Using artificial intelligence in colonoscopy's adenoma detection: An invention to help clinicians (Part 1)

Posted by Master, Doctor Mai Vien Phuong - Gastrointestinal Endoscopy - Department of Examination & Internal Medicine - Vinmec Central Park International General Hospital

Computer-aided disease (CAD) detection and diagnosis, thanks to the newly developed innovations of artificial intelligence, will help increase the detection rate of adenomas and thus contribute to a reduction in the incidence of cancer. , improves the effectiveness of colonoscopy in screening for important outcomes such as colorectal cancer-related mortality.
Colonoscopy remains the standard strategy for colorectal cancer screening worldwide due to its effectiveness in both detecting adenoma or precancerous lesions and its ability to remove them immediately. in endoscopic procedures. Computer-aided disease (CAD) detection and diagnosis, thanks to newly developed innovations of artificial intelligence and especially artificial intelligence techniques, leads to a promising solution for performance biases, human error by ensuring decision support during colonoscopy.
The application of CAD to colonoscopy will increase the detection rate of adenomas and thus contribute to a reduction in the incidence of cancer, improving the effectiveness of colonoscopy in screening important outcomes such as death deaths related to colorectal cancer. Moreover, it is also expected to significantly reduce costs. In addition, mechanical assistance will reduce examination time and thus optimize endoscopic scheduling. The aim of this paper is to analyze the clinical applications of CAD and artificial intelligence in colonoscopy, as well as the evidence applied, limitations, and future prospects.

Colon polyps are small masses of cells that form on the lining of the colon (large intestine). Most colon polyps are harmless, but over time, some colon polyps can develop into colon cancer, which is fatal when found in its late stages.
Colorectal cancer (CRC) is a major healthcare problem worldwide. It is the third most common cancer in men, the second in women and the fourth leading cause of cancer death worldwide. To date, almost 60%-70% of cases recorded in symptomatic patients have been diagnosed at the end stage. Early detection leads to better outcomes in terms of reducing disease burden.
Globally, colonoscopy remains the standard strategy for colon cancer screening for CRC due to its effectiveness in both detecting adenoma or precancerous colonic lesions and its ability to remove them right in the trick. However, the identification and classification of lesions is strongly dependent on the endoscopist, and human error in this process increases the likelihood of progression to CRC. Although uncertain, circumstantial evidence highlights that endoscopists may not detect lesions even within the scope of view of endoscopy, thereby increasing the occurrence of colorectal cancer. rectal.
Computer-aided detection and diagnosis (CAD), thanks to newly developed innovations of artificial intelligence (AI), leads to a promising solution for the performance deviations of humans by ensuring decision support during colonoscopy. The purpose of this opinion review was to analyze the clinical applications of CAD and AI in colonoscopy, as it has been reported in the literature, to address the evidence, limitations, and prospects in future.

Artificial intelligence is an emerging technology whose application is rapidly increasing in many medical fields. Several applications of artificial intelligence in digestion are showing promising results, especially in the area of ​​gastrointestinal cancer. Among these, techniques that can increase the detection rate of adenomas will play an important role in reducing the incidence of colorectal cancer and its associated mortality from colorectal cancer. detected or unclassified.
2.1 What is Artificial Intelligence (AI)? CAD systems using advanced AI techniques represent an innovative technology that has the potential to lead to a paradigm shift in the field of diagnostic colonoscopy. Since endoscopy often involves computer vision technology, this technique allows computers to "see" and decode visual content. Through machine learning processes and, more recently, learning and memory, AI systems can be set up to recognize “normal” features by connecting the gold standard to the right image.
Deep learning is a method of computer learning, recently using deep neural networks, that automatically extracts specific features from data without human effort if some are available. very large number of learning samples.

The initial development of AI was based on creating an algorithm using highly accurate data sets, coded in an independently organized way by a team of experts. This process is called "foundational truth" establishment, where the computer is prepared to distinguish between "abnormal" and "normal" tissue. Once an algorithm is created, complex neural networks
use vast data sets to allow the algorithm to become more skilled. This intelligence is extendable to algorithms and it can learn by developing its own rules and classifiers. AI is expected to have at least 2 major roles in colonoscopy practice: Polyp detection (CADe) and polyp characterization (CADx). CADe has the potential to reduce polyp missed rates, contributing to improved adenoma detection, while CADx can improve the accuracy of optical diagnosis of colorectal polyps, leading to a reduction in unnecessary removal of lesions noncancerous lesions, the potential for performing resection and resection. strategies and appropriate application of advanced resection techniques.
Currently, gastrointestinal cancer screening is a scientific and effective measure for early detection of gastrointestinal cancer (esophageal cancer, stomach cancer, colon cancer) and giving a treatment plan. best treatment. Currently, Vinmec International General Hospital has a package of screening and early detection of cancers of the gastrointestinal tract (esophagus - stomach - colon) combined with clinical and paraclinical examination to bring the most accurate results. maybe.

When screened for gastrointestinal cancer at Vinmec, you will receive:
Gastroenterology specialist examination with an oncologist (by appointment). Gastroscopy and colonoscopy with an NBI endoscope under anesthesia. Complete peripheral blood cytology (by laser counter). Automated prothrombin time test. Automated thrombin time test. Activated Partial Thromboplastin Time (APTT) test using an automated machine. General abdominal ultrasound

References
Emanuele Sinagra, Matteo Badalamenti, et al., Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped. World J Gastroenterol. Oct 21, 2020; 26(39): 5911-5918 Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65:87-108. [PubMed] [DOI] Maida M, Morreale G, Sinagra E, Ianiro G, Margherita V, Cirrone Cipolla A, Camilleri S. Quality measures improving endoscopic screening of colorectal cancer: a review of the literature. Expert Rev Anticancer Ther. 2019;19:223-235. [PubMed] [DOI]