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Artificial intelligence in colorectal surgery: an AI-powered systematic review

Spinelli A, Carrano FM, Laino ME, Andreozzi M, Koleth G, Hassan C, et al.

Tech Coloproctol, 2023 Aug;27(8):615-629.
PMID: 36805890 DOI: 10.1007/s10151-023-02772-8

Artificial intelligence (AI) has the potential to revolutionize surgery in the coming years. Still, it is essential to clarify what the meaningful current applications are and what can be reasonably expected. This AI-powered review assessed the role of AI in colorectal surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of PubMed, Embase, Scopus, Cochrane Library databases, and gray literature was conducted on all available articles on AI in colorectal surgery (from January 1 1997 to March 1 2021), aiming to define the perioperative applications of AI. Potentially eligible studies were identified using novel software powered by natural language processing (NLP) and machine learning (ML) technologies dedicated to systematic reviews. Out of 1238 articles identified, 115 were included in the final analysis. Available articles addressed the role of AI in several areas of interest. In the preoperative phase, AI can be used to define tailored treatment algorithms, support clinical decision-making, assess the risk of complications, and predict surgical outcomes and survival. Intraoperatively, AI-enhanced surgery and integration of AI in robotic platforms have been suggested. After surgery, AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway. Additional areas of applications included the assessment of patient-reported outcomes, automated pathology assessment, and research. Available data on these aspects are limited, and AI in colorectal surgery is still in its infancy. However, the rapid evolution of technologies makes it likely that it will increasingly be incorporated into everyday practice.
Fulltext Endoscopic Biliary Drainage in Surgically Altered Anatomy

Spadaccini M, Giacchetto CM, Fiacca M, Colombo M, Andreozzi M, Carrara S, et al.

Diagnostics (Basel), 2023 Dec 08;13(24).
PMID: 38132207 DOI: 10.3390/diagnostics13243623

Endoscopic retrograde cholangiopancreatography (ERCP) is considered the preferred method for managing biliary obstructions. However, the prevalence of surgically modified anatomies often poses challenges, making the standard side-viewing duodenoscope unable to reach the papilla in most cases. The increasing instances of surgically altered anatomies (SAAs) result from higher rates of bariatric procedures and surgical interventions for pancreatic malignancies. Conventional ERCP with a side-viewing endoscope remains effective when there is continuity between the stomach and duodenum. Nonetheless, percutaneous transhepatic biliary drainage (PTBD) or surgery has historically been used as an alternative for biliary drainage in malignant or benign conditions. The evolving landscape has seen various endoscopic approaches tailored to anatomical variations. Innovative methodologies such as cap-assisted forward-viewing endoscopy and enteroscopy have enabled the performance of ERCP. Despite their utilization, procedural complexities, prolonged durations, and accessibility challenges have emerged. As a result, there is a growing interest in novel enteroscopy and endoscopic ultrasound (EUS) techniques to ensure the overall success of endoscopic biliary drainage. Notably, EUS has revolutionized this domain, particularly through several techniques detailed in the review. The rendezvous approach has been pivotal in this field. The antegrade approach, involving biliary tree puncturing, allows for the validation and treatment of strictures in an antegrade fashion. The EUS-transmural approach involves connecting a tract of the biliary system with the GI tract lumen. Moreover, the EUS-directed transgastric ERCP (EDGE) procedure, combining EUS and ERCP, presents a promising solution after gastric bypass. These advancements hold promise for expanding the horizons of comprehensive and successful biliary drainage interventions, laying the groundwork for further advancements in endoscopic procedures.
Artificial intelligence in gastroenterology: Where are we heading?

Koleth G, Emmanue J, Spadaccini M, Mascagni P, Khalaf K, Mori Y, et al.

Endosc Int Open, 2022 Nov;10(11):E1474-E1480.
PMID: 36397868 DOI: 10.1055/a-1907-6569

Background and study aims Artificial intelligence (AI) is set to impact several fields within gastroenterology. In gastrointestinal endoscopy, AI-based tools have translated into clinical practice faster than expected. We aimed to evaluate the status of research for AI in gastroenterology while predicting its future applications. Methods All studies registered on Clinicaltrials.gov up to November 2021 were analyzed. The studies included used AI in gastrointestinal endoscopy, inflammatory bowel disease (IBD), hepatology, and pancreatobiliary diseases. Data regarding the study field, methodology, endpoints, and publication status were retrieved, pooled, and analyzed to observe underlying temporal and geographical trends. Results Of the 103 study entries retrieved according to our inclusion/exclusion criteria, 76 (74 %) were based on AI application to gastrointestinal endoscopy, mainly for detection and characterization of colorectal neoplasia (52/103, 50 %). Image analysis was also more frequently reported than data analysis for pancreaticobiliary (six of 10 [60 %]), liver diseases (eight of nine [89 %]), and IBD (six of eight [75 %]). Overall, 48 of 103 study entries (47 %) were interventional and 55 (53 %) observational. In 2018, one of eight studies (12.5 %) were interventional, while in 2021, 21 of 34 (61.8 %) were interventional, with an inverse ratio between observational and interventional studies during the study period. The majority of the studies were planned as single-center (74 of 103 [72 %]) and more were in Asia (45 of 103 [44 %]) and Europe (44 of 103 [43 %]). Conclusions AI implementation in gastroenterology is dominated by computer-aided detection and characterization of colorectal neoplasia. The timeframe for translational research is characterized by a swift conversion of observational into interventional studies.
Comparing Number and relevance Of false activations between two Artificial Intelligence CADe SystEms: the NOISE study

Spadaccini M, Hassan C, Alfarone L, Da Rio L, Maselli R, Carrara S, et al.

Gastrointest Endosc, 2022 Jan 04.
PMID: 34995639 DOI: 10.1016/j.gie.2021.12.031

BACKGROUND AND AIMS: Artificial Intelligence (AI) has been shown to be effective in polyp detection, and multiple computer-aided detection (CADe) system have been developed. False positive (FP) activation emerged as a possible way to benchmark CADe performances in clinical practice. The aim of this study is to validate a previously developed classification of FP comparing the performances of different brands of approved CADe systems.
METHODS: We compared 2 different consecutive video libraries (40 video per arm) collected at Humanitas Research Hospital with 2 different CADe system brands (CADe A and CADe B). For each video, the number of CADe false activations, the cause and the time spent by the endoscopist to examine the area erroneously highlighted were reported. The FP activations were classified according to the previously developed classification of false positives (the NOISE classification) according to their cause and relevance.
RESULTS: A total of 1021 FP activations were registered across the 40 videos of the Group A (25.5±12.2 FPs per colonoscopy). A comparable number of FPs were identified in the Group B (n=1028, mean:25.7±13.2 FPs per colonoscopy) (p 0.53). Among them, 22.9±9.9 (89.8%, Group A), and 22.1±10.0 (86.0%, Group B) were due to artifacts from bowel wall. Conversely, 2.6±1.9 (10.2%) and 3.5±2.1 (14%) were caused by bowel content (p 0.45). Within the Group A each false activation required 0.2±0.9 seconds, with 1.6±1.0 (6.3%) FPs requiring additional time for endoscopic assessment. Comparable results were reported within the Group B with 0.2±0.8 seconds spent per false activation and 1.8±1.2 FPs per colonoscopy requiring additional inspection.
CONCLUSION: The use of a standardized nomenclature permitted to provide comparable results with either of the 2 recently approved CADe systems.
Fulltext The Effect of Regularly Dosed Acetaminophen vs No Acetaminophen on Renal Function in Plasmodium knowlesi Malaria (PACKNOW): A Randomized, Controlled Trial

Cooper DJ, Grigg MJ, Plewes K, Rajahram GS, Piera KA, William T, et al.

Clin Infect Dis, 2022 Oct 12;75(8):1379-1388.
PMID: 35180298 DOI: 10.1093/cid/ciac152

BACKGROUND: Acetaminophen inhibits cell-free hemoglobin-induced lipid peroxidation and improves renal function in severe falciparum malaria but has not been evaluated in other infections with prominent hemolysis, including Plasmodium knowlesi malaria.
METHODS: PACKNOW was an open-label, randomized, controlled trial of acetaminophen (500 mg or 1000 mg every 6 hours for 72 hours) vs no acetaminophen in Malaysian patients aged ≥5 years with knowlesi malaria of any severity. The primary end point was change in creatinine at 72 hours. Secondary end points included longitudinal changes in creatinine in patients with severe malaria or acute kidney injury (AKI), stratified by hemolysis.
RESULTS: During 2016-2018, 396 patients (aged 12-96 years) were randomized to acetaminophen (n = 199) or no acetaminophen (n = 197). Overall, creatinine fell by a mean (standard deviation) 14.9% (18.1) in the acetaminophen arm vs 14.6% (16.0) in the control arm (P = .81). In severe disease, creatinine fell by 31.0% (26.5) in the acetaminophen arm vs 20.4% (21.5) in the control arm (P = .12), and in those with hemolysis by 35.8% (26.7) and 19% (16.6), respectively (P = .07). No difference was seen overall in patients with AKI; however, in those with AKI and hemolysis, creatinine fell by 34.5% (20.7) in the acetaminophen arm vs 25.9% (15.8) in the control arm (P = .041). Mixed-effects modeling demonstrated a benefit of acetaminophen at 72 hours (P = .041) and 1 week (P = .002) in patients with severe malaria and with AKI and hemolysis (P = .027 and P = .002, respectively).
CONCLUSIONS: Acetaminophen did not improve creatinine among the entire cohort but may improve renal function in patients with severe knowlesi malaria and in those with AKI and hemolysis.
CLINICAL TRIALS REGISTRATION: NCT03056391.