. Objective This study aims to establish a patient-specific AAA growth model based on HCMT, simulate the long-term G&R (Growth and Remodeling G&R) process of AAA, and validate the feasibility and accuracy of the method using two additional AAA cases with 5 follow-up data. Methods The media and adventitia of the aorta were modeled as mixtures composed of elastin, collagen fibers, and SMC (smooth muscle cells, SMC). The strain energy function was used to describe the continuously generation and degradation of the mixture during the AAA G&R process. Multiple sets of growth parameters were applied to finite element simulations, and the simulation results were compared with the follow-up data for gradually selecting the optimal growth parameters. Two additional AAA patients with different growth rates were used for validating the method, the optimal growth parameters were obtained using the first two follow-up imaging data, and the growth model was applied to simulate the subsequent four time points. The differences between the simulated diameters and the follow-up diameters of AAA were compared to validate the accuracy of the growth model. Results The growth parameters, especially the stress-mediated substance deposition gain factor K σ i , is highly related to the AAA G&R process. When setting the optimal growth parameters to simulate AAA growth, the proportion of simulation results within the distance of less than 0.5 mm from the follow-up model is above 80%. For the validating cases, during the 5 follow-up processes, the mean difference rates between the simulated diameter and the real-world diameter are within 2.5%, which basically meets the clinical demand for quantitatively predicting the AAA growth in maximum diameters. Conclusion This study simulated the growth process of AAA, and validated the accuracy of this growth model. This method was proved to be used to predict the G&R process of AAA caused by dynamic changes in the mixtures of the AAA vessel wall at a long-term time scale, assisting accurately and quantitatively predicting the multi-dimensional morphological development and mixtures evolution process of AAA in clinic. Abdominal Aortic Aneurysms Growth and Remodeling Homogenized Constrained Mixture Theory Inverse Method Finite Element Simulation Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2024 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted Editorial decision: Revision requested 22 Dec, 2023 Reviews received at journal 20 Nov, 2023 Reviewers agreed at journal 10 Nov, 2023 Reviewers agreed at journal 10 Nov, 2023 Reviewers invited by journal 10 Nov, 2023 Editor assigned by journal 01 Nov, 2023 Submission checks completed at journal 31 Oct, 2023 First submitted to journal 30 Oct, 2023 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-3518210","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":244308695,"identity":"5def2fc0-cf1c-4e00-85bd-f910180315db","order_by":0,"name":"Chen Peng","email":"","orcid":"","institution":"Zhejiang Lab","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Peng","suffix":""},{"id":244308696,"identity":"8c6b02c3-bc9b-4556-b146-ad7bee728774","order_by":1,"name":"Wei He","email":"","orcid":"","institution":"Zhongshan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"He","suffix":""},{"id":244308698,"identity":"52c82e1e-e8a3-4306-b552-4ea8f04a8c7e","order_by":2,"name":"Jingyang Luan","email":"","orcid":"","institution":"Zhongshan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jingyang","middleName":"","lastName":"Luan","suffix":""},{"id":244308700,"identity":"1b52566e-932e-4beb-8009-e150419e8945","order_by":3,"name":"Tong Yuan","email":"","orcid":"","institution":"Zhongshan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tong","middleName":"","lastName":"Yuan","suffix":""},{"id":244308702,"identity":"9126ede4-f2ee-4c93-a12a-76148940b9b7","order_by":4,"name":"Weiguo Fu","email":"","orcid":"","institution":"Zhongshan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weiguo","middleName":"","lastName":"Fu","suffix":""},{"id":244308703,"identity":"12ef0e60-82dd-4152-a4de-97e680f68d67","order_by":5,"name":"Yun Shi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIie2QMYvCMBSAXxHSJaVrxOPyF1ocXA78Kyk3dHJ1jghZXXso+Bccva01q9zcoYNdnG64SU5w8MXe6XGQujrkgySPx/t4Lw/A4XhEmCfN84yHmIACdCQ0yXalf1WoqW9XmieRPwrcVfh8KjuBqtLlLCe7r1P1NPQL6R3XwAcWJaoKo+xHk0z48ZvaU0oTzGwhfrd0ipgpUHo0ZeGhF0iNf8GMp0BEuWWwrFFSEuakR0+ohDUO1qJA2SiCgkCFoIJ9IWhRIlSKxYeOMyZI9/KXspY6UCxeWQdL693nWHOOG2O4saE/ey3qo3rh1sGQDb3F+e/N7PWI9/1fcTgcDsdfzq/TWbcWGe7UAAAAAElFTkSuQmCC","orcid":"","institution":"Zhongshan Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Shi","suffix":""},{"id":244308704,"identity":"8e2c7f9e-b559-4a02-af32-489fc6209b9e","order_by":6,"name":"Shengzhang Wang","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shengzhang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2023-10-31 02:14:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3518210/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3518210/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10237-024-01828-4","type":"published","date":"2024-03-28T15:01:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53869700,"identity":"4b8099d8-a728-4a36-bc09-0f7bed92b9b0","added_by":"auto","created_at":"2024-04-01 15:10:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":851308,"visible":true,"origin":"","legend":"","description":"","filename":"MANUSCRIPT1031.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3518210/v1_covered_b3250394-aa05-48d5-8fca-525c6cd37ace.pdf"},{"id":45648955,"identity":"e5737429-341b-4b85-a604-76f1534c7529","added_by":"auto","created_at":"2023-11-01 12:16:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1356659,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3518210/v1/e5014d525808e8d7729ba905.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biomechanics-and-modeling-in-mechanobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmmb","sideBox":"Learn more about [Biomechanics and Modeling in Mechanobiology](http://link.springer.com/journal/10237)","snPcode":"10237","submissionUrl":"https://submission.nature.com/new-submission/10237/3","title":"Biomechanics and Modeling in Mechanobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Abdominal Aortic Aneurysms, Growth and Remodeling, Homogenized Constrained Mixture Theory, Inverse Method, Finite Element Simulation","lastPublishedDoi":"10.21203/rs.3.rs-3518210/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3518210/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTraditional medical imaging studies and biomechanical researches have limitations in analyzing the long-term evolution process of AAA (Abdominal Aortic Aneurysm, AAA). The HCMT (Homogenized Constrained Mixture Theory, HCMT) allows for quantitative analysis of the changes of the three-dimensional morphology and composition of AAA. However, the accuracy of HCMT still requires further clinical verification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aims to establish a patient-specific AAA growth model based on HCMT, simulate the long-term G\u0026amp;R (Growth and Remodeling G\u0026amp;R) process of AAA, and validate the feasibility and accuracy of the method using two additional AAA cases with 5 follow-up data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe media and adventitia of the aorta were modeled as mixtures composed of elastin, collagen fibers, and SMC (smooth muscle cells, SMC). The strain energy function was used to describe the continuously generation and degradation of the mixture during the AAA G\u0026amp;R process. Multiple sets of growth parameters were applied to finite element simulations, and the simulation results were compared with the follow-up data for gradually selecting the optimal growth parameters. Two additional AAA patients with different growth rates were used for validating the method, the optimal growth parameters were obtained using the first two follow-up imaging data, and the growth model was applied to simulate the subsequent four time points. The differences between the simulated diameters and the follow-up diameters of AAA were compared to validate the accuracy of the growth model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe growth parameters, especially the stress-mediated substance deposition gain factor K\u003csub\u003eσ\u003c/sub\u003e\u003csup\u003ei\u003c/sup\u003e, is highly related to the AAA G\u0026amp;R process. When setting the optimal growth parameters to simulate AAA growth, the proportion of simulation results within the distance of less than 0.5 mm from the follow-up model is above 80%. For the validating cases, during the 5 follow-up processes, the mean difference rates between the simulated diameter and the real-world diameter are within 2.5%, which basically meets the clinical demand for quantitatively predicting the AAA growth in maximum diameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study simulated the growth process of AAA, and validated the accuracy of this growth model. This method was proved to be used to predict the G\u0026amp;R process of AAA caused by dynamic changes in the mixtures of the AAA vessel wall at a long-term time scale, assisting accurately and quantitatively predicting the multi-dimensional morphological development and mixtures evolution process of AAA in clinic.\u003c/p\u003e","manuscriptTitle":"Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-11-01 12:15:58","doi":"10.21203/rs.3.rs-3518210/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-12-22T09:58:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-11-20T19:32:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"707bd7f1-0cbf-4acc-b316-df020439e106","date":"2023-11-10T13:27:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26a8674d-a0b6-4fe6-9db6-a79da6c44613","date":"2023-11-10T09:27:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-11-10T09:24:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-11-01T11:07:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-10-31T06:32:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biomechanics and Modeling in Mechanobiology","date":"2023-10-31T02:05:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biomechanics-and-modeling-in-mechanobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmmb","sideBox":"Learn more about [Biomechanics and Modeling in Mechanobiology](http://link.springer.com/journal/10237)","snPcode":"10237","submissionUrl":"https://submission.nature.com/new-submission/10237/3","title":"Biomechanics and Modeling in Mechanobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fbc1a8af-7ad3-41a9-8f44-1b000ea9ce7a","owner":[],"postedDate":"November 1st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-01T15:06:14+00:00","versionOfRecord":{"articleIdentity":"rs-3518210","link":"https://doi.org/10.1007/s10237-024-01828-4","journal":{"identity":"biomechanics-and-modeling-in-mechanobiology","isVorOnly":false,"title":"Biomechanics and Modeling in Mechanobiology"},"publishedOn":"2024-03-28 15:01:27","publishedOnDateReadable":"March 28th, 2024"},"versionCreatedAt":"2023-11-01 12:15:58","video":"","vorDoi":"10.1007/s10237-024-01828-4","vorDoiUrl":"https://doi.org/10.1007/s10237-024-01828-4","workflowStages":[]},"version":"v1","identity":"rs-3518210","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3518210","identity":"rs-3518210","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}