Deformation-Aware MR-TRUS Image Translation for Prostate Cancer Brachytherapy

Deformation-Aware MR-TRUS Image Translation for Prostate Cancer Brachytherapy | 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 Article Deformation-Aware MR-TRUS Image Translation for Prostate Cancer Brachytherapy Jun Lian, Yunkui Pang, Xu Chen, Yunzhi Huang, Brenton Lian, Pew-Thian Yap This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7958252/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Transrectal ultrasound (TRUS) is widely used in prostate cancer brachytherapy for real-time imaging and to guide radioactive seed implants. However, its low soft tissue contrast limits precise anatomical localization. In contrast, magnetic resonance imaging (MRI) offers superior soft-tissue contrast but exhibits different structural deformations and nonlinear intensity responses compared to TRUS, preventing its direct use in brachytherapy procedures. To achieve accurate seed localization and soft tissue visualization, it often relies on manual annotations on both images, which are labor-intensive and prone to errors. We propose a region-of-interest (ROI)-guided modality translation framework that synthesizes TRUS images from MRI using structural priors and intensity-aware normalization. By generating synthetic TRUS images that are modality-aligned with real TRUS images, our approach simplifies subsequent deformable registration. The method combines cross-domain image synthesis with anatomical constraints to ensure fidelity in both geometric and intensity representations. Evaluations on multiinstitutional datasets demonstrate significant improvements in synthetic image quality and MR-TRUS alignment. This work advances multimodal medical image translation and supports robust cross-modality signal registration, thereby facilitating image-guided therapies and communication-driven clinical systems. Health sciences/Health care/Medical imaging/Ultrasonography Health sciences/Health care/Medical imaging/Magnetic resonance imaging Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review 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-7958252","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":541192070,"identity":"456534d5-9253-49da-af05-df028f2fb61c","order_by":0,"name":"Jun Lian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACxgYg8cCAgYEfSEtABQ0Ia0kAqpFsIFYLGCSAlB0gVgvzjNwDDAkFdnnG1w4fvMHYdkeegb15mwQ+LYwz8hKADksuNrudlmzB2PbMsIHnWBkBLTkGQC3Midtu55hJMLYdTmCQADKI0FKfuHl2/jeIFvk3RGk5nLhBOocNagsPAS09b0BajifOuJ1mbJFw7rBhG09asQU+LYbtQFs+/KlO7J+d/PDGh7LD8vzshzfewKulgYH9B5yXAMRs+JSDgDwhBaNgFIyCUTAKGAAU2ES71cXgjAAAAABJRU5ErkJggg==","orcid":"","institution":"University of North Carolina at Chapel Hill","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Lian","suffix":""},{"id":541192071,"identity":"74ec3186-d804-4feb-8a3a-9716a17061da","order_by":1,"name":"Yunkui Pang","email":"","orcid":"https://orcid.org/0000-0003-2798-337X","institution":"University of North Carolina at Chapel Hill","correspondingAuthor":false,"prefix":"","firstName":"Yunkui","middleName":"","lastName":"Pang","suffix":""},{"id":541192072,"identity":"540a8c1f-6d36-4ed3-85c0-962428950f63","order_by":2,"name":"Xu Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xu","middleName":"","lastName":"Chen","suffix":""},{"id":541192073,"identity":"bff727a7-b2cc-4ee1-958c-29f0f1022d02","order_by":3,"name":"Yunzhi Huang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yunzhi","middleName":"","lastName":"Huang","suffix":""},{"id":541192074,"identity":"5b37d999-5f48-4346-8287-9e36a3d49bed","order_by":4,"name":"Brenton Lian","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Brenton","middleName":"","lastName":"Lian","suffix":""},{"id":541192075,"identity":"3a905548-c3c0-45f5-b618-9af7d47b59c0","order_by":5,"name":"Pew-Thian Yap","email":"","orcid":"https://orcid.org/0000-0003-1489-2102","institution":"The University of North Carolina at Chapel Hill","correspondingAuthor":false,"prefix":"","firstName":"Pew-Thian","middleName":"","lastName":"Yap","suffix":""}],"badges":[],"createdAt":"2025-10-27 12:31:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7958252/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7958252/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96214312,"identity":"5443f53b-95a2-493f-a543-c4080f3f108d","added_by":"auto","created_at":"2025-11-18 19:42:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15778861,"visible":true,"origin":"","legend":"","description":"","filename":"USMRcommunicationsengineering.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7958252/v1/aab0a2613e5bb5879340517b.pdf"},{"id":96214311,"identity":"0606b12f-7fcf-458a-847b-dde5badc880a","added_by":"auto","created_at":"2025-11-18 19:42:17","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":7466,"visible":true,"origin":"","legend":"","description":"","filename":"COMMSENG250816.json","url":"https://assets-eu.researchsquare.com/files/rs-7958252/v1/fec3af910cf61573c8f7496b.json"},{"id":96253369,"identity":"b593f8ac-dfbf-4f2d-9413-9a7a0cd78c58","added_by":"auto","created_at":"2025-11-19 07:42:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2433353,"visible":true,"origin":"","legend":"Article File","description":"","filename":"USMRcommunicationsengineering.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7958252/v1_covered_f51a1523-8da9-4280-8d9d-bda7a833bb6a.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Deformation-Aware MR-TRUS Image Translation for Prostate Cancer Brachytherapy","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7958252/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7958252/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Transrectal ultrasound (TRUS) is widely used in prostate cancer brachytherapy for real-time imaging and to guide radioactive seed implants. However, its low soft tissue contrast limits precise anatomical localization. In contrast, magnetic resonance imaging (MRI) offers superior soft-tissue contrast but exhibits different structural deformations and nonlinear intensity responses compared to TRUS, preventing its direct use in brachytherapy procedures. To achieve accurate seed localization and soft tissue visualization, it often relies on manual annotations on both images, which are labor-intensive and prone to errors. We propose a region-of-interest (ROI)-guided modality translation framework that synthesizes TRUS images from MRI using structural priors and intensity-aware normalization. By generating synthetic TRUS images that are modality-aligned with real TRUS images, our approach simplifies subsequent deformable registration. The method combines cross-domain image synthesis with anatomical constraints to ensure fidelity in both geometric and intensity representations. Evaluations on multiinstitutional datasets demonstrate significant improvements in synthetic image quality and MR-TRUS alignment. This work advances multimodal medical image translation and supports robust cross-modality signal registration, thereby facilitating image-guided therapies and communication-driven clinical systems.","manuscriptTitle":"Deformation-Aware MR-TRUS Image Translation for Prostate Cancer Brachytherapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-18 19:42:12","doi":"10.21203/rs.3.rs-7958252/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-engineering","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commseng","sideBox":"Learn more about [Communications Engineering](http://link.springer.com/journal/44172)","snPcode":"44172","submissionUrl":"https://mts-commseng.nature.com/cgi-bin/main.plex","title":"Communications Engineering","twitterHandle":"@commseng","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"948adefb-1c19-458c-9d7f-fb9226bca978","owner":[],"postedDate":"November 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":57576781,"name":"Health sciences/Health care/Medical imaging/Ultrasonography"},{"id":57576782,"name":"Health sciences/Health care/Medical imaging/Magnetic resonance imaging"}],"tags":[],"updatedAt":"2026-05-05T18:45:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-18 19:42:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7958252","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7958252","identity":"rs-7958252","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}