@inproceedings{98f635c4c14a43c481ec468d155e59d5,
title = "Effect of computerized decision support on diagnostic accuracy and intra-observer variability in multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography",
abstract = "We have previously developed a computerized decision support system for bladder cancer treatment response assessment (CDSS-T) in CT urography (CTU). In this work, we conducted an observer study to evaluate the diagnostic accuracy and intra-observer variability with and without the CDSS-T system. One hundred fifty-seven pre-and posttreatment lesion pairs were identified in pre-and post-chemotherapy CTU scans of 123 patients. Forty lesion pairs had T0 stage (complete response) after chemotherapy. Multi-disciplinary observers from 4 different institutions participated in reading the lesion pairs, including 5 abdominal radiologists, 4 radiology residents, 5 oncologists, 1 urologist, and 1 medical student. Each observer provided estimates of the T0 likelihood after treatment without and then with the CDSST aid for each lesion. To assess the intra-observer variability, 51 cases were evaluated two times-the original and the repeated evaluation. The average area under the curve (AUC) of 16 observers for estimation of T0 disease after treatment increased from 0.73 without CDSS-T to 0.77 with CDSS-T (p = 0.003). For the evaluation with CDSS-T, the average AUC performance for different institutions was similar. The performance with CDSS-T was improved significantly and the AUC standard deviations were slightly smaller showing potential trend of more accurate and uniform performance with CDSS-T. There was no significant difference between the original and repeated evaluation. This study demonstrated that our CDSS-T system has the potential to improve treatment response assessment of physicians from different specialties and institutions, and reduce the inter-and intra-observer variabilities of the assessments.",
author = "Di Sun and Lubomir Hadjiiski and Rohan Garje and Yousef Zakharia and Lauren Pomerantz and Monika Joshi and Ajjai Alva and Chan, {Heang Ping} and Cohan, {Richard H.} and Caoili, {Elaine M.} and Cha, {Kenny H.} and Galina Kirova-Nedyalkova and Davenport, {Matthew S.} and Shankar, {Prasad R.} and Francis, {Isaac R.} and Kimberly Shampain and Nathaniel Meyer and Daniel Barkmeier and Sean Woolen and Palmbos, {Phillip L.} and Weizer, {Alon Z.} and Samala, {Ravi K.} and Chuan Zhou and Martha Matuszak",
note = "Funding Information: This work is supported by National Institutes of Health Grant number U01CA232931. Publisher Copyright: {\textcopyright} 2022 SPIE.; Medical Imaging 2022: Computer-Aided Diagnosis ; Conference date: 21-03-2022 Through 27-03-2022",
year = "2022",
doi = "10.1117/12.2611179",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Karen Drukker and Iftekharuddin, {Khan M.}",
booktitle = "Medical Imaging 2022",
address = "United States",
}