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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.
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.
International standardization and optimization group for intersphincteric resection (ISOG-ISR): modified Delphi consensus on anatomy, definition, indication, surgical technique, specimen description and functional outcome

Piozzi GN, Khobragade K, Aliyev V, Asoglu O, Bianchi PP, Butiurca VO, et al.

Colorectal Dis, 2023 Sep;25(9):1896-1909.
PMID: 37563772 DOI: 10.1111/codi.16704

AIM: Intersphincteric resection (ISR) is an oncologically complex operation for very low-lying rectal cancers. Yet, definition, anatomical description, operative indications and operative approaches to ISR are not standardized. The aim of this study was to standardize the definition of ISR by reaching international consensus from the experts in the field. This standardization will allow meaningful comparison in the literature in the future.
METHOD: A modified Delphi approach with three rounds of questionnaire was adopted. A total of 29 international experts from 11 countries were recruited for this study. Six domains with a total of 37 statements were examined, including anatomical definition; definition of intersphincteric dissection, intersphincteric resection (ISR) and ultra-low anterior resection (uLAR); indication for ISR; surgical technique of ISR; specimen description of ISR; and functional outcome assessment protocol.
RESULTS: Three rounds of questionnaire were performed (response rate 100%, 89.6%, 89.6%). Agreement (≥80%) reached standardization on 36 statements.
CONCLUSION: This study provides an international expert consensus-based definition and standardization of ISR. This is the first study standardizing terminology and definition of deep pelvis/anal canal anatomy from a surgical point of view. Intersphincteric dissection, ISR and uLAR were specifically defined for precise surgical description. Indication for ISR was determined by the rectal tumour's maximal radial infiltration (T stage) below the levator ani. A new surgical definition of T3isp was reached by consensus to define T3 low rectal tumours infiltrating the intersphincteric plane. A practical flowchart for surgical indication for uLAR/ISR/abdominoperineal resection was developed. A standardized ISR surgical technique and functional outcome assessment protocol was defined.

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