Background: Colorectal cancer (CRC) is the third most common cancer worldwide. Colonoscopy is the gold standard examination that reduces the morbidity and mortality of CRC. Artificial intelligence (AI) could be useful in reducing the errors of the specialist and in drawing attention to the suspicious area. Methods: A prospective single-center randomized controlled study was conducted in an outpatient endoscopy unit with the aim of evaluating the usefulness of AI-assisted colonoscopy in PDR and ADR during the day time. It is important to understand how already available CADe systems improve the detection of polyps and adenomas in order to make a decision about their routine use in practice. In the period from October 2021 to February 2022, 400 examinations (patients) were included in the study. One hundred and ninety-four patients were examined using the ENDO-AID CADe artificial intelligence device (study group), and 206 patients were examined without the artificial intelligence (control group). Results: None of the analyzed indicators (PDR and ADR during morning and afternoon colonoscopies) showed differences between the study and control groups. There was an increase in PDR during afternoon colonoscopies, as well as ADR during morning and afternoon colonoscopies. Conclusions: Based on our results, the use of AI systems in colonoscopies is recommended, especially in circumstances of an increase of examinations. Additional studies with larger groups of patients at night are needed to confirm the already available data.
The narrow-band imaging (NBI) International Colorectal Endoscopic (NICE) classification is based on narrow-band pictures of colon polyps viewed through a narrow-band spectrum. The categorisation utilises staining, surface structure, and vascular patterns to differentiate between hyperplastic and adenomatous colon polyps. It is known that accuracy of the NICE classification for colorectal polyps varies depending on the localisation in the colon.The aim of this study was to compare the diagnostic accuracy of the NICE classification and the gold standard — morphological analysis for the determination of the type of colorectal lesions depending on localisation in colon. A prospective study was performed in an outpatient clinic. 1214 colonoscopies were performed by two expert endoscopists and 475 polyps were found in 291 patients. The overall diagnostic accuracy of the NICE classification was 80.3%. Optical verification was better in ascending colon — 93.9%, followed by sigmoid colon — 82.1%. Inferior results were found for the descending colon — 64.0%. The results of this study showed that the NICE classification could be a helpful instrument in daily practice for the ascending and sigmoid colon. For better results, proper training should be considered. The NICE system could have a role in the replacement of morphological analysis if appropriate results of verification could be achieved.
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