Ultrafast T2-weighted MR Imaging of the Urinary Bladder using Deep Learning-Accelerated HASTE at 3 Tesla

Ultrafast T2-weighted MR Imaging of the Urinary Bladder using Deep Learning-Accelerated HASTE at 3 Tesla | 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 Ultrafast T2-weighted MR Imaging of the Urinary Bladder using Deep Learning-Accelerated HASTE at 3 Tesla Li Yan, Qinxuan Tan, David Kohnert, Marcel Nickel, Elisabeth Weiland, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4804140/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jul, 2025 Read the published version in BMC Medical Imaging → Version 1 posted 11 You are reading this latest preprint version Abstract Objective This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifacts. Methods 50 patients underwent pelvic T2w imaging at 3 Tesla using the following MR sequences in sagittal orientation without antiperistaltic premedication: T2-TSE (time of acquisition [TA]: 2.03-4.00 min), standard HASTE (TA: 0.65–1.10 min), and DL-HASTE (TA: 0.25–0.47 min), with a slice thickness of 3 mm and a varying number of slices (25–45). Three radiologists evaluated the image quality of the three sequences quantitatively and qualitatively. Results Overall image quality of DL-HASTE (5; [IQR]: 4, 5) was superior to HASTE and T2-TSE (p < .001). DL-HASTE provided the clearest bladder wall delineation, especially in the apical part of the bladder (p < .001). SNR (36.3 ± 6.3) and CNR (50.3 ± 19.7) were the highest on DL-HASTE, followed by T2-TSE (33.1 ± 6.3 and 44.3 ± 21.0, respectively; p < .05) and HASTE (21.7 ± 5.4 and 35.8 ± 17.5, respectively; p < .01). A limitation of DL-HASTE and HASTE was the susceptibility to urine flow artifact within the bladder, which was absent or only minimal on T2-TSE. Diagnostic confidence in assessment of the bladder was highest with the combination of DL-HASTE and T2-TSE (p < .05). Conclusion DL-HASTE allows for ultrafast imaging of the bladder with high image quality and is a promising additional sequence to T2-TSE. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Jul, 2025 Read the published version in BMC Medical Imaging → Version 1 posted Editorial decision: Revision requested 15 Apr, 2025 Reviews received at journal 24 Jan, 2025 Reviewers agreed at journal 16 Jan, 2025 Reviewers agreed at journal 11 Oct, 2024 Reviews received at journal 15 Sep, 2024 Reviewers agreed at journal 19 Aug, 2024 Reviewers invited by journal 06 Aug, 2024 Editor invited by journal 06 Aug, 2024 Editor assigned by journal 06 Aug, 2024 Submission checks completed at journal 06 Aug, 2024 First submitted to journal 25 Jul, 2024 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. 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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-4804140","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":348016937,"identity":"6db0de5f-581e-4002-85c3-620c0e5592eb","order_by":0,"name":"Li Yan","email":"","orcid":"","institution":"Charité - University Medicine Berlin","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Yan","suffix":""},{"id":348016938,"identity":"c26de248-4b69-44d4-ac53-12e317b8984c","order_by":1,"name":"Qinxuan Tan","email":"","orcid":"","institution":"Charité - University Medicine Berlin","correspondingAuthor":false,"prefix":"","firstName":"Qinxuan","middleName":"","lastName":"Tan","suffix":""},{"id":348016939,"identity":"8e4424d3-588e-4e24-9d73-523a5f687016","order_by":2,"name":"David Kohnert","email":"","orcid":"","institution":"Charité - 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Three radiologists evaluated the image quality of the three sequences quantitatively and qualitatively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOverall image quality of DL-HASTE (5; [IQR]: 4, 5) was superior to HASTE and T2-TSE (p\u0026thinsp;\u0026lt;\u0026thinsp;.001). DL-HASTE provided the clearest bladder wall delineation, especially in the apical part of the bladder (p\u0026thinsp;\u0026lt;\u0026thinsp;.001). SNR (36.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3) and CNR (50.3\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7) were the highest on DL-HASTE, followed by T2-TSE (33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3 and 44.3\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;.05) and HASTE (21.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4 and 35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;.01). A limitation of DL-HASTE and HASTE was the susceptibility to urine flow artifact within the bladder, which was absent or only minimal on T2-TSE. Diagnostic confidence in assessment of the bladder was highest with the combination of DL-HASTE and T2-TSE (p\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDL-HASTE allows for ultrafast imaging of the bladder with high image quality and is a promising additional sequence to T2-TSE.\u003c/p\u003e","manuscriptTitle":"Ultrafast T2-weighted MR Imaging of the Urinary Bladder using Deep Learning-Accelerated HASTE at 3 Tesla","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-02 17:41:35","doi":"10.21203/rs.3.rs-4804140/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-15T09:29:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-24T15:48:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73728223272036990555479975313165833772","date":"2025-01-16T07:40:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140733093860438028519227857350526644180","date":"2024-10-11T19:14:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-15T15:11:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116144694137425711627408153162188485863","date":"2024-08-19T23:16:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-06T13:49:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-08-06T09:07:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-06T09:05:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-06T09:05:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Imaging","date":"2024-07-25T20:59:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-imaging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmim","sideBox":"Learn more about [BMC Medical Imaging](http://bmcmedimaging.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmim/default.aspx","title":"BMC Medical Imaging","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"95a198e0-cc71-4539-b12a-ac15b51e749d","owner":[],"postedDate":"September 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T16:00:04+00:00","versionOfRecord":{"articleIdentity":"rs-4804140","link":"https://doi.org/10.1186/s12880-025-01810-1","journal":{"identity":"bmc-medical-imaging","isVorOnly":false,"title":"BMC Medical Imaging"},"publishedOn":"2025-07-15 15:57:15","publishedOnDateReadable":"July 15th, 2025"},"versionCreatedAt":"2024-09-02 17:41:35","video":"","vorDoi":"10.1186/s12880-025-01810-1","vorDoiUrl":"https://doi.org/10.1186/s12880-025-01810-1","workflowStages":[]},"version":"v1","identity":"rs-4804140","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4804140","identity":"rs-4804140","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}