Effect of CADe on radiologists’ performance in detection of "difficult" polyps in CT colonography

Kenji Suzuki; Masatoshi Hori; Gen Iinuma; Abraham H. Dachman

doi:10.1117/12.2008284

18 March 2013 Effect of CADe on radiologists’ performance in detection of "difficult" polyps in CT colonography

Kenji Suzuki, Masatoshi Hori, Gen Iinuma, Abraham H. Dachman

Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86700U (2013) https://doi.org/10.1117/12.2008284
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

To investigate the actual usefulness of computer-aided detection (CADe) of polyps as a second reader, we conducted a free-response observer performance study with radiologists in the detection of “difficult” polyps in CT colonography (CTC) from a multicenter clinical trial. The “difficult” polyps were defined as the ones that had been “missed” by radiologists in the clinical trial or rated “difficult” in our retrospective review. Our advanced CADe scheme utilizing massive-training artificial neural networks (MTANNs) technology was sensitive and specific to the “difficult” polyps. Four board-certified abdominal radiologists participated in this observer study. They were instructed, first without and then with our CADe, to indicate the location of polyps and their confidence level regarding the presence of polyps. Our database contains 20 patients with 23 polyps including 14 false-negative (FN) and 7 “difficult” polyps and 10 negative patients. With CADe, the average by-polyp sensitivity of radiologists was improved from 53 to 63% at a statistically significant level (P=0.037). Thus, our CADe scheme utilizing the MTANN technology improved the diagnostic performance of radiologists, including expert readers, in the detection of “difficult” polyps in CTC.

Citation Download Citation

Kenji Suzuki, Masatoshi Hori, Gen Iinuma, and Abraham H. Dachman "Effect of CADe on radiologists’ performance in detection of "difficult" polyps in CT colonography", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86700U (18 March 2013); https://doi.org/10.1117/12.2008284

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