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Colorectal cancer is the second most common malignancy in the countries of the European Union. Colonoscopy is the primary method for detecting and preventing the development of colorectal cancer is endoscopic examination. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.
Colorectal cancer is the second most common malignancy in the countries of the European Union. The primary method for detecting and preventing the development of colorectal cancer is endoscopic examination-colonoscopy, during which precancerous lesions such as adenomas and serrated polyps can be removed. The effectiveness of colonoscopy depends on the adenoma detection rate, which varies among endoscopists and is influenced by their skills and experience. It has been proven that high-quality colonoscopy prevents the omission of colorectal cancer, which might develop in the future as so-called interval cancer. A breakthrough in machine learning in recent years has enabled the development of commercial artificial intelligence systems. These systems aim to improve the detection rates of precancerous polyps and, consequently, potentially reduce the risk of developing colorectal cancer. Artificial intelligence is also expected to help standardize performance across endoscopic procedures of varying quality, thereby contributing to a reduction in colorectal cancer incidence in the future. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI-group | Experimental | AI-group will include patients undergoing colonoscopy with the support of the ENDO-AID OIP-1 artificial intelligence system for colorectal polyp detection. |
|
| Non-AI-group | No Intervention | Non-AI-group will consist of patients undergoing colonoscopy without the assistance of this system. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Computer-aided detection (CADe) | Device | Endo-Aid CADe system is an AI-assisted computer-aided lesion detection application on ENDO-AID hardware. It uses a complex algorithm created via a neural network developed and taught by Olympus. With this new app, the sophisticated machine learning system can alert the endoscopist in real-time when a suspicious lesion appears on the screen. The image from the vision processor is transferred to the CADe device. The computer application recognizes the shape of the polyps and marks their place on the monitor screen. |
| Measure | Description | Time Frame |
|---|---|---|
| Adenoma detection rate (ADR) | The percentage of colonoscopies when at least one histologically proven adenoma was found. | During the colonoscopy examination |
| Measure | Description | Time Frame |
|---|---|---|
| Utility of artificial intelligence for both novice and experienced endoscopists | The difference in adenoma detection rates (ADR) achieved with and without AI in trainees and expert endoscopists. | During the colonoscopy examination |
| Assessing the morphology of polyps detected during colonoscopy |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Zofia Orzeszko, MD | Contact | +48123797145 | z.orzeszko@bonifratrzy.krakow.pl |
| Name | Affiliation | Role |
|---|---|---|
| Miroslaw Szura, Prof. | Jagiellonian University in Krakow | Study Chair |
| Zofia Orzeszko, MD | Jagiellonian University in Krakow | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| MEDICINA Medical Center | Recruiting | Krakow | Lesser Poladn | 31559 | Poland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23567353 | Background | Boroff ES, Gurudu SR, Hentz JG, Leighton JA, Ramirez FC. Polyp and adenoma detection rates in the proximal and distal colon. Am J Gastroenterol. 2013 Jun;108(6):993-9. doi: 10.1038/ajg.2013.68. Epub 2013 Apr 9. | |
| 32240683 | Background | Mori Y, Kudo SE, East JE, Rastogi A, Bretthauer M, Misawa M, Sekiguchi M, Matsuda T, Saito Y, Ikematsu H, Hotta K, Ohtsuka K, Kudo T, Mori K. Cost savings in colonoscopy with artificial intelligence-aided polyp diagnosis: an add-on analysis of a clinical trial (with video). Gastrointest Endosc. 2020 Oct;92(4):905-911.e1. doi: 10.1016/j.gie.2020.03.3759. Epub 2020 Mar 30. |
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Assessment of the differences in polyps' morphology detected in both arms of the study. |
| During the colonoscopy examination |
| Cost analysis of procedures performed with the use of artificial intelligence | The assessment of cost-efficiency of AI implementation, including the increased cost of pathological evaluation and additional surveillance examinations. | Through study completion, an average of 6 months |
| Brothers Hospitallers Medical Center, Hospital of St John of god in Krakow | Recruiting | Krakow | Lesser Polasd | 31061 | Poland |
|
| 25817896 | Background | van Doorn SC, Klanderman RB, Hazewinkel Y, Fockens P, Dekker E. Adenoma detection rate varies greatly during colonoscopy training. Gastrointest Endosc. 2015 Jul;82(1):122-9. doi: 10.1016/j.gie.2014.12.038. Epub 2015 Mar 24. |
| 32557490 | Background | Barua I, Vinsard DG, Jodal HC, Loberg M, Kalager M, Holme O, Misawa M, Bretthauer M, Mori Y. Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis. Endoscopy. 2021 Mar;53(3):277-284. doi: 10.1055/a-1201-7165. Epub 2020 Sep 29. |
| 32371116 | Background | Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1. |
| 24693890 | Background | Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086. |
| 20463339 | Background | Kaminski MF, Regula J, Kraszewska E, Polkowski M, Wojciechowska U, Didkowska J, Zwierko M, Rupinski M, Nowacki MP, Butruk E. Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med. 2010 May 13;362(19):1795-803. doi: 10.1056/NEJMoa0907667. |