Colorectal Adenoma, Colorectal Cancer, Colorectal Polyp
Conditions
Keywords
Artificial intelligence, Colonoscopy, colorectal cancer
Brief summary
Nowadays, colonoscopy is considered the gold standard for the detection of lesions in the colorectal mucosa. However, around 25% of polyps may be missed during the conventional colonoscopy. Based on this, new technological tools aimed to improve the quality of the procedures, diminishing the technical and operator-related factors associated with the missed lesions. These tools use artificial intelligence (AI), a computer system able to perform human tasks after a previous training process from a large dataset. The DiscoveryTM AI-assisted polyp detector (Pentax Medical, Hoya Group, Tokyo, Japan) is a newly developed detection system based on AI. It was designed to alert and direct the attention to potential mucosal lesions. According to its remarkable features, it may increase the polyp and adenoma detection rates (PDR and ADR, respectively) and decrease the adenoma miss rate (AMR). Based on the above, the investigators aim to assess the real-world effectiveness of the DiscoveryTM AI-assisted polyp detector system in clinical practice and compare the results between expert (seniors) and non-expert (juniors) endoscopists.
Detailed description
Colorectal cancer (CRC) is worldwide the second and third cancer-related cause of death in men and women, respectively. For the detection of lesions in the mucosa (premalignant and malignant), colonoscopy has been considered the gold standard. However, up to 25% of lesions can be missed during conventional colonoscopy. Some technical (i.e., bowel preparation) and operator-related (i.e., expertise, and fatigue) factors are related to these missing lesions. During the rapid-growing technological era, new tools were launched to improve the quality and performance of colonoscopies. Through the assistance of artificial intelligence (AI) an identification of a pattern can be achieved after a previous training from a large dataset of images. The DiscoveryTM AI-assisted polyp detector (Pentax Medical, Hoya Group, Tokyo, Japan), is a computer-assisted polyp/adenoma detection system based on AI. It detects classic adenomas and flat lesions, distinguished features like mucus cap or rim of debris with the advantage of a real-time and simultaneous multiple polyp detection. It was developed to minimize the missed lesions increasing as a result the polyp detection rate (PDR) and the adenoma detection rate (ADR). Lately, published data evaluating the AI-assisted polyp detectors has demonstrate high sensitivity, specificity, and interobserver agreement. Due to the importance of CRC diagnosis and prompt treatment, and taking advantage of the newly introduced DiscoveryTM AI system, the investigators aim to assess the real-world effectiveness of this AI-assisted polyp detector system in clinical practice and compare the results between expert (seniors) and non-expert (juniors) endoscopists.
Interventions
DIAGNOSTIC_TESTHD- colonoscopy
HD-colonoscopy performed by an expert or non-expert endoscopist. All lesions will be recorded, assessed, and removed for histological analysis.
DIAGNOSTIC_TESTHD-colonoscopy assisted by AI
HD-colonoscopy with AI-assisted polyp detector. New polyps detected by AI will be recorded, removed, and studied.
Sponsors
Instituto Ecuatoriano de Enfermedades Digestivas
Study design
Allocation
NON_RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Caregiver)
Intervention model description
Blinded, single center, controlled, prospective trial
Eligibility
Sex/Gender
ALL
Age
45 Years to 89 Years
Healthy volunteers
No
Inclusion criteria
* Adults ≥45 years old * Patients referred for screening colonoscopy * Adequate bowel preparation, Boston Bowel Preparation Scale (BBPS) ≥8 * Patients who authorized for endoscopic approach.
Exclusion criteria
* Pregnancy * Any clinical condition which makes endoscopy inviable. * Patients with history of Colorectal Carcinoma. * Patients with history of Inflammatory Bowel Disease (IBD) * Inability to provide informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Adenoma detection rate (ADR) | up to one month | The ADR will be determined by every new colonoscopy (second intervention) with at least one adenoma, histologically proven/NBI NICE classification. Results will be compared between experts and non-experts endoscopists. |
| Polyp detection rate (PDR) | up to two hours | The PDR will be determined by every new colonoscopy (second intervention) with at least one polyp. Results will be compared between experts and non-experts endoscopists. |
| Diagnostic performance of AI-assisted polyp detector | up to three years | The diagnostic performance of the AI-assisted system will be assessed by sensitivity, specificity, positive and negative predictive values (PPV and NPV) and observer agreement. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Adenoma Miss Rate (AMR) | Up to one month | The AMR will be determined by the total number of missed adenomas on initial examination. The diagnosis of adenoma will be made by NBI NICE classification or biopsy. |
Countries
Ecuador
Contacts
Primary ContactCarlos Robles-Medranda, MD FASGE
Outcome results
None listed