BACKGROUND AND AIM: The Japan Narrow-Band Imaging (NBI) Expert Team (JNET) classification is a recently proposed NBI magnifying endoscopy-based classification system for colorectal tumors. Although the usefulness of this system has been reported by JNET experts, its objective validity remains unclear. We tested its validity and usefulness for the diagnosis of colorectal polyps by including colonoscopy experts and non-experts as test participants. METHODS: Forty NBI images of polyps of various JNET types were shown to 22 doctors (11 experts and 11 non-gastrointestinal [GI] trainees) who had not examined the patients. The doctors diagnosed the polyps based solely on the surface and vessel patterns in the magnified images and the JNET classification system. Concordance rates of their diagnoses with the pathological findings of the polyps were determined, and the results for experts and non-GI trainees were compared. RESULTS: Both for colonoscopy experts and non-GI trainees, the JNET classification system was particularly useful for classifying polyps as benign or malignant. Although the accuracy rates for classifying polyps into each JNET type varied among colonoscopy experts, those who were familiar with the JNET classification system were able to diagnose polyps with approximately 90% accuracy. Common mistakes were attributable to misunderstandings of the wording in the JNET classification chart and lack of proper training. CONCLUSION: The JNET classification system is a practical approach for the diagnosis of colorectal polyps. Training is required even for experienced colonoscopists to adopt the system properly. Common pitfalls must be shared among colonoscopists to improve the accuracy of the diagnosis.
BACKGROUND AND AIM: The Japan Narrow-Band Imaging (NBI) Expert Team (JNET) classification is a recently proposed NBI magnifying endoscopy-based classification system for colorectal tumors. Although the usefulness of this system has been reported by JNET experts, its objective validity remains unclear. We tested its validity and usefulness for the diagnosis of colorectal polyps by including colonoscopy experts and non-experts as test participants. METHODS: Forty NBI images of polyps of various JNET types were shown to 22 doctors (11 experts and 11 non-gastrointestinal [GI] trainees) who had not examined the patients. The doctors diagnosed the polyps based solely on the surface and vessel patterns in the magnified images and the JNET classification system. Concordance rates of their diagnoses with the pathological findings of the polyps were determined, and the results for experts and non-GI trainees were compared. RESULTS: Both for colonoscopy experts and non-GI trainees, the JNET classification system was particularly useful for classifying polyps as benign or malignant. Although the accuracy rates for classifying polyps into each JNET type varied among colonoscopy experts, those who were familiar with the JNET classification system were able to diagnose polyps with approximately 90% accuracy. Common mistakes were attributable to misunderstandings of the wording in the JNET classification chart and lack of proper training. CONCLUSION: The JNET classification system is a practical approach for the diagnosis of colorectal polyps. Training is required even for experienced colonoscopists to adopt the system properly. Common pitfalls must be shared among colonoscopists to improve the accuracy of the diagnosis.
Authors: Tiing Leong Ang; Jit Fong Lim; Tju Siang Chua; Kok Yang Tan; James Weiquan Li; Chern Hao Chong; Kok Ann Gwee; Vikneswaran S/O Namasivayam; Charles Kien Fong Vu; Christopher Jen Lock Khor; Lai Mun Wang; Khay Guan Yeoh Journal: Singapore Med J Date: 2020-07-16 Impact factor: 3.331