A Polyp Worth Removing: A Paradigm for Measuring Colonoscopy Quality and Performance of Novel Technologies for Polyp Detection.

Leaving no significant polyp behind while avoiding risks due to unnecessary resections is a commonsense strategy to safely and effectively prevent colorectal cancer (CRC) with colonoscopy. It also alludes to polyps worth removing and, therefore, worth finding. The majority of "worthy" precancerous polyps are adenomas, which for over 2 decades, have received the most attention in performance research and metrics. Consequently, the detection rate of adenomas is currently the only validated, outcome-based measure of colonoscopy demonstrated to correlate with reduced risk of postcolonoscopy CRC. However, a third or more of postcolonoscopy CRCs originate from sessile serrated polyps (SSPs), which are notoriously difficult to find, diagnose and completely resect. Among serrated polyps, the agreement among pathologists differentiating SSPs from non-neoplastic hyperplastic polyps is moderate at best. This lack of ground truth precludes SSPs from consideration in primary metrics of colonoscopy quality or performance of novel polyp detection technologies. By instead leveraging the distinct endoscopic and clinical features of serrated polyps, including those considered important due to proximal location and larger size, clinically significant serrated polyps represent serrated polyps worth removing, enriched with subtle precancerous SSPs. With the explosion of technologies to assist polyp detection, now is the time to broaden benchmarks to include clinically significant serrated polypss alongside adenomas, a measure that is relevant both for assessing the performance of endoscopists, and for assessing new polyp detection technologies.

Prediction of Polyp Pathology Using Convolutional Neural Networks Achieves "Resect and Discard" Thresholds.

OBJECTIVES: Reliable in situ diagnosis of diminutive (≤5 mm) colorectal polyps could allow for "resect and discard" and "diagnose and leave" strategies, resulting in $1 billion cost savings per year in the United States alone. Current methodologies have failed to consistently meet the Preservation and Incorporation of Valuable endoscopic Innovations (PIVIs) initiative thresholds. Convolutional neural networks (CNNs) have the potential to predict polyp pathology and achieve PIVI thresholds in real time. METHODS: We developed a CNN-based optical pathology (OP) model using Tensorflow and pretrained on ImageNet, capable of operating at 77 frames per second. A total of 6,223 images of unique colorectal polyps of known pathology, location, size, and light source (white light or narrow band imaging [NBI]) underwent 5-fold cross-training (80%) and validation (20%). Separate fresh validation was performed on 634 polyp images. Surveillance intervals were calculated, comparing OP with true pathology. RESULTS: In the original validation set, the negative predictive value for adenomas was 97% among diminutive rectum/rectosigmoid polyps. Results were independent of use of NBI or white light. Surveillance interval concordance comparing OP and true pathology was 93%. In the fresh validation set, the negative predictive value was 97% among diminutive polyps in the rectum and rectosigmoid and surveillance concordance was 94%. DISCUSSION: This study demonstrates the feasibility of in situ diagnosis of colorectal polyps using CNN. Our model exceeds PIVI thresholds for both "resect and discard" and "diagnose and leave" strategies independent of NBI use. Point-of-care adenoma detection rate and surveillance recommendations are potential added benefits.

Mechanism and Pathophysiology of Gastroesophageal Reflux Disease.

Gastroesophageal reflux (GER) describes a process in which gastric contents travel retrograde into the esophagus. GER can be either a physiologic phenomenon that occurs in asymptomatic individuals or can potentially cause symptoms. When the latter occurs, this represents GER disease (GERD). The process by which GER transforms into GERD begins at the esophagogastric junction. Impaired clearance of the refluxate also contributes to GERD. Reflux causes degradation of esophageal mucosal defense. The refluxate triggers sensory afferents leading to symptom generation.