An interventional study of Colonoscopy in Colorectal Cancer (CRC), Adenomatous Polyposis and Colorectal Lesions, sponsored by Instituto do Cancer do Estado de São Paulo. Recruiting at 1 site in Brazil. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-06-23.
Sponsored by Instituto do Cancer do Estado de São Paulo · Not applicable, Interventional, and Diagnostic
The study aims to evaluate the effectiveness of artificial intelligence-assisted colonoscopy in increasing adenoma detection rate and the accuracy in the characterization of colorectal lesions, compared to standard colonoscopy, in a randomized controlled clinical trial setting.
Colorectal cancer (CRC) currently shows, according to GLOBOCAN, an incidence of 19.5 individuals per 100,000 inhabitants in both sexes, being the third most common cancer in men and the second in women, representing the third leading cause of death in both men and women.
According to the GLOBOCAN registry of the World Health Organization (WHO), it is estimated that CRC is the third most common type of cancer worldwide, responsible for 10% of all newly diagnosed cancer cases, corresponding to 1,931,590 cases in 2020, preceded only by lung cancer (11.4%) and breast cancer (11.7%). CRC is the second leading cause of cancer mortality (9.4%; 935,173 cases in 2020), following only lung cancer, which accounts for 18% of cancer deaths globally.
In Brazil, according to data from the National Cancer Institute (INCA), CRC mirrors the global incidence, being the second most common cancer by sex.
Colonoscopy is the most accurate CRC screening method, with sensitivity reaching 100% in the detection of colorectal lesions. According to studies, for each 1% increase in adenoma detection rate, there is a 5% decrease in CRC mortality, highlighting the importance of performing colonoscopy to detect colorectal lesions, especially adenomas.
Consequently, with the advancement of technology, new high-definition endoscopes with virtual chromoscopy and image magnification have been developed to increase adenoma detection rates. More recently, AI-assisted colonoscopy has been gaining prominence in helping prevent CRC in some medical centers worldwide, such as in Japan.
In a multicenter study with 700 patients in 2019, a significantly higher adenoma detection rate was demonstrated with AI-assisted colonoscopy compared to standard colonoscopy (54.8% vs. 40.4%). Subsequently, a randomized, double-blind clinical trial with 1,058 patients was conducted, comparing standard colonoscopy to AI-assisted colonoscopy. The result was an adenoma detection rate of 29% for AI-assisted colonoscopy and 20% for standard colonoscopy, with the difference being statistically significant. Two other studies comparing AI-assisted colonoscopy and standard colonoscopy showed similar results.
However, when analyzing the accuracy of AI systems in characterizing colorectal lesions, different results are observed in the literature. On one hand, Japanese studies report accuracies above 90% in characterizing neoplastic and non-neoplastic lesions with artificial intelligence, while other studies, such as the Dutch study and the German study, found accuracies of 74.4% and 84.7%, respectively, results significantly lower compared to the Japanese studies.
Therefore, given not only the differences in results obtained by various authors but also the differences in population and the lack of studies on AI-assisted colonoscopy in developing countries, the objective of this work is to evaluate the adenoma detection rate of AI-assisted colonoscopy and assess the accuracy of artificial intelligence in characterizing colorectal lesions.
6,541 studies on the registry are indexed under Colorectal Neoplasms; 1,667 are open to participants now.
This study's planned enrollment of 1,000 is above the median of 76 across 4,800 interventional studies indexed under Colorectal Neoplasms.
Browse Colorectal Neoplasms studies →Instituto do Cancer do Estado de São Paulo is the lead sponsor of 91 studies on the registry; 22 are open to participants now.
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Exclusion Criteria:
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Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
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A biopsy takes a small piece of tissue to examine. “Archival tissue” is a sample already taken, for example at diagnosis, and kept by the hospital.
Whether a stored sample will do depends on when it was taken, how much there is and what the study needs. Ask whether the study accepts your stored sample or needs a new biopsy.
The anaesthetists’ scale of health before surgery: I is healthy, II has a mild illness that is under control, III a severe one, IV a severe illness that is a constant threat to life. V and VI are used for the critically ill and for organ donors.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Contraindication
A reason a treatment, test or procedure should not be given to a particular person, such as an allergy, another illness or a medicine they take.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Biopsy and archival tissue
A biopsy takes a small piece of tissue to examine. “Archival tissue” is a sample already taken, for example at diagnosis, and kept by the hospital.
Whether a stored sample will do depends on when it was taken, how much there is and what the study needs. Ask whether the study accepts your stored sample or needs a new biopsy.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
ASA physical status
The anaesthetists’ scale of health before surgery: I is healthy, II has a mild illness that is under control, III a severe one, IV a severe illness that is a constant threat to life. V and VI are used for the critically ill and for organ donors.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Stratum 1: Patients aged 18 to 44 years Stratum 2: Patients aged 45 to 75 years Stratum 3: Patients aged 76 years or older
Procedure: Colonoscopy
Stratum 1: Patients aged 18 to 44 years Stratum 2: Patients aged 45 to 75 years Stratum 3: Patients aged 76 years or older
Procedure: Colonoscopy
This single-center, randomized, open-label clinical trial will assess the effectiveness of artificial intelligence (AI)-assisted colonoscopy versus standard high-definition colonoscopy in detecting and characterizing colorectal lesions. Conducted over 12 months in São Paulo, Brazil, the study will include 100 adult patients undergoing elective colonoscopy. Participants will be stratified by age and randomized (1:1) after sedation. All lesions will be resected, recorded, and analyzed histologically. The intervention group will also include AI output data (CAD EYE). The primary goals are to evaluate adenoma detection rate (ADR) and AI diagnostic accuracy. Given the global burden of colorectal cancer (CRC), particularly in developing countries, this study aims to provide real-world data on the impact of AI in CRC screening.
Number of patients with at least one adenoma detected, confirmed by histopathological analysis, during colonoscopy, in the AI group vs. control group
The measure will be expressed as the number and percentage (%) of patients with at least one adenoma detected during colonoscopy and confirmed by histopathological analysis, comparing the AI and non-AI groups (CAD EYE). Detection will be based on the analysis of biopsies performed and processed according to the standard protocol.
Time frame: 7 days after colonoscopy (estimated time for histopathological report release).
Diagnostic accuracy of CAD EYE for characterization of lesions as neoplastic (adenoma) or non-neoplastic (hyperplastic), compared to histopathological analysis as the gold standard.
The accuracy of artificial intelligence (CAD EYE) in characterizing detected lesions as neoplastic or non-neoplastic will be calculated, based on comparison with histopathological diagnosis (gold standard). The following will be reported: sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), in percentage (%), for each type of lesion.
Time frame: 7 days after colonoscopy
PDFs hosted by the registry, ClinicalTrials.gov.
Plan to share: No — We do not plan to share Individual Participant Data (IPD) with other researchers due to privacy concerns and the nature of the study
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Instituto do Cancer do Estado de São Paulo