Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy

Kenichi Takeda; Shin-ei Kudo; Yuichi Mori; Masashi Misawa; Toyoki Kudo; Kunihiko Wakamura; Atsushi Katagiri; Toshiyuki Baba; Eiji Hidaka; Fumio Ishida; Haruhiro Inoue; Masahiro Oda; Kensaku Mori

doi:10.1055/s-0043-105486

Endoscopy, Table of Contents

Endoscopy 2017; 49(08): 798-802
DOI: 10.1055/s-0043-105486

Innovations and brief communications

Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy

Kenichi Takeda

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Shin-ei Kudo

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Yuichi Mori

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Masashi Misawa

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Toyoki Kudo

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Kunihiko Wakamura

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Atsushi Katagiri

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Toshiyuki Baba

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Eiji Hidaka

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Fumio Ishida

¹Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan

,

Haruhiro Inoue

²Digestive Disease Center, Showa University Koto Toyosu Hospital, Tokyo, Japan

,

Masahiro Oda

³Graduate School of Information Science, Nagoya University, Nagoya, Japan

,

Kensaku Mori

⁴Information and Communications, Nagoya University, Nagoya, Japan

› Author Affiliations

Abstract

Background and study aims Invasive cancer carries the risk of metastasis, and therefore, the ability to distinguish between invasive cancerous lesions and less-aggressive lesions is important. We evaluated a computer-aided diagnosis system that uses ultra-high (approximately × 400) magnification endocytoscopy (EC-CAD).

Patients and methods We generated an image database from a consecutive series of 5843 endocytoscopy images of 375 lesions. For construction of a diagnostic algorithm, 5543 endocytoscopy images from 238 lesions were randomly extracted from the database for machine learning. We applied the obtained algorithm to 200 endocytoscopy images and calculated test characteristics for the diagnosis of invasive cancer. We defined a high-confidence diagnosis as having a ≥ 90 % probability of being correct.

Results Of the 200 test images, 188 (94.0 %) were assessable with the EC-CAD system. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were 89.4 %, 98.9 %, 94.1 %, 98.8 %, and 90.1 %, respectively. High-confidence diagnosis had a sensitivity, specificity, accuracy, PPV, and NPV of 98.1 %, 100 %, 99.3 %, 100 %, and 98.8 %, respectively.

Conclusion: EC-CAD may be a useful tool in diagnosing invasive colorectal cancer.

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References

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