Withdrawal time in excellent or very poor bowel preparation qualities

AIM: To evaluate association(s) between withdrawal time and polyp detection in various bowel preparation qualities. METHODS: Retrospective cohort analysis of screening colonoscopies performed between January 2005 and June 2011 for patients with average risk of colorectal cancer. Exclusion criteria included patients with a personal history of adenomatous polyps or colon cancer, prior colonic resection, significant family history of colorectal cancer, screening colonoscopy after other abnormal screening tests such as flexible sigmoidoscopy or barium enema, and screening colonoscopies during in-patient care. All procedures were performed or directly supervised by gastroenterologists. Main measurements were number of colonic segments with polyps and total number of colonic polyps.RESULTS: Multivariate analysis of 8331 colonosco-pies showed longer withdrawal time was associated with more colonic segments with polyps in good(adjusted OR = 1.16; 95%CI: 1.13-1.19), fair(OR = 1.13; 95%CI: 1.10-1.17), and poor(OR = 1.18; 95%CI: 1.11-1.26) bowel preparation qualities. A higher number of total polyps was associated with longer withdrawal time in good(OR = 1.15; 95%CI: 1.13-1.18), fair(OR = 1.13; 95%CI: 1.10-1.16), and poor(OR = 1.20; 95%CI: 1.13-1.29) bowel preparation qualities. Longer withdrawal time was not associated with more colonic segments with polyps or greater number of colonic polyps in bowel preparations with excellent(OR = 1.07, 95%CI: 0.99-1.26; OR = 1.11, 95%CI: 0.99-1.24, respectively) and very poor(OR = 1.02, 95%CI: 0.99-1.12; OR = 1.05, 95%CI: 0.99-1.10, respectively) qualities.CONCLUSION: Longer withdrawal time is not associated with higher polyp number detected in colonoscopies with excellent or very poor bowel preparation quality.

Colometer:A real-time quality feedback system for screening colonoscopy

AIM:To investigate the performance of a new software-based colonoscopy quality assessment system.METHODS:The software-based system employs a novel image processing algorithm which detects the levels of image clarity,withdrawal velocity,and level of the bowel preparation in a real-time fashion from live video signal.Threshold levels of image blurriness and the withdrawal velocity below which the visualization could be considered adequate have initially been determined arbitrarily by review of sample colonoscopy videos by two experienced endoscopists.Subsequently,an overall colonoscopy quality rating was computed based on the percentage of the withdrawal time with adequate visualization(scored 1-5;1,when the percentage was 1%-20%;2,when the percentage was 21%-40%,etc.).In order to test the proposed velocity and blurriness thresholds,screening colonoscopy withdrawal videos from a specialized ambulatory colon cancer screening center were collected,automatically processed and rated.Quality ratings on the withdrawal were compared to the insertion in the same patients.Then,3 experienced endoscopists reviewed the collected videos in a blinded fashion and rated the overall quality of each withdrawal(scored 1-5;1,poor;3,average;5,excellent) based on 3 major aspects:image quality,colon preparation,and withdrawal velocity.The automated quality ratings were compared to the averaged endoscopist quality ratings using Spearman correlation coefficient.RESULTS:Fourteen screening colonoscopies were assessed.Adenomatous polyps were detected in 4/14(29%) of the collected colonoscopy video samples.As a proof of concept,the Colometer software rated colonoscope withdrawal as having better visualization than the insertion in the 10 videos which did not have any polyps(average percent time with adequate visualization:79% ± 5% for withdrawal and 50% ± 14% for insertion,P < 0.01).Withdrawal times during which no polyps were removed ranged from 4-12 min.The median quality rating from the automated system and the reviewers was 3.45 [interquartile range(IQR),3.1-3.68] and 3.00(IQR,2.33-3.67) respectively for all colonoscopy video samples.The automated rating revealed a strong correlation with the reviewer's rating(ρ coefficient= 0.65,P = 0.01).There was good correlation of the automated overall quality rating and the mean endoscopist withdrawal speed rating(Spearman r coefficient= 0.59,P = 0.03).There was no correlation of automated overall quality rating with mean endoscopists image quality rating(Spearman r coefficient= 0.41,P = 0.15).CONCLUSION:The results from a novel automated real-time colonoscopy quality feedback system strongly agreed with the endoscopists' quality assessments.Further study is required to validate this approach.

Improving polyp detection at colonoscopy: Non-technological techniques

Colonoscopy and polypectomy remain the gold standard investigation for the detection and prevention of colorectal cancer.Halting the progression of colonic adenoma through adequate detection of pre-cancerous lesions interrupts the progression to carcinoma.The adenoma detection rate is a key performance indicator.Increasing adenoma detection rates are associated with reducing rates of interval colorectal cancer.Endoscopists with high baseline adenoma detection rate have a meticulous technique during colonoscopy withdrawal that improves their adenoma detection.This minireview article summarizes the evidence on the following simple operator techniques and their effects on the adenoma detection rate;minimum withdrawal times,dynamic patient position change and proximal colon retroflexion.

Artificial intelligence fails to improve colonoscopy quality:A single centre retrospective cohort study

BACKGROUND Limited data currently exists on the clinical utility of Artificial Intelligence Assisted Colonoscopy(AIAC)outside of clinical trials.AIM To evaluate the impact of AIAC on key markers of colonoscopy quality compared to conventional colonoscopy(CC).METHODS This single-centre retrospective observational cohort study included all patients undergoing colonoscopy at a secondary centre in Brisbane,Australia.CC outcomes between October 2021 and October 2022 were compared with AIAC outcomes after the introduction of the Olympus Endo-AID module from October 2022 to January 2023.Endoscopists who conducted over 50 procedures before and after AIAC introduction were included.Procedures for surveillance of inflammatory bowel disease were excluded.Patient demographics,proceduralist specialisation,indication for colonoscopy,and colonoscopy quality metrics were collected.Adenoma detection rate(ADR)and sessile serrated lesion detection rate(SSLDR)were calculated for both AIAC and CC.RESULTS The study included 746 AIAC procedures and 2162 CC procedures performed by seven endoscopists.Baseline patient demographics were similar,with median age of 60 years with a slight female predominance(52.1%).Procedure indications,bowel preparation quality,and caecal intubation rates were comparable between groups.AIAC had a slightly longer withdrawal time compared to CC,but the difference was not statistically significant.The introduction of AIAC did not significantly change ADR(52.1%for AIAC vs 52.6%for CC,P=0.91)or SSLDR(17.4%for AIAC vs 18.1%for CC,P=0.44).CONCLUSION The implementation of AIAC failed to improve key markers of colonoscopy quality,including ADR,SSLDR and withdrawal time.Further research is required to assess the utility and cost-efficiency of AIAC for high performing endoscopists.

Time to Withdraw?

As the new year progresses, policymakers around the world are asking themselves the same question: Is it time to halt stimulus policies? But the question seems almost unanswerable now as signs of