Automated detection of colorectal polyps in photon-counting CT colonography

Janne J. Näppi; Toru Hironaka; Dufan Wu; Stephen R. Yoshida; Rajiv Gupta; Rie Tachibana; Katsuyuki Taguchi; Hiroyuki Yoshida

doi:10.1117/12.2654292

10 April 2023 Automated detection of colorectal polyps in photon-counting CT colonography

Janne J. Näppi, Toru Hironaka, Dufan Wu, Stephen R. Yoshida, Rajiv Gupta, Rie Tachibana, Katsuyuki Taguchi, Hiroyuki Yoshida

Author Affiliations +

Proceedings Volume 12469, Medical Imaging 2023: Imaging Informatics for Healthcare, Research, and Applications; 124690T (2023) https://doi.org/10.1117/12.2654292
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Colorectal cancer (CRC) is the third most common cancer type and the second most common cause of cancer deaths. CT colonography is a nearly ideal safe and accurate method for effective colorectal screening and prevention of CRCs, but the ionizing radiation of CT has been cited as a risk for population screening by CT colonography. Photon-counting CT (PCCT) can be used to address that risk. However, there have been no studies on the performance of automated polyp detection in PCCT colonography. In this preliminary study, we investigated the feasibility of the automated detection of clinically significant polyps from a PCCT colonography dataset. A laxative-free CT colonography examination that was simulated on an anthropomorphic colon phantom was scanned by use of a 16-slice PCCT scanner at 120 kVp and 40 mA. Our previously developed computer-aided detection (CADe) system was used to detect polyps from the PCCT dataset. The polyp detection performance was evaluated by use of 10-fold cross-validation. Our preliminary results show that the CADe system was able to detect the clinically significant polyps ≥6 mm in size from the PCCT colonography dataset at a high accuracy. This indicates that PCCT colonography is indeed a very promising approach for addressing the remaining obstacles of CT colonography in the population screening for CRC.

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Janne J. Näppi, Toru Hironaka, Dufan Wu, Stephen R. Yoshida, Rajiv Gupta, Rie Tachibana, Katsuyuki Taguchi, and Hiroyuki Yoshida "Automated detection of colorectal polyps in photon-counting CT colonography", Proc. SPIE 12469, Medical Imaging 2023: Imaging Informatics for Healthcare, Research, and Applications, 124690T (10 April 2023); https://doi.org/10.1117/12.2654292

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