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Inform. med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The aim of this study was to develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI and compare models trained on datasets with aneurysm-like differential diagnoses. This retrospective study (2020\u20132023) included 385 anonymized 3D TOF-MRI images from 345 patients (mean age 59\u00a0years, 60% female) at multiple centers plus 113 subjects from the ADAM challenge. Images featured untreated or possible UICA and differential diagnoses. Four distinct training datasets were created, and the nnU-Net framework was used for model development. Performance was assessed on a separate test set using sensitivity and false positive (FP)\/case rate for detection and DICE score and NSD (normalized surface distance, 0.5\u00a0mm threshold) for segmentation. Segmentation performance on the test set was also compared to a second human reader. The four models achieved overall sensitivity between 82 and 85% and an FP\/case rate of 0.20 to 0.31, with no significant differences (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20090.90 and\n                    <jats:italic>p<\/jats:italic>\n                    \u2009=\u20090.16) between them. The primary model showed 85% sensitivity and 0.23 FP\/case rate, outperforming the ADAM-challenge winner (61%) and a nnU-Net trained on ADAM data (51%) in sensitivity (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05). Mean DICE (0.73) and NSD (0.84 for 0.5\u00a0mm threshold) for correctly detected UICA did not significantly differ from human reader performance. Our open-source, nnU-Net-based AI model (available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/zenodo.org\/records\/13386859\" ext-link-type=\"uri\">https:\/\/zenodo.org\/records\/13386859<\/jats:ext-link>\n                    ) demonstrates high sensitivity, low FP rates, and consistent segmentation accuracy for UICA detection and segmentation in 3D TOF-MRI, suggesting its potential to improve clinical diagnosis and monitoring of UICA.\n                  <\/jats:p>","DOI":"10.1007\/s10278-025-01533-3","type":"journal-article","created":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T18:02:20Z","timestamp":1747072940000},"page":"345-354","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI"],"prefix":"10.1007","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3623-2271","authenticated-orcid":false,"given":"Ashraya Kumar","family":"Indrakanti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9921-5698","authenticated-orcid":false,"given":"Jakob","family":"Wasserthal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7820-2778","authenticated-orcid":false,"given":"Martin","family":"Segeroth","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5209-0576","authenticated-orcid":false,"given":"Shan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3495-6253","authenticated-orcid":false,"given":"Andrew Phillip","family":"Nicoli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0945-8379","authenticated-orcid":false,"given":"Victor","family":"Schulze-Zachau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9407-6473","authenticated-orcid":false,"given":"Johanna","family":"Lieb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4584-0623","authenticated-orcid":false,"given":"Joshy","family":"Cyriac","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4275-7936","authenticated-orcid":false,"given":"Michael","family":"Bach","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0016-414X","authenticated-orcid":false,"given":"Marios","family":"Psychogios","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2101-823X","authenticated-orcid":false,"given":"Matthias Anthony","family":"Mutke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"issue":"7","key":"1533_CR1","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/s1474-4422(11)70109-0","volume":"10","author":"MH Vlak","year":"2011","unstructured":"Vlak, M. 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The authors have no relevant financial or non-financial interests to disclose. This retrospective study received an ethics waiver from the local institutional Review Board under project-ID Req-2024\u201300337.The study was exempted by the Ethics Committee because it uses completely anonymized data in a retrospective analysis. Anonymized data is no longer considered personal data, as it cannot be traced back to individual participants. As a result, the study does not pose any risk to the privacy or rights of the participants, and therefore, formal ethical approval was deemed unnecessary by the committee.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}}]}}