Malignancy in Large Colorectal Lesions

Abstract

-Context -The size of colorectal lesions, besides a risk factor for malignancy, is a predictor for deeper invasion. Objective -To evaluate the malignancy of colorectal lesions >20 mm. Methods -Between 2007 and 2011, 76 neoplasms >20 mm in 70 patients were analyzed. Results -The mean age of the patients was 67.4 years, and 41 were women. Mean lesion size was 24.7 mm + 6.2 mm (range: 20 to 50 mm). Half of the neoplasms were polypoid and the other half were non-polypoid. Forty-two (55.3%) lesions were located in the left colon, and 34 in the right colon. There was a high prevalence of III L (39.5%) and IV (53.9%) pit patterns. There were 72 adenomas and 4 adenocarcinomas. Malignancy was observed in 5.3% of the lesions. Thirty-three lesions presented advanced histology (adenomas with high-grade dysplasia or early adenocarcinoma), with no difference in morphology and site. Only one lesion (1.3%) invaded the submucosa. Lesions larger than 30 mm had advanced histology (P = 0.001). The primary treatment was endoscopic resection, and invasive carcinoma was referred to surgery. Recurrence rate was 10.6%. Conclusions -Large colorectal neoplasms showed a low rate of malignancy. Endoscopic treatment is an effective therapy for these lesions. HEADINGS -Colonic polyps. Colorectal neoplasms. Gastrointestinal endoscopy.

Colon polyps: updates in classification and management

“…Multiple uses for artificial intelligence are now being considered including its use in endoscopic polyp classification. Several models incorporating machine learning are currently in the development pipeline to assist in endoscopic pathology assessment and once developed may revolutionize the current schema of endoscopic classification [48–50,51 ▪▪ ]. With a more standardized and reliable technology that can identify polyp pathology using machine learning, opportunities may arise for additional improvement in quality measures such as resect and discard, reducing the number of required pathology assessment and providing patients with real-time surveillance recommendations [52].…”