Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis

Gastroenterology

Volumn 154, Issue 3, 2018, Pages 568-575

  Chen, Peng Jen ^a   Lin, Meng Chiung ^b,c   Lai, Mei Ju ^a   Lin, Jung Chun ^a   Lu, Henry Horng Shing ^b   Tseng, Vincent S ^b  

^a TRI SERVICE GENERAL HOSPITAL   (Taiwan)

^b NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^c TAICHUNG ARMED FORCES GENERAL HOSPITAL   (Taiwan)

Author keywords

Colon Cancer Detection; Cost effectiveness; Machine Learning; Magnifying

Indexed keywords

ADENOMATOUS POLYP; ADULT; ARTICLE; CANCER MORTALITY; COLONOSCOPY; COLORECTAL POLYP; COMPARATIVE STUDY; COMPUTER ASSISTED RADIOGRAPHY; COMPUTER ASSISTED TOMOGRAPHY; DEEP NEURAL NETWORK; DESCENDING COLON; DESCENDING COLON POLYP; DIAGNOSTIC ACCURACY; ENDOSCOPIST; FEMALE; HUMAN; IMAGE ANALYSIS; IMAGE ENHANCEMENT; INTESTINE POLYP; MAJOR CLINICAL STUDY; MALE; MCNEMAR TEST; NARROW BAND IMAGING; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; OUTCOME ASSESSMENT; PREDICTION; PREDICTIVE VALUE; PRIORITY JOURNAL; PROSPECTIVE STUDY; RECTUM POLYP; SIGMOID; SIGMOID COLON POLYP; TAIWAN; TERTIARY CARE CENTER; TRANSVERSE COLON; TRANSVERSE COLON POLYP; ARTIFICIAL NEURAL NETWORK; AUTOMATION; CLASSIFICATION; COLON POLYP; COLORECTAL TUMOR; COMPUTER ASSISTED DIAGNOSIS; DECISION SUPPORT SYSTEM; FACTUAL DATABASE; HYPERPLASIA; OBSERVER VARIATION; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; RETROSPECTIVE STUDY; TUMOR VOLUME;

AUTOMATION; COLONIC POLYPS; COLONOSCOPY; COLORECTAL NEOPLASMS; DATABASES, FACTUAL; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; HYPERPLASIA; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NARROW BAND IMAGING; NEURAL NETWORKS (COMPUTER); OBSERVER VARIATION; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; TAIWAN; TUMOR BURDEN;

EID: 85044847443     PISSN: 00165085     EISSN: 15280012     Source Type: Journal    
DOI: 10.1053/j.gastro.2017.10.010     Document Type: Article

References (30)

1. Liou, J.M., Lin, J.T., Huang, S.P., et al. Screening for colorectal cancer in average-risk Chinese population using a mixed strategy with sigmoidoscopy and colonoscopy. Dis Colon Rectum 50 (2007), 630–640.
2. Walsh, J.M., Terdiman, J.P., Colorectal cancer screening: scientific review. JAMA 289 (2003), 1288–1296.
3. Winawer, S.J., Zauber, A.G., Ho, M.N., et al. Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med 329 (1993), 1977–1981.
4. Zauber, A.G., Winawer, S.J., O'Brien, M.J., et al. Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med 366 (2012), 687–696.
5. Patel, S.G., Schoenfeld, P., Kim, H.M., et al. Real-time characterization of diminutive colorectal polyp histology using narrow-band imaging: implications for the resect and discard strategy. Gastroenterology 150 (2016), 406–418.
6. Tanaka, S., Sano, Y., Aim to unify the narrow band imaging (NBI) magnifying classification for colorectal tumors: current status in Japan from a summary of the consensus symposium in the 79th Annual Meeting of the Japan Gastroenterological Endoscopy Society. Dig Endosc 23:suppl 1 (2011), 131–139.
7. Hewett, D.G., Kaltenbach, T., Sano, Y., et al. Validation of a simple classification system for endoscopic diagnosis of small colorectal polyps using narrow-band imaging. Gastroenterology 143 (2012), 599–607.
8. Ladabaum, U., Fioritto, A., Mitani, A., et al. Real-time optical biopsy of colon polyps with narrow band imaging in community practice does not yet meet key thresholds for clinical decisions. Gastroenterology 144 (2013), 81–91.
9. Kuiper, T., Marsman, W.A., Jansen, J.M., et al. Accuracy for optical diagnosis of small colorectal polyps in nonacademic settings. Clin Gastroenterol Hepatol 10 (2012), 1016–1020.
10. Kominami, Y., Yoshida, S., Tanaka, S., et al. Computer-aided diagnosis of colorectal polyp histology by using a real-time image recognition system and narrow-band imaging magnifying colonoscopy. Gastrointest Endosc 83 (2016), 643–649.
11. Tischendorf, J.J., Gross, S., Winograd, R., et al. Computer-aided classification of colorectal polyps based on vascular patterns: a pilot study. Endoscopy 42 (2010), 203–207.
12. Misawa, M., Kudo, S.E., Mori, Y., et al. Characterization of colorectal lesions using a computer-aided diagnostic system for narrow-band imaging endocytoscopy. Gastroenterology 150 (2016), 1531–1532.
13. Tensorflow. Available at: http://www.tensorflow.org/. (Accessed April 25, 2016).
14. Szegedy C, Vanhoucke V, Ioffe S, et al. Rethinking the inception architecture for computer vision. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016;2818–2826.
15. TensorBoard. Available at: http://www.tensorflow.org/versions/r0.7/how_tos/summaries_and_tensorboard/index.html. (Accessed April 25, 2016).
16. The Paris endoscopic classification of superficial neoplastic lesions: esophagus, stomach, and colon: November 30 to December 1, 2002. Gastrointest Endosc 58 (2003), S3–S43.
17. Rex, D.K., Kahi, C., O'Brien, M., et al. The American Society for Gastrointestinal Endoscopy PIVI (Preservation and Incorporation of Valuable Endoscopic Innovations) on real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 73 (2011), 419–422.
18. Vogelstein, B., Fearon, E.R., Hamilton, S.R., et al. Genetic alterations during colorectal-tumor development. N Engl J Med 319 (1988), 525–532.
19. ASGE Technology Committee, Abu Dayyeh, B.K., Thosani, N., et al. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 81 (2015), 502.e1–502.e16.
20. Su, M.Y., Hsu, C.M., Ho, Y.P., et al. Comparative study of conventional colonoscopy, chromoendoscopy, and narrow-band imaging systems in differential diagnosis of neoplastic and nonneoplastic colonic polyps. Am J Gastroenterol 101 (2006), 2711–2716.
21. Chiu, H.M., Chang, C.Y., Chen, C.C., et al. A prospective comparative study of narrow-band imaging, chromoendoscopy, and conventional colonoscopy in the diagnosis of colorectal neoplasia. Gut 56 (2007), 373–379.
22. Rogart, J.N., Jain, D., Siddiqui, U.D., et al. Narrow-band imaging without high magnification to differentiate polyps during real-time colonoscopy: improvement with experience. Gastrointest Endosc 68 (2008), 1136–1145.
23. Sikka, S., Ringold, D.A., Jonnalagadda, S., et al. Comparison of white light and narrow band high definition images in predicting colon polyp histology, using standard colonoscopes without optical magnification. Endoscopy 40 (2008), 818–822.
24. Abadi M, Agarwal A, Barham P, et al. TensorFlow: large-scale machine learning on heterogeneous distributed systems. Available at: http://download.tensorflow.org/paper/whitepaper2015.pdf. (Accessed April 14, 2016).
25. Frome A, Corrado GS, Shlens J et al. DeVISE: a deep visual-semantic embedding model. Available at: http://research.google.com/pubs/archive/41869.pdf. (Accessed April 15, 2016).
26. Rosenberg C. Improving photo search: a step across the semantic gap. Available at: http://googleresearch.blogspot.com/2013/06/improving-photo-search-step-across.html. (Accessed April 15, 2016).
27. Szegedy C, Wei L, Yangqing J, et al. Going deeper with convolutions. Paper presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7–12 June 2015; Boston, MA, USA.
28. Iwatate, M., Sano, Y., Hattori, S., et al. The addition of high magnifying endoscopy improves rates of high confidence optical diagnosis of colorectal polyps. Endosc Int Open 3 (2015), E140–E145.
29. Rex, D.K., Narrow-band imaging without optical magnification for histologic analysis of colorectal polyps. Gastroenterology 136 (2009), 1174–1181.
30. Rees, C.J., Rajasekhar, P.T., Wilson, A., et al. Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study. Gut 66 (2017), 887–895.