{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:44:14Z","timestamp":1785545054449,"version":"3.56.0"},"reference-count":26,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Computer-aided diagnostic systems such as S-Detect (Samsung Medison) are increasingly integrated into breast ultrasound workflows. Notwithstanding extensive past evaluation of S-Detect\u2019s diagnostic accuracy, its intrasystem repeatability at the software level with identical static images, a fundamental prerequisite for clinical reliability, has not been systematically investigated.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to evaluate the intrasystem repeatability of the S-Detect computer-aided diagnostic system in classifying breast nodules in identical static ultrasound images.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This retrospective, registered, blinded repeatability study analyzed 398 breast nodules from 261 women (mean age 43.10, SD 12.57 years) who underwent surgery between February 2019 and March 2020 at a single institution. Identical stored static ultrasound images, acquired by a single experienced sonographer on 1 Samsung RS80A ultrasound system, were each analyzed twice using the same S-Detect workstation: immediately after acquisition (S-Detect 1) and again at least 4 weeks later under blinded conditions with manual cursor repositioning (S-Detect 2). Repeatability was assessed using concordance rate and Cohen \u03ba. The diagnostic performance of each run was compared against surgical histopathology.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Of 398 nodules, 156 (39.2%) were initially classified as possibly benign, and 242 (60.8%) were initially classified as possibly malignant. On repeat analysis, 37.4% (149\/398) and 62.6% (249\/398) of the nodules were classified as possibly benign and malignant, respectively. A total of 4.5% (7\/156) of the nodules initially classified as benign were reclassified as malignant, whereas no malignant-to-benign changes occurred. The overall concordance rate was 98.2% (391\/398), with a Cohen \u03ba of 0.95 (95% CI 0.94\u20100.99;\n P<\/jats:italic>\n <.001). Diagnostic performance remained stable across runs (area under the curve=0.913 vs 0.902;\n P<\/jats:italic>\n =0.702).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Under controlled conditions with identical static images, S-Detect showed high intrasystem repeatability, underscoring strong software-level consistency, although its translation to real-world clinical reproducibility requires further validation.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/86278","type":"journal-article","created":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T19:30:07Z","timestamp":1780774207000},"page":"e86278-e86278","source":"Crossref","is-referenced-by-count":0,"title":["Intrasystem Repeatability of S-Detect for Breast Ultrasound Classification With Identical Static Images: Single-Center Retrospective Repeatability 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