Clinical Validation of BASIC Classification for the Resect and Discard Strategy for Diminutive Colorectal Polyps.

Blue-light imaging (BLI) is a chromoendoscopy technique that uses direct (not filtered) emission of blue light with short wavelength (410 nm) to increase visibility of microvascular pattern and superficial mucosa. A BLI-based classification system for colorectal polyps (also called BLI Adenomas Serrated International Classification, BASIC) has been created and was validated using still images or short videos. We aimed to validate BASIC in a clinical practice setting, using thresholds recommended by the American Society for Gastrointestinal Endoscopy for the resect and discard strategy as the reference standard. We studied 333 patients (mean age, 62.7±8.1 y; 176 men) who underwent screening colonoscopy from January through July 2019. Six endoscopists trained in BASIC participated in the study. All detected diminutive polyps were characterized by real-time BLI and categorized as adenoma or non-adenoma according to BASIC. All polyps were removed and evaluated by histopathology. The BLI-directed surveillance intervals (based on high-confidence characterization of polyps 5 mm or smaller and pathology feature for others) were compared with histology-directed surveillance intervals, according to United States Multi-society Task Force and European Society of Gastrointestinal Endoscopy recommendations. We calculated negative-predictive values of optical real-time analysis of diminutive rectosigmoid adenomas. When we applied BASIC, 748 polyps smaller than 5 mm were categorized with 89% accuracy (95% CI, 85.9%-90.6%). BLI-directed surveillance was correct for 90% of patients according to the United States Multi-society task force criteria (95% CI, 86%-93%) and for 96% of patients according to European Society of Gastrointestinal Endoscopy criteria (95% CI, 93%-97%). The negative-predictive value for 302 polyps smaller than 5 mm, located in the rectosigmoid colon and evaluated with high confidence, based on histologic features of adenomatous polyps, was 91% (95% CI, 85%-95%). Our analysis of data from 333 patients undergoing screen colonoscopies supports the validity of BASIC discriminating diminutive colorectal polyps with histologic features of adenomas from non-adenomas. This allows for the implementation of the resect and discard strategy based on BLI in clinical practice. ClinicalTrials.gov no: NCT03746171.

Rondonotti E ，Hassan C ，Andrealli A ，Paggi S ，Amato A ，Scaramella L ，Repici A ，Radaelli F ... -  《-》

Real-Time Characterization of Diminutive Colorectal Polyp Histology Using Narrow-Band Imaging: Implications for the Resect and Discard Strategy.

Narrow-band imaging (NBI) allows real-time histologic classification of colorectal polyps. We investigated whether endoscopists without prior training in NBI can achieve the following thresholds recommended by the American Society for Gastrointestinal Endoscopy: for diminutive colorectal polyps characterized with high confidence, a ≥90% negative predictive value for adenomas in the rectosigmoid and a ≥90% agreement in surveillance intervals. Twenty-six endoscopists from 2 tertiary care centers underwent standardized training in NBI interpretation. Endoscopists made real-time predictions of diminutive colorectal polyp histology and surveillance interval predictions based on NBI. Their performance was evaluated by comparing predicted with actual findings from histologic analysis. Multilevel logistic regression was used to assess predictors of performance. Cumulative summation analysis was used to characterize learning curves. The endoscopists performed 1451 colonoscopies and made 3012 diminutive polyp predictions (74.3% high confidence) using NBI. They made 898 immediate post-procedure surveillance interval predictions. An additional 505 surveillance intervals were determined with histology input. The overall negative predictive value for high-confidence characterizations in the rectosigmoid was 94.7% (95% confidence interval: 92.6%-96.8%) and the surveillance interval agreement was 91.2% (95% confidence interval: 89.7%-92.7%). Overall, 97.0% of surveillance interval predictions would have brought patients back on time or early. High-confidence characterization was the strongest predictor of accuracy (odds ratio = 3.42; 95% confidence interval: 2.72-4.29; P < .001). Performance improved over time, however, according to cumulative summation analysis, only 7 participants (26.9%) identified adenomas with sufficient sensitivity such that further auditing is not required. With standardized training, gastroenterologists without prior expertise in NBI were able to meet the negative predictive value and surveillance interval thresholds set forth by the American Society for Gastrointestinal Endoscopy. The majority of disagreement in surveillance interval brought patients back early. Performance improves with time, but most endoscopists will require ongoing auditing of performance. ClinicalTrials.gov ID NCT02441998.

Patel SG ，Schoenfeld P ，Kim HM ，Ward EK ，Bansal A ，Kim Y ，Hosford L ，Myers A ，Foster S ，Craft J ，Shopinski S ，Wilson RH ，Ahnen DJ ，Rastogi A ，Wani S ... -  《-》

Blue-light imaging compared with high-definition white light for real-time histology prediction of colorectal polyps less than 1 centimeter: a prospective randomized study.

Blue-light imaging (BLI) is a new chromoendoscopy technique, potentially useful for differentiating neoplastic from nonneoplastic lesions. The present study was aimed at comparing BLI with high-definition white light (HDWL) in the real-time histology prediction of colon polyps <10 mm. Consecutive outpatients undergoing colonoscopy with the ELUXEO 7000 endoscopy platform and 760 series video colonoscopes (Fujifilm Co, Tokyo, Japan) who had at least 1 polyp <10 mm were randomized to BLI or HDWL for polyp characterization. The accuracy of high-confidence real-time histology prediction (adenoma vs not adenoma) by either BLI or HDWL for polyps <10 mm (primary end-point) and diminutive (≤5 mm) polyps was calculated, along with sensitivity, specificity, and positive and negative predictive values, with histopathology as the reference standard. A total of 483 polyps were detected in 245 randomized patients (125 and 120 in the BLI and HDWL arms, respectively). A total of 358 were diminutive, and 283 were adenomas. Overall, 222 (85.7%) and 193 (86.1%) polyps were characterized with high confidence by BLI and HDWL, respectively (P = .887), with an overall accuracy of 92% and 84%, respectively (P = .011). The accuracy was significantly higher by BLI than HDWL, also for diminutive polyps (92% vs 83%; P = .008). When BLI was used, the negative predictive value for diminutive rectosigmoid polyps was 88%, and the post-polypectomy surveillance interval was correctly attributed in 85.7% and 93.7% of patients, respectively, according to U.S. and European guidelines. BLI was superior to HDWL for the real-time prediction of histology in polyps <10 mm. A BLI-dedicated classification might further improve the endoscopist performance. (Clinical trial registration number: NCT03274115.).

Rondonotti E ，Paggi S ，Amato A ，Mogavero G ，Andrealli A ，Conforti FS ，Conte D ，Spinzi G ，Radaelli F ... -  《-》

Artificial Intelligence Allows Leaving-In-Situ Colorectal Polyps.

Artificial Intelligence (AI) could support cost-saving strategies for colonoscopy because of its accuracy in the optical diagnosis of colorectal polyps. However, AI must meet predefined criteria to be implemented in clinical settings. An approved computer-aided diagnosis (CADx) module for differentiating between adenoma and nonadenoma in unmagnified white-light colonoscopy was used in a consecutive series of colonoscopies. For each polyp, CADx output and subsequent endoscopist diagnosis with advanced imaging were matched against the histology gold standard. The primary outcome was the negative predictive value (NPV) of CADx for adenomatous histology for ≤5-mm rectosigmoid lesions. We also calculated the NPV for AI-assisted endoscopist predictions, and agreement between CADx and histology-based postpolypectomy surveillance intervals according to European and American guidelines. Overall, 544 polyps were removed in 162 patients, of which 295 (54.2%) were ≤5-mm rectosigmoid histologically verified lesions. CADx diagnosis was feasible in 291 of 295 (98.6%), and the NPV for ≤5-mm rectosigmoid lesions was 97.6% (95% CI, 94.1%-99.1%). There were 242 of 295 (82%) lesions that were amenable for a leave-in-situ strategy. Based on CADx output, 212 of 544 (39%) would be amenable to a resect-and-discard strategy, resulting in a 95.6% (95% CI, 90.8%-98.0%) and 95.9% (95% CI, 89.8%-98.4%) agreement between CADx- and histology-based surveillance intervals according to European and American guidelines, respectively. A similar NPV (97.6%; 95% CI, 94.8%-99.1%) for ≤5-mm rectosigmoids was achieved by AI-assisted endoscopists assessing polyps with electronic chromoendoscopy, with a CADx-concordant diagnosis in 97.2% of cases. In this study, CADx without advanced imaging exceeded the benchmarks required for optical diagnosis of colorectal polyps. CADx could help implement cost-saving strategies in colonoscopy by reducing the burden of polypectomy and/or pathology. gov registration number: NCT04884581.

Hassan C ，Balsamo G ，Lorenzetti R ，Zullo A ，Antonelli G ... -  《-》

Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: the Artificial intelligence BLI Characterization (ABC) study.

Optical diagnosis of colonic polyps is poorly reproducible outside of high volume referral centers. The present study aimed to assess whether real-time artificial intelligence (AI)-assisted optical diagnosis is accurate enough to implement the leave-in-situ strategy for diminutive (≤ 5 mm) rectosigmoid polyps (DRSPs). Consecutive colonoscopy outpatients with ≥ 1 DRSP were included. DRSPs were categorized as adenomas or nonadenomas by the endoscopists, who had differing expertise in optical diagnosis, with the assistance of a real-time AI system (CAD-EYE). The primary end point was ≥ 90 % negative predictive value (NPV) for adenomatous histology in high confidence AI-assisted optical diagnosis of DRSPs (Preservation and Incorporation of Valuable endoscopic Innovations [PIVI-1] threshold), with histopathology as the reference standard. The agreement between optical- and histology-based post-polypectomy surveillance intervals (≥ 90 %; PIVI-2 threshold) was also calculated according to European Society of Gastrointestinal Endoscopy (ESGE) and United States Multi-Society Task Force (USMSTF) guidelines. Overall 596 DRSPs were retrieved for histology in 389 patients; an AI-assisted high confidence optical diagnosis was made in 92.3 %. The NPV of AI-assisted optical diagnosis for DRSPs (PIVI-1) was 91.0 % (95 %CI 87.1 %-93.9 %). The PIVI-2 threshold was met with 97.4 % (95 %CI 95.7 %-98.9 %) and 92.6 % (95 %CI 90.0 %-95.2 %) of patients according to ESGE and USMSTF, respectively. AI-assisted optical diagnosis accuracy was significantly lower for nonexperts (82.3 %, 95 %CI 76.4 %-87.3 %) than for experts (91.9 %, 95 %CI 88.5 %-94.5 %); however, nonexperts quickly approached the performance levels of experts over time. AI-assisted optical diagnosis matches the required PIVI thresholds. This does not however offset the need for endoscopists' high level confidence and expertise. The AI system seems to be useful, especially for nonexperts.

Rondonotti E ，Hassan C ，Tamanini G ，Antonelli G ，Andrisani G ，Leonetti G ，Paggi S ，Amato A ，Scardino G ，Di Paolo D ，Mandelli G ，Lenoci N ，Terreni N ，Andrealli A ，Maselli R ，Spadaccini M ，Galtieri PA ，Correale L ，Repici A ，Di Matteo FM ，Ambrosiani L ，Filippi E ，Sharma P ，Radaelli F ... -  《-》