Search

Background: Recent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convolutional neural networks, have allowed for real-time AI-aided detection of polyps with higher sensitivity than the average endoscopist. However, not all endoscopists welcome the advent of AI systems. Methods: We conducted a survey on the knowledge of AI, perceptions of AI in medicine, and behaviours regarding use of AI-aided colonoscopy, in a single centre 2 months after the implementation of Medtronic's GI Genius in colonoscopy. We obtained a response rate of 66.7% (16/24) amongst consultant-grade endoscopists. Fisher's exact test was used to calculate the significance of correlations. Results: Knowledge of AI varied widely amongst endoscopists. Most endoscopists were optimistic about AI's capabilities in performing objective administrative and clinical tasks, but reserved about AI providing personalised, empathetic care. 68.8% (n = 11) of endoscopists agreed or strongly agreed that GI Genius should be used as an adjunct in colonoscopy. In analysing the 31.3% (n = 5) of endoscopists who disagreed or were ambivalent about its use, there was no significant correlation with their knowledge or perceptions of AI, but a significant number did not enjoy using the programme (p-value = 0.0128) and did not think it improved the quality of colonoscopy (p-value = 0.033). Conclusions: Acceptance of AI-aided colonoscopy systems is more related to the endoscopist's experience with using the programme, rather than general knowledge or perceptions towards AI. Uptake of such systems will rely greatly on how the device is delivered to the end user. [ABSTRACT FROM AUTHOR]

Background: The Erector Spinae Plane (ESP) block is a recent development in the field of regional anaesthesia and has been increasingly explored for abdominal surgeries to reduce opioid use and improve pain control. Colorectal cancer is the commonest cancer in multi-ethnic Singapore and requires surgery for curative treatment. ESP is a promising alternative in colorectal surgeries, but few studies have evaluated its efficacy in such surgeries. Therefore, this study aims to evaluate the use of ESP blocks in laparoscopic colorectal surgeries to establish its safety and efficacy in this field. Methods: A prospective two-armed interventional cohort study comparing T8–T10 ESP blocks with conventional multimodal intravenous analgesia for laparoscopic colectomies was conducted in a single institution in Singapore. The decision for doing an ESP block versus conventional multimodal intravenous analgesia was made by a consensus between the attending surgeon and anesthesiologist. Outcomes measured were total intra-operative opioid consumption, post-operative pain control and patient outcome. Post-operative pain control was measured by pain score, analgesia use, and amount of opioids consumed. Patient outcome was determined by presence of ileus. Results: A total of 146 patients were included, of which 30 patients received an ESP block. Overall, the ESP group had a significantly lower median opioid usage both intra-operatively and post-operatively (p = 0.031). Fewer patients required patient-controlled analgesia and rescue analgesia post-operatively for pain control (p < 0.001) amongst the ESP group. Pain scores were similar and post-operative ileus was absent in both groups. Multivariate analysis found that the ESP block had an independent effect on reducing intra-opioid consumption (p = 0.014). Multivariate analysis of post-operative opioid use and pain scores did not yield statistically significant results. Conclusions: The ESP block was an effective alternative regional anaesthesia for colorectal surgery that reduced intra-operative and post-operative opioid use while attaining satisfactory pain control. [ABSTRACT FROM AUTHOR]

Background: Colonoscopy is a mainstay to detect premalignant neoplastic lesions in the colon. Real-time Artificial Intelligence (AI)-aided colonoscopy purportedly improves the polyp detection rate, especially for small flat lesions. The aim of this study is to evaluate the performance of real-time AI-aided colonoscopy in the detection of colonic polyps. Methods: A prospective single institution cohort study was conducted in Singapore. All real-time AI-aided colonoscopies, regardless of indication, performed by specialist-grade endoscopists were anonymously recorded from July to September 2021 and reviewed by 2 independent authors (FHK, JL). Sustained detection of an area by the program was regarded as a "hit". Histology for the polypectomies were reviewed to determine adenoma detection rate (ADR). Individual endoscopist's performance with AI were compared against their baseline performance without AI endoscopy. Results: A total of 24 (82.8%) endoscopists participated with 18 (62.1%) performing ≥ 5 AI-aided colonoscopies. Of the 18, 72.2% (n = 13) were general surgeons. During that 3-months period, 487 "hits" encountered in 298 colonoscopies. Polypectomies were performed for 51.3% and 68.4% of these polypectomies were adenomas on histology. The post-intervention median ADR was 30.4% was higher than the median baseline polypectomy rate of 24.3% (p = 0.02). Of the adenomas excised, 14 (5.6%) were sessile serrated adenomas. Of those who performed ≥ 5 AI-aided colonoscopies, 13 (72.2%) had an improvement of ADR compared to their polypectomy rate before the introduction of AI, of which 2 of them had significant improvement. Conclusions: Real-time AI-aided colonoscopy have the potential to improved ADR even for experienced endoscopists and would therefore, improve the quality of colonoscopy. [ABSTRACT FROM AUTHOR]