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- Title
Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study.
- Authors
Sun, Di; Hadjiiski, Lubomir; Alva, Ajjai; Zakharia, Yousef; Joshi, Monika; Chan, Heang-Ping; Garje, Rohan; Pomerantz, Lauren; Elhag, Dean; Cohan, Richard H.; Caoili, Elaine M.; Kerr, Wesley T.; Cha, Kenny H.; Kirova-Nedyalkova, Galina; Davenport, Matthew S.; Shankar, Prasad R.; Francis, Isaac R.; Shampain, Kimberly; Meyer, Nathaniel; Barkmeier, Daniel
- Abstract
This observer study investigates the effect of computerized artificial intelligence (AI)-based decision support system (CDSS-T) on physicians' diagnostic accuracy in assessing bladder cancer treatment response. The performance of 17 observers was evaluated when assessing bladder cancer treatment response without and with CDSS-T using pre- and post-chemotherapy CTU scans in 123 patients having 157 pre- and post-treatment cancer pairs. The impact of cancer case difficulty, observers' clinical experience, institution affiliation, specialty, and the assessment times on the observers' diagnostic performance with and without using CDSS-T were analyzed. It was found that the average performance of the 17 observers was significantly improved (p = 0.002) when aided by the CDSS-T. The cancer case difficulty, institution affiliation, specialty, and the assessment times influenced the observers' performance without CDSS-T. The AI-based decision support system has the potential to improve the diagnostic accuracy in assessing bladder cancer treatment response and result in more consistent performance among all physicians.
- Subjects
BLADDER cancer; DECISION support systems; CANCER treatment; ARTIFICIAL intelligence; COMPUTER-aided diagnosis; ARTIFICIAL sphincters
- Publication
Tomography: A Journal for Imaging Research, 2022, Vol 8, Issue 2, p644
- ISSN
2379-1381
- Publication type
Article
- DOI
10.3390/tomography8020054