Computer-aided diagnosis for the resect-and-discard strategy for colorectal polyps: a systematic review and meta-analysis.

BACKGROUND: The resect-and-discard strategy allows endoscopists to replace post-polypectomy pathology with real-time prediction of polyp histology during colonoscopy (optical diagnosis). We aimed to investigate the benefits and harms of implementing computer-aided diagnosis (CADx) for polyp pathology into the resect-and-discard strategy. METHODS: In this systematic review and meta-analysis, we searched MEDLINE, Embase, and Scopus from database inception to June 5, 2024, without language restrictions, for diagnostic accuracy studies that assessed the performance of real-time CADx systems, compared with histology, for the optical diagnosis of diminutive polyps (≤5 mm) in the entire colon. We synthesised data for three strategies: CADx-alone, CADx-unassisted, and CADx-assisted; when the endoscopist was involved in the optical diagnosis, we synthesised data exclusively from diagnoses for which confidence in the prediction was reported as high. The primary outcomes were the proportion of polyps that would have avoided pathological assessment (ie, the proportion optically diagnosed with high confidence; main benefit) and the proportion of polyps incorrectly predicted due to false positives and false negatives (main harm), directly compared between CADx-assisted and CADx-unassisted strategies. We used DerSimonian and Laird's random-effects model to calculate all outcomes. We used Higgins I2 to assess heterogeneity, the Grading of Recommendations, Assessment, Development, and Evaluation approach to rate certainty, and funnel plots and Egger's test to examine publication bias. This study is registered with PROSPERO, CRD42024508440. FINDINGS: We found 1019 studies, of which 11 (7400 diminutive polyps, 3769 patients, and 185 endoscopists) were included in the final meta-analysis. Three studies (1817 patients and 4086 polyps [2148 neoplastic and 1938 non-neoplastic]) provided data to directly compare the primary outcome measures between the CADx-unassisted and CADx-assisted strategies. We found no significant difference between the CADx-assisted and CADx-unassisted strategies for the proportion of polyps that would have avoided pathological assessment (90% [88-93], 3653 [89·4%] of 4086 polyps diagnosed with high confidence vs 90% [95% CI 85-94], 3588 [87·8%] of 4086 polyps diagnosed with high confidence; risk ratio 1·01 [95% CI 0·99-1·04; I2=53·49%; low-certainty evidence; Egger's test p=0·18). The proportion of incorrectly predicted polyps was lower with the CADx-assisted strategy than with the CADx-unassisted strategy (12% [95% CI 7-17], 523 [14·3%] of 3653 polyps incorrectly predicted with a CADx-assisted strategy vs 13% [6-20], 582 [16·2%] of 3588 polyps incorrectly diagnosed with a CADx-unassisted strategy; risk ratio 0·88 [95% CI 0·79-0·98]; I2=0·00%; low-certainty evidence; Egger's test p=0·18). INTERPRETATION: CADx did not produce benefit nor harm for the resect-and-discard strategy, questioning its value in clinical practice. Improving the accuracy and explainability of CADx is desired. FUNDING: European Commission (Horizon Europe), the Japan Society of Promotion of Science, and Associazione Italiana per la Ricerca sul Cancro.

White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice.

Background and study aims Artificial Intelligence (AI) systems could make the optical diagnosis (OD) of diminutive colorectal polyps (DCPs) more reliable and objective. This study was aimed at prospectively evaluating feasibility and diagnostic performance of AI-standalone and AI-assisted OD of DCPs in a real-life setting by using a white light-based system (GI Genius, Medtronic Co, Minneapolis, Minnesota, United States). Patients and methods Consecutive colonoscopy outpatients with at least one DCP were evaluated by 11 endoscopists (5 experts and 6 non-experts in OD). DCPs were classified in real time by AI (AI-standalone OD) and by the endoscopist with the assistance of AI (AI-assisted OD), with histopathology as the reference standard. Results Of the 480 DCPs, AI provided the outcome "adenoma" or "non-adenoma" in 81.4% (95% confidence interval [CI]: 77.5-84.6). Sensitivity, specificity, positive and negative predictive value, and accuracy of AI-standalone OD were 97.0% (95% CI 94.0-98.6), 38.1% (95% CI 28.9-48.1), 80.1% (95% CI 75.2-84.2), 83.3% (95% CI 69.2-92.0), and 80.5% (95% CI 68.7-82.8%), respectively. Compared with AI-standalone, the specificity of AI-assisted OD was significantly higher (58.9%, 95% CI 49.7-67.5) and a trend toward an increase was observed for other diagnostic performance measures. Overall accuracy and negative predictive value of AI-assisted OD for experts and non-experts were 85.8% (95% CI 80.0-90.4) vs. 80.1% (95% CI 73.6-85.6) and 89.1% (95% CI 75.6-95.9) vs. 80.0% (95% CI 63.9-90.4), respectively. Conclusions Standalone AI is able to provide an OD of adenoma/non-adenoma in more than 80% of DCPs, with a high sensitivity but low specificity. The human-machine interaction improved diagnostic performance, especially when experts were involved.

Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ : A Systematic Review and Meta-analysis.

BACKGROUND: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES: Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE: European Commission. (PROSPERO: CRD42023402197).

Comparing accuracy of tomosynthesis plus digital mammography or synthetic 2D mammography in breast cancer screening: baseline results of the MAITA RCT consortium.

AIM: The analyses here reported aim to compare the screening performance of digital tomosynthesis (DBT) versus mammography (DM). METHODS: MAITA is a consortium of four Italian trials, REtomo, Proteus, Impeto, and MAITA trial. The trials adopted a two-arm randomised design comparing DBT plus DM (REtomo and Proteus) or synthetic-2D (Impeto and MAITA trial) versus DM; multiple vendors were included. Women aged 45 to 69 years were individually randomised to one round of DBT or DM. FINDINGS: From March 2014 to February 2022, 50,856 and 63,295 women were randomised to the DBT and DM arm, respectively. In the DBT arm, 6656 women were screened with DBT plus synthetic-2D. Recall was higher in the DBT arm (5·84% versus 4·96%), with differences between centres. With DBT, 0·8/1000 (95% CI 0·3 to 1·3) more women received surgical treatment for a benign lesion. The detection rate was 51% higher with DBT, ie. 2·6/1000 (95% CI 1·7 to 3·6) more cancers detected, with a similar relative increase for invasive cancers and ductal carcinoma in situ. The results were similar below and over the age of 50, at first and subsequent rounds, and with DBT plus DM and DBT plus synthetic-2D. No learning curve was appreciable. Detection of cancers >= 20 mm, with 2 or more positive lymph nodes, grade III, HER2-positive, or triple-negative was similar in the two arms. INTERPRETATION: Results from MAITA confirm that DBT is superior to DM for the detection of cancers, with a possible increase in recall rate. DBT performance in screening should be assessed locally while waiting for long-term follow-up results on the impact of advanced cancer incidence.

Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy : A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence computer-aided detection (CADe) of colorectal neoplasia during colonoscopy may increase adenoma detection rates (ADRs) and reduce adenoma miss rates, but it may increase overdiagnosis and overtreatment of nonneoplastic polyps. PURPOSE: To quantify the benefits and harms of CADe in randomized trials. DESIGN: Systematic review and meta-analysis. (PROSPERO: CRD42022293181). DATA SOURCES: Medline, Embase, and Scopus databases through February 2023. STUDY SELECTION: Randomized trials comparing CADe-assisted with standard colonoscopy for polyp and cancer detection. DATA EXTRACTION: Adenoma detection rate (proportion of patients with ≥1 adenoma), number of adenomas detected per colonoscopy, advanced adenoma (≥10 mm with high-grade dysplasia and villous histology), number of serrated lesions per colonoscopy, and adenoma miss rate were extracted as benefit outcomes. Number of polypectomies for nonneoplastic lesions and withdrawal time were extracted as harm outcomes. For each outcome, studies were pooled using a random-effects model. Certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. DATA SYNTHESIS: Twenty-one randomized trials on 18 232 patients were included. The ADR was higher in the CADe group than in the standard colonoscopy group (44.0% vs. 35.9%; relative risk, 1.24 [95% CI, 1.16 to 1.33]; low-certainty evidence), corresponding to a 55% (risk ratio, 0.45 [CI, 0.35 to 0.58]) relative reduction in miss rate (moderate-certainty evidence). More nonneoplastic polyps were removed in the CADe than the standard group (0.52 vs. 0.34 per colonoscopy; mean difference [MD], 0.18 polypectomy [CI, 0.11 to 0.26 polypectomy]; low-certainty evidence). Mean inspection time increased only marginally with CADe (MD, 0.47 minute [CI, 0.23 to 0.72 minute]; moderate-certainty evidence). LIMITATIONS: This review focused on surrogates of patient-important outcomes. Most patients, however, may consider cancer incidence and cancer-related mortality important outcomes. The effect of CADe on such patient-important outcomes remains unclear. CONCLUSION: The use of CADe for polyp detection during colonoscopy results in increased detection of adenomas but not advanced adenomas and in higher rates of unnecessary removal of nonneoplastic polyps. PRIMARY FUNDING SOURCE: European Commission Horizon 2020 Marie Sklodowska-Curie Individual Fellowship.

Texture and color enhancement imaging versus high definition white-light endoscopy for detection of colorectal neoplasia: a randomized trial.

BACKGROUND: Texture and color enhancement imaging (TXI) was recently proposed as a substitute for standard high definition white-light imaging (WLI) to increase lesion detection during colonoscopy. This international, multicenter randomized trial assessed the efficacy of TXI in detection of colorectal neoplasia. METHODS: Consecutive patients aged ≥ 40 years undergoing screening, surveillance, or diagnostic colonoscopies at five centers (Italy, Germany, Japan) between September 2021 and May 2022 were enrolled. Patients were randomly assigned (1:1) to TXI or WLI. Primary outcome was adenoma detection rate (ADR). Secondary outcomes were adenomas per colonoscopy (APC) and withdrawal time. Relative risks (RRs) adjusted for age, sex, and colonoscopy indication were calculated. RESULTS: We enrolled 747 patients (mean age 62.3 [SD 9.5] years, 50.2 % male). ADR was significantly higher with TXI (221/375, 58.9 %) vs. WLI (159/372, 42.7 %; adjusted RR 1.38 [95 %CI 1.20-1.59]). This was significant for ≤ 5 mm (RR 1.42 [1.16-1.73]) and 6-9 mm (RR 1.36 [1.01-1.83]) adenomas. A higher proportion of polypoid (151/375 [40.3 %] vs. 104/372 [28.0 %]; RR 1.43 [1.17-1.75]) and nonpolypoid (136/375 [36.3 %] vs. 102/372 [27.4 %]; RR 1.30 [1.05-1.61]) adenomas, and proximal (143/375 [38.1 %] vs. 111/372 [29.8 %]; RR 1.28 [1.05-1.57]) and distal (144/375 [38.4 %] vs. 98/372 [26.3 %]; RR 1.46 [1.18-1.80]) lesions were found with TXI. APC was higher with TXI (1.36 [SD 1.79] vs. 0.89 [SD 1.35]; incident rate ratio 1.53 [1.25-1.88]). CONCLUSIONS: TXI increased ADR and APC among patients undergoing colonoscopy for various indications. TXI increased detection of polyps < 10 mm, both in the proximal and distal colon, and may help to improve colonoscopy quality indicators.

Rapid on-site evaluation improves the sensitivity of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) for solid pancreatic lesions irrespective of technique: A single-centre experience.

OBJECTIVE: Endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) is the first-line technique for the sampling of pancreatic lesions. Many factors can influence the diagnostic performance of this procedure, including the use of rapid on-site evaluation (ROSE). The primary aim of this study was to compare the adequacy, diagnostic yield, accuracy, sensitivity and specificity of EUS-FNA for solid pancreatic lesions before and after the introduction of ROSE. METHODS: This retrospective single-centre study evaluated all consecutive patients who underwent EUS-FNA for suspicious, solid pancreatic masses from April 2012 to March 2015. We compared the findings of EUS-FNA procedures performed during the first and second years following the adoption of ROSE ("ROSE1" and "ROSE2", respectively) to those performed the year before ROSE introduction (the "pre-ROSE" group). RESULTS: Ninety-one consecutive patients with a total of 93 pancreatic lesions were enrolled. For the pre-ROSE, ROSE1 and ROSE2 groups, the adequacy rates were 96.2%, 96.6% and 100%, the diagnostic yield values were 76.9%, 89.7% and 92.1% and accuracy values were 69.2%, 86.2% and 89.5% (p = NS). Sensitivity for malignancy improved from 63.7% in the pre-ROSE group to 91.7% and 91.2% in the post-ROSE groups (p < 0.05). Specificity for malignancy was 100% in all groups. CONCLUSIONS: ROSE can improve the diagnostic performance of EUS-FNA for solid pancreatic lesions, although only sensitivity reached statistical significance.

AI-based opportunistic CT screening of incidental cardiovascular disease, osteoporosis, and sarcopenia: cost-effectiveness analysis.

PURPOSE: To assess the cost-effectiveness and clinical efficacy of AI-assisted abdominal CT-based opportunistic screening for atherosclerotic cardiovascular (CV) disease, osteoporosis, and sarcopenia using artificial intelligence (AI) body composition algorithms. METHODS: Markov models were constructed and 10-year simulations were performed on hypothetical age- and sex-specific cohorts of 10,000 U.S. adults (base case: 55 year olds) undergoing abdominal CT. Using expected disease prevalence, transition probabilities between health states, associated healthcare costs, and treatment effectiveness related to relevant conditions (CV disease/osteoporosis/sarcopenia) were modified by three mutually exclusive screening models: (1) usual care ("treat none"; no intervention regardless of opportunistic CT findings), (2) universal statin therapy ("treat all" for CV prevention; again, no consideration of CT findings), and (3) AI-assisted abdominal CT-based opportunistic screening for CV disease, osteoporosis, and sarcopenia using automated quantitative algorithms for abdominal aortic calcification, bone mineral density, and skeletal muscle, respectively. Model validity was assessed against published clinical cohorts. RESULTS: For the base-case scenarios of 55-year-old men and women modeled over 10 years, AI-assisted CT-based opportunistic screening was a cost-saving and more effective clinical strategy, unlike the "treat none" and "treat all" strategies that ignored incidental CT body composition data. Over a wide range of input assumptions beyond the base case, the CT-based opportunistic strategy was dominant over the other two scenarios, as it was both more clinically efficacious and more cost-effective. Cost savings and clinical improvement for opportunistic CT remained for AI tool costs up to $227/patient in men ($65 in women) from the $10/patient base-case scenario. CONCLUSION: AI-assisted CT-based opportunistic screening appears to be a highly cost-effective and clinically efficacious strategy across a broad array of input assumptions, and was cost saving in most scenarios.

Wide-area transepithelial sampling with computer-assisted analysis to detect high grade dysplasia and cancer in Barrett's esophagus: a multicenter randomized study.

BACKGROUND: Current surveillance for Barrett's esophagus (BE), consisting of four-quadrant random forceps biopsies (FBs), has an inherent risk of sampling error. Wide-area transepithelial sampling (WATS) may increase detection of high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC). In this multicenter randomized trial, we aimed to evaluate WATS as a substitute for FB. METHODS: Patients with known BE and a recent history of dysplasia, without visible lesions, at 17 hospitals were randomized to receive either WATS followed by FB or vice versa. All WATS samples were examined, with computer assistance, by at least two experienced pathologists at the CDx Diagnostics laboratory. Similarly, all FBs were examined by two expert pathologists. The primary end point was concordance/discordance for detection of HGD/EAC between the two techniques. RESULTS: 172 patients were included, of whom 21 had HGD/EAC detected by both modalities, 18 had HGD/EAC detected by WATS but missed by FB, and 12 were detected by FB but missed by WATS. The detection rate of HGD/EAC did not differ between WATS and FB (P = 0.36). Using WATS as an adjunct to FB significantly increased the detection of HGD/EAC vs. FB alone (absolute increase 10 % [95 %CI 6 % to 16 %]). Mean procedural times in minutes for FB alone, WATS alone, and the combination were 6.6 (95 %CI 5.9 to 7.1), 4.9 (95 %CI 4.1 to 5.4), and 11.2 (95 %CI 10.5 to 14.0), respectively. CONCLUSIONS: Although the combination of WATS and FB increases dysplasia detection in a population of BE patients enriched for dysplasia, we did not find a statistically significant difference between WATS and FB for the detection of HGD/EAC as single modality.

Impact of Artificial Intelligence on Colonoscopy Surveillance After Polyp Removal: A Pooled Analysis of Randomized Trials.

BACKGROUND AND AIMS: Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal. METHODS: We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method. RESULTS: A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%-9.5%) in the non-AI group to 11.3% (95% CI, 10.2%-12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%-4.4%]; risk ratio, 1.35 [95% CI, 1.16-1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%-7.0%) to 7.4% (95% CI, 6.5%-8.4%) (absolute difference, 1.3% [95% CI, 0.01%-2.6%]; risk ratio, 1.22 [95% CI, 1.01-1.47]). CONCLUSIONS: The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs.

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

BACKGROUND: 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). METHODS: 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. RESULTS: 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. CONCLUSION: 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.

A randomised controlled trial of digital breast tomosynthesis vs digital mammography as primary screening tests: Screening results over subsequent episodes of the Proteus Donna study.

Proteus Donna is a randomised controlled trial aimed at prospectively evaluating screening with digital breast tomosynthesis (DBT), including interval cancer detection (ICD) and cancer detection (CD) in the analysis as a cumulative measure over subsequent screening episodes. Consenting women aged 46 to 68 attending the regional Breast Screening Service were randomly assigned to conventional digital mammography (DM, control arm) or DBT in addition to DM (DBT, study arm). At the subsequent round all participants underwent DM. Thirty-six months follow-up allowed for the identification of cancers detected in the subsequent screening and interscreening interval. Relative risk (RR) and 95% confidence interval (95% CI) were computed. Cumulative CD and Nelson-Aalen incidence were analysed over the follow-up period. Between 31 December 2014 and 31 December 2017, 43 022 women were randomised to DM and 30 844 to DBT. At baseline, CD was significantly higher (RR: 1.44, 95% CI: 1.21-1.71) in the study arm. ICD did not differ significantly between the two arms (RR: 0.92, 95% CI: 0.62-1.35). At subsequent screening with DM, the CD was lower (nearly significant) in the study arm (RR: 0.83, 95% CI: 0.65-1.06). Over the follow-up period, the cumulative CD (comprehensive of ICD) was slightly higher in the study arm (RR: 1.15, 95% CI: 1.01-1.31). The Nelson-Aalen cumulative incidence over time remained significantly higher in the study arm for approximately 24 months. Benign lesions detection was higher in the study arm at baseline and lower at subsequent tests. Outcomes are consistent with a lead time gain of DBT compared to DM, with an increase in false positives and moderate overdiagnosis.

Efficacy of a computer-aided detection system in a fecal immunochemical test-based organized colorectal cancer screening program: a randomized controlled trial (AIFIT study).

BACKGROUND: Computer-aided detection (CADe) increases adenoma detection in primary screening colonoscopy. The potential benefit of CADe in a fecal immunochemical test (FIT)-based colorectal cancer (CRC) screening program is unknown. This study assessed whether use of CADe increases the adenoma detection rate (ADR) in a FIT-based CRC screening program. METHODS: In a multicenter, randomized trial, FIT-positive individuals aged 50-74 years undergoing colonoscopy, were randomized (1:1) to receive high definition white-light (HDWL) colonoscopy, with or without a real-time deep-learning CADe by endoscopists with baseline ADR > 25 %. The primary outcome was ADR. Secondary outcomes were mean number of adenomas per colonoscopy (APC) and advanced adenoma detection rate (advanced-ADR). Subgroup analysis according to baseline endoscopists' ADR (≤ 40 %, 41 %-45 %, ≥ 46 %) was also performed. RESULTS: 800 individuals (median age 61.0 years [interquartile range 55-67]; 409 men) were included: 405 underwent CADe-assisted colonoscopy and 395 underwent HDWL colonoscopy alone. ADR and APC were significantly higher in the CADe group than in the HDWL arm: ADR 53.6 % (95 %CI 48.6 %-58.5 %) vs. 45.3 % (95 %CI 40.3 %-50.45 %; RR 1.18; 95 %CI 1.03-1.36); APC 1.13 (SD 1.54) vs. 0.90 (SD 1.32; P  = 0.03). No significant difference in advanced-ADR was found (18.5 % [95 %CI 14.8 %-22.6 %] vs. 15.9 % [95 %CI 12.5 %-19.9 %], respectively). An increase in ADR was observed in all endoscopist groups regardless of baseline ADR. CONCLUSIONS: Incorporating CADe significantly increased ADR and APC in the framework of a FIT-based CRC screening program. The impact of CADe appeared to be consistent regardless of endoscopist baseline ADR.

Dye-based chromoendoscopy for the detection of colorectal neoplasia: meta-analysis of randomized controlled trials.

BACKGROUND AND AIMS: Dye-based chromoendoscopy (DBC) could be effective in increasing the adenoma detection rate (ADR) in patients undergoing colonoscopy, but the technique is time-consuming and its uptake is limited. We aimed to assess the effect of DBC on ADR based on available randomized controlled trials (RCTs). METHODS: Four databases were searched up to April 2022 for RCTs comparing DBC with conventional colonoscopy (CC) in terms of ADR, advanced ADR, and sessile serrated adenoma detection rate as well as the mean adenomas per patient and non-neoplastic lesions. Relative risk (RR) for dichotomous outcomes and mean difference (MD) for continuous outcomes were calculated using random-effect models. The I2 test was used for quantifying heterogeneity. Risk of bias was evaluated with the Cochrane tool. RESULTS: Overall, 10 RCTs (5334 patients) were included. Indication for colonoscopy was screening or surveillance (3 studies) and mixed (7 studies). Pooled ADR was higher in the DBC group versus the CC group (95% CI, 48.1% [41.4%-54.8%] vs 39.3% [33.5%-46.4%]; RR, 1.20 [1.11-1.29]), with low heterogeneity (I2 = 29%). This effect was consistent for advanced ADR (RR, 1.21 [1.03-1.42]; I2 = .0%), sessile serrated adenomas (6.1% vs 3.5%; RR, 1.68 [1.15-2.47]; I2 = 9.8%), and mean adenomas per patient (MD, .24 [.17-.31]) overall and in the right-sided colon (MD, .28 [.14-.43]). A subgroup analysis considering only trials using high-definition white-light endoscopy reduced the heterogeneity while still showing a significant increase in adenoma detection with DBC: 51.6% (95% confidence interval [CI], 47.1%-56.1%) and 59.1% (95% CI, 54.7-63.3%), RR = 1.14 (95% CI, 1.06-1.23), P = .0004, I2 = .0%, P = .50. CONCLUSIONS: Meta-analysis of RCTs showed that DBC increases key quality parameters in colonoscopy, supporting its use in everyday clinical practice.

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools. METHODS: We conducted Markov model microsimulation of using colonoscopy with and without AI for colorectal cancer screening for individuals at average risk (no personal or family history of colorectal cancer, adenomas, inflammatory bowel disease, or hereditary colorectal cancer syndrome). We ran the microsimulation in a hypothetical cohort of 100 000 individuals in the USA aged 50-100 years. The primary analysis investigated screening colonoscopy with versus without AI every 10 years starting at age 50 years and finishing at age 80 years, with follow-up until age 100 years, assuming 60% screening population uptake. In secondary analyses, we modelled once-in-life screening colonoscopy at age 65 years in adults aged 50-79 years at average risk for colorectal cancer. Post-polypectomy surveillance followed the simplified current guideline. Costs of AI tools and cost for downstream treatment of screening detected disease were estimated with 3% annual discount rates. The main outcome measures included the incremental effect of AI-assisted colonoscopy versus standard (no-AI) colonoscopy on colorectal cancer incidence and mortality, and cost-effectiveness of screening projected for the average risk screening US population. FINDINGS: In the primary analyses, compared with no screening, the relative reduction of colorectal cancer incidence with screening colonoscopy without AI tools was 44·2% and with screening colonoscopy with AI tools was 48·9% (4·8% incremental gain). Compared with no screening, the relative reduction in colorectal cancer mortality with screening colonoscopy with no AI was 48·7% and with screening colonoscopy with AI was 52·3% (3·6% incremental gain). AI detection tools decreased the discounted costs per screened individual from $3400 to $3343 (a saving of $57 per individual). Results were similar in the secondary analyses modelling once-in-life colonoscopy. At the US population level, the implementation of AI detection during screening colonoscopy resulted in yearly additional prevention of 7194 colorectal cancer cases and 2089 related deaths, and a yearly saving of US$290 million. INTERPRETATION: Our findings suggest that implementation of AI detection tools in screening colonoscopy is a cost-saving strategy to further prevent colorectal cancer incidence and mortality. FUNDING: European Commission and Japan Society of Promotion of Science.

The endoscopic ultrasound features of pancreatic fluid collections and their impact on therapeutic decisions: an interobserver agreement study.

BACKGROUND: A validated classification of endoscopic ultrasound (EUS) morphological characteristics and consequent therapeutic intervention(s) in pancreatic and peripancreatic fluid collections (PFCs) is lacking. We performed an interobserver agreement study among expert endosonographers assessing EUS-related PFC features and the therapeutic approaches used. METHODS: 50 EUS videos of PFCs were independently reviewed by 12 experts and evaluated for PFC type, percentage solid component, presence of infection, recognition of and communication with the main pancreatic duct (MPD), stent choice for drainage, and direct endoscopic necrosectomy (DEN) performance and timing. The Gwet's AC1 coefficient was used to assess interobserver agreement. RESULTS: A moderate agreement was found for lesion type (AC1, 0.59), presence of infection (AC1, 0.41), and need for DEN (AC1, 0.50), while fair or poor agreements were stated for percentage solid component (AC1, 0.15) and MPD recognition (AC1, 0.31). Substantial agreement was rated for ability to assess PFC-MPD communication (AC1, 0.69), decision between placing a plastic versus lumen-apposing metal stent (AC1, 0.62), and timing of DEN (AC1, 0.75). CONCLUSIONS: Interobserver agreement between expert endosonographers regarding morphological features of PFCs appeared suboptimal, while decisions on therapeutic approaches seemed more homogeneous. Studies to achieve standardization of the diagnostic endosonographic criteria and therapeutic approaches to PFCs are warranted.

Performance of a new integrated computer-assisted system (CADe/CADx) for detection and characterization of colorectal neoplasia.

BACKGROUND: Use of artificial intelligence may increase detection of colorectal neoplasia at colonoscopy by improving lesion recognition (CADe) and reduce pathology costs by improving optical diagnosis (CADx). METHODS: A multicenter library of ≥ 200 000 images from 1572 polyps was used to train a combined CADe/CADx system. System testing was performed on two independent image sets (CADe: 446 with polyps, 234 without; CADx: 267) from 234 polyps, which were also evaluated by six endoscopists (three experts, three non-experts). RESULTS: CADe showed sensitivity, specificity, and accuracy of 92.9 %, 90.6 %, and 91.7 %, respectively. Experts showed significantly higher accuracy and specificity, and similar sensitivity, while non-experts + CADe showed comparable sensitivity but lower specificity and accuracy than CADe and experts. CADx showed sensitivity, specificity, and accuracy of 85.0 %, 79.4 %, and 83.6 %, respectively. Experts showed comparable performance, whereas non-experts + CADx showed comparable accuracy but lower specificity than CADx and experts. CONCLUSIONS: The high accuracy shown by CADe and CADx was similar to that of experts, supporting further evaluation in a clinical setting. When using CAD, non-experts achieved a similar performance to experts, with suboptimal specificity.

Artificial intelligence and colonoscopy experience: lessons from two randomised trials.

BACKGROUND AND AIMS: Artificial intelligence has been shown to increase adenoma detection rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which extent this effect may be related to physician experience is not known. We performed a randomised trial with colonoscopists in their qualification period (AID-2) and compared these data with a previously published randomised trial in expert endoscopists (AID-1). METHODS: In this prospective, randomised controlled non-inferiority trial (AID-2), 10 non-expert endoscopists (<2000 colonoscopies) performed screening/surveillance/diagnostic colonoscopies in consecutive 40-80 year-old subjects using high-definition colonoscopy with or without a real-time deep-learning computer-aided detection (CADe) (GI Genius, Medtronic). The primary outcome was ADR in both groups with histology of resected lesions as reference. In a post-hoc analysis, data from this randomised controlled trial (RCT) were compared with data from the previous AID-1 RCT involving six experienced endoscopists in an otherwise similar setting. RESULTS: In 660 patients (62.3±10 years; men/women: 330/330) with equal distribution of study parameters, overall ADR was higher in the CADe than in the control group (53.3% vs 44.5%; relative risk (RR): 1.22; 95% CI: 1.04 to 1.40; p<0.01 for non-inferiority and p=0.02 for superiority). Similar increases were seen in adenoma numbers per colonoscopy and in small and distal lesions. No differences were observed with regards to detection of non-neoplastic lesions. When pooling these data with those from the AID-1 study, use of CADe (RR 1.29; 95% CI: 1.16 to 1.42) and colonoscopy indication, but not the level of examiner experience (RR 1.02; 95% CI: 0.89 to 1.16) were associated with ADR differences in a multivariate analysis. CONCLUSIONS: In less experienced examiners, CADe assistance during colonoscopy increased ADR and a number of related polyp parameters as compared with the control group. Experience appears to play a minor role as determining factor for ADR. TRIAL REGISTRATION NUMBER: NCT:04260321.

A prospective study on quality in endoscopic retrograde cholangiopancreatography (ERCP): trend in Italy from the REQUEST study.

Background and study aims Endoscopic retrograde cholangiopancreatography (ERCP) is a complex procedure with a relatively high rate of adverse events. Data on training of operators and fulfillment of quality indicators in Italy are scarce. The goal of this study was to assess the overall quality of ERCP in Italy compared to international standards. Patients and methods This was a prospective, observational study from different Italian centers performing ERCP. Operators answered a questionnaire, then recorded data on ERCPs over a 1-to 3-month period. Results Nineteen Italian centers participated in the study. The most common concern of operators about training was the lack of structured programs. Seven/19 centers routinely used conscious sedation for ERCP. Forty-one experienced operators and 21 trainees performed 766 ERCPs: a successful deep biliary cannulation in native-papilla patients was achieved in 95.1 % of cases; the post-ERCP pancreatitis (PEP) rate was 5.4 % in native-papilla patients; cholangitis rate was 1.0 %; bleeding and perforation occurred in 2.7 % and 0.4 % of the patients, respectively. Conclusions This study revealed that, overall, ERCP is performed in the participating Italian centers meeting good quality standards, but structured training and sedation practice are still subpar. The bleeding and perforation rate slightly exceeded the American Society of Gastrointestinal Endoscopy indicator targets but they are comparable to the reported rates from other international surveys.

Endoscopic Ultrasound-guided Fine-needle Biopsy With or Without Rapid On-site Evaluation for Diagnosis of Solid Pancreatic Lesions: A Randomized Controlled Non-Inferiority Trial.

BACKGROUND AND AIMS: The benefit of rapid on-site evaluation (ROSE) on the diagnostic accuracy of endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) has never been evaluated in a randomized study. This trial aimed to test the hypothesis that in solid pancreatic lesions (SPLs), diagnostic accuracy of EUS-FNB without ROSE was not inferior to that of EUS-FNB with ROSE. METHODS: A noninferiority study (noninferiority margin, 5%) was conducted at 14 centers in 8 countries. Patients with SPLs requiring tissue sampling were randomly assigned (1:1) to undergo EUS-FNB with or without ROSE using new-generation FNB needles. The touch-imprint cytology technique was used to perform ROSE. The primary endpoint was diagnostic accuracy, and secondary endpoints were safety, tissue core procurement, specimen quality, and sampling procedural time. RESULTS: Eight hundred patients were randomized over an 18-month period, and 771 were analyzed (385 with ROSE and 386 without). Comparable diagnostic accuracies were obtained in both arms (96.4% with ROSE and 97.4% without ROSE, P = .396). Noninferiority of EUS-FNB without ROSE was confirmed with an absolute risk difference of 1.0% (1-sided 90% confidence interval, -1.1% to 3.1%; noninferiority P < .001). Safety and sample quality of histologic specimens were similar in both groups. A significantly higher tissue core rate was obtained by EUS-FNB without ROSE (70.7% vs. 78.0%, P = .021), with a significantly shorter mean sampling procedural time (17.9 ± 8.8 vs 11.7 ± 6.0 minutes, P < .0001). CONCLUSIONS: EUS-FNB demonstrated high diagnostic accuracy in evaluating SPLs independently on execution of ROSE. When new-generation FNB needles are used, ROSE should not be routinely recommended. (ClinicalTrial.gov number NCT03322592.).