{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T09:08:18Z","timestamp":1778749698298,"version":"3.51.4"},"reference-count":26,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Radiostereometric analysis (RSA) is the gold standard for measuring implant migration, with CT-RSA increasingly used as an alternative. To evaluate CT-RSA, it is important to assess data that include the surrounding soft tissues, rather than data from simplified phantoms, while also avoiding unnecessary radiation from multiple scans. This study proposes a method for generating multiple follow-up CTs from a single post-operative CT (baseline CT) by simulating stem migration and uses it to assess an AI-based CT-RSA tool. Methods: The method involves extracting the stem implant voxels from the baseline CT, digitally translating them along the x-, y-, and z-axes, and storing the result as new follow-up CTs. The voxel spacing of the baseline CT is used to define the ground-truth translations, which are then compared with the AI-based CT-RSA results using descriptive statistics and Bland\u2013Altman plots. Results: Using 10 patients\u2019 baseline CTs, 780 follow-up CTs were generated. Bland\u2013Altman analysis showed a mean difference of 0.00 mm, largest LoA \u22120.10 to 0.09 mm, and translational precision for zero-migration of 0.026 to 0.049 mm. Conclusions: The proposed method offers a practical alternative to phantom-based models, and the AI-based CT-RSA showed high accuracy and precision for stem translation. The study addresses translational migration only.<\/jats:p>","DOI":"10.3390\/diagnostics16101484","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T07:50:15Z","timestamp":1778745015000},"page":"1484","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Synthetic Implant Migration Generation for Accuracy and Precision Evaluation of AI-Based CT-RSA in Total Hip Arthroplasty"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5863-0748","authenticated-orcid":false,"given":"Hassan","family":"M. Nemati","sequence":"first","affiliation":[{"name":"Ortoma AB, 412 85 Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3169-6971","authenticated-orcid":false,"given":"Albin","family":"Christensson","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Sk\u00e5ne University Hospital, Clinical Sciences, Lund University, 221 84 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Pettersson","sequence":"additional","affiliation":[{"name":"Ortoma AB, 412 85 Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6872-4174","authenticated-orcid":false,"given":"Gunnar","family":"Flivik","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Sk\u00e5ne University Hospital, Clinical Sciences, Lund University, 221 84 Lund, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"491","DOI":"10.3109\/17453678909149328","article-title":"Roentgen stereophotogrammetry: Review of orthopedic applications","volume":"60","year":"1989","journal-title":"Acta Orthop. 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Phys."}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/10\/1484\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T08:12:51Z","timestamp":1778746371000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/10\/1484"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,14]]},"references-count":26,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,5]]}},"alternative-id":["diagnostics16101484"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics16101484","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,14]]}}}