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Training methods in optical diagnosis and characterization of colorectal polyps: a systematic review and meta-analysis.

ABSTRACT: Background and study aims Correct optical diagnosis of colorectal polyps is crucial to implement a resect and discard strategy. Training methods have been proposed to reach recommended optical diagnosis thresholds. The aim of our study was to present a systematic review and meta-analysis on optical diagnosis training. Methods PubMed/Medline and Cochrane databases were searched between 1980 and October 2019 for studies reporting outcomes on optical diagnosis training of colorectal polyps. The primary outcome was optical diagnosis accuracy compared to histological analysis pre-training and post-training intervention. Subgroup analyses of experienced/trainee endoscopists, training methods, and small/diminutive polyps were included. Results Overall, 16 studies met inclusion criteria, analyzing the impact of training on 179 endoscopists. Pre-training accuracy was 70.3 % (6416/9131 correct diagnoses) whereas post-training accuracy was 81.6 % (7416/9213 correct diagnoses) (risk ratio [RR] 1.17; 95 % confidence interval [CI]: 1.09-1.24, P < 0.001). In experienced endoscopists, accuracy improved from 69.8 % (3771/5403 correct diagnoses) to 82.4 % (4521/5485 correct diagnoses) (RR 1.20; 95 % CI: 1.11-1.29, P < 0.001). Among trainees, accuracy improved from 69.6 % (2645/3803 correct diagnoses) to 78.8 % (2995/3803 correct diagnoses) (RR 1.14; 95 % CI 1.06-1.24, P < 0.001). In the small/diminutive polyp subgroup, accuracy improved from 68.1 % (3549/5214 correct diagnoses) to 77.1 % (4022/5214 correct diagnoses) in (RR 1.16 95 % CI 1.08-1.24 P < 0.001). On meta-regression analysis, the improvement in accuracy did not differ between computerized vs. didactic training approaches for experienced ( P = 0.792) and trainee endoscopists ( P = 0.312). Conclusions Optical diagnosis training is effective in improving accuracy of histology prediction in colorectal polyps. Didactic and computer-based training show comparable effectiveness in improving diagnostic accuracy.

SUBMITTER: Smith SCL

PROVIDER: S-EPMC8062231 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundColonoscopy reduces the incidence of colorectal cancer (CRC) by allowing detection and resection of neoplastic polyps. Evidence shows that many small polyps are missed on a single colonoscopy. There has been a successful adoption of artificial intelligence (AI) technologies to tackle the issues around missed polyps and as tools to increase the adenoma detection rate (ADR).ObjectiveThe aim of this review was to examine the diagnostic accuracy of AI-based technologies in assessing colorectal polyps.MethodsA comprehensive literature search was undertaken using the databases of Embase, MEDLINE, and the Cochrane Library. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Studies reporting the use of computer-aided diagnosis for polyp detection or characterization during colonoscopy were included. Independent proportions and their differences were calculated and pooled through DerSimonian and Laird random-effects modeling.ResultsA total of 48 studies were included. The meta-analysis showed a significant increase in pooled polyp detection rate in patients with the use of AI for polyp detection during colonoscopy compared with patients who had standard colonoscopy (odds ratio [OR] 1.75, 95% CI 1.56-1.96; P<.001). When comparing patients undergoing colonoscopy with the use of AI to those without, there was also a significant increase in ADR (OR 1.53, 95% CI 1.32-1.77; P<.001).ConclusionsWith the aid of machine learning, there is potential to improve ADR and, consequently, reduce the incidence of CRC. The current generation of AI-based systems demonstrate impressive accuracy for the detection and characterization of colorectal polyps. However, this is an evolving field and before its adoption into a clinical setting, AI systems must prove worthy to patients and clinicians.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42020169786; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020169786.

Project description:Several studies have evaluated the utility of double-balloon enteroscopy (DBE) and capsule endoscopy (CE) for patients with small-bowel disease showing inconsistent results. The aim of this study was to determine the sensitivity and specificity of overtube-assisted enteroscopy (OAE) as well as the diagnostic concordance between OAE and CE for small-bowel polyps and tumors.We conducted a systematic review and meta-analysis of studies in which the results of OAE were compared with the results of CE for the evaluation of small-bowel polyps and tumors. When data for surgically resected lesions were available, the histopathological results of OAE and surgical specimens were compared. The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for the diagnosis of small-bowel polyps and tumors were analyzed. Secondarily, the rates of diagnostic concordance and discordance between OAE and CE were calculated.There were 15 full-length studies with a total of 821 patients that met the inclusion criteria. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were as follows: 0.89 (95 % confidence interval [CI] 0.84 - 0.93), with heterogeneity χ(2) = 41.23 (P = 0.0002) and inconsistency (I (2)) = 66.0 %; 0.97 (95 %CI 0.95 - 0.98), with heterogeneity χ(2) = 45.27 (P = 0.07) and inconsistency (I (2)) = 69.1 %; 16.61 (95 %CI 3.74 - 73.82), with heterogeneity Cochrane's Q = 225.19 (P < 0.01) and inconsistency (I (2)) = 93.8 %; and 0.14 (95 %CI 0.05 - 0.35), with heterogeneity Cochrane's Q = 81.01 (P < .01) and inconsistency (I (2)) = 82.7 %, respectively. A summary receiver operating characteristic curve (SROC) curve was constructed, and the area under the curve (AUC) was 0.97.OAE is an accurate test for the detection of small-bowel polyps and tumors. OAE and CE have a high diagnostic concordance rate for small-bowel polyps and tumors. This study was registered in the PROSPERO international database (www.crd.york.ac.uk/prospero/) with the study number CRD42015016000.

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Training methods in optical diagnosis and characterization of colorectal polyps: a systematic review and meta-analysis.

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