Journal article
Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study
Tomography (Ann Arbor), Vol.8(2), pp.644-656
03/02/2022
DOI: 10.3390/tomography8020054
PMCID: PMC8938803
PMID: 35314631
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 (
= 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.
Details
- Title: Subtitle
- Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study
- Creators
- Di Sun - University of MichiganLubomir Hadjiiski - University of MichiganAjjai Alva - University of MichiganYousef Zakharia - University of IowaMonika Joshi - Pennsylvania State UniversityHeang-Ping Chan - University of MichiganRohan Garje - University of IowaLauren Pomerantz - Pennsylvania State UniversityDean Elhag - University of IowaRichard H Cohan - University of MichiganElaine M Caoili - University of MichiganWesley T Kerr - University of MichiganKenny H Cha - United States Food and Drug AdministrationGalina Kirova-Nedyalkova - Tokuda HospitalMatthew S Davenport - University of MichiganPrasad R Shankar - University of MichiganIsaac R Francis - University of MichiganKimberly Shampain - University of MichiganNathaniel Meyer - University of MichiganDaniel Barkmeier - University of MichiganSean Woolen - University of MichiganPhillip L Palmbos - University of MichiganAlon Z Weizer - University of MichiganRavi K Samala - University of MichiganChuan Zhou - University of MichiganMartha Matuszak - University of Michigan
- Resource Type
- Journal article
- Publication Details
- Tomography (Ann Arbor), Vol.8(2), pp.644-656
- DOI
- 10.3390/tomography8020054
- PMID
- 35314631
- PMCID
- PMC8938803
- NLM abbreviation
- Tomography
- ISSN
- 2379-1381
- eISSN
- 2379-139X
- Grant note
- R25 NS065723 / NINDS NIH HHS U01 CA232931 / NCI NIH HHS
- Language
- English
- Date published
- 03/02/2022
- Academic Unit
- Hematology, Oncology, and Blood & Marrow Transplantation; Internal Medicine
- Record Identifier
- 9984544951602771
Metrics
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