Flat Colorectal Lesion
Conditions
Keywords
detection, AI, CAD, colorectal cancer, LST, adenoma, SSL
Brief summary
The development of artificial intelligence (AI) systems in the field of colorectal endoscopy is currently booming, colorectal cancer being, by its frequency and severity, a real public health problem. In terms of image analysis, AI is indeed able to perform many tasks simultaneously (lesion detection, classification, and segmentation) and to combine them. Lesion detection is thus the starting point of the whole chain to choose at the end the most appropriate treatment for the patient. Large-scale studies have demonstrated the superiority of artificial intelligence-assisted detection over the usual detection by gastroenterologists, mainly for the detection of sub-centimeter polyps. However, the investigators have shown that a recent computer-aided detection system (CADe) such as the ENDO-AID software in combination with the EVIS X1 video column (Olympus, Tokyo, Japan) may present difficulties in the detection of flat lesions such as sessile serrated lesions (SSLs) and non-granular laterally spreading tumors (LST-NGs). This represents a major challenge because in addition to their shape being difficult to identify for the human eye in practice and where AI assistance would be of great value, these rare lesions are associated with advanced histology. In addition, the investigators recently described the case of a worrisome false negative of AI-assisted colonoscopy, which failed to detect a flat adenocarcinoma in the transverse colon. Therefore, it is important to measure the false negative rate of AI detection based on the macroscopic shape of the lesion. Comparing this rate to the human endoscopist's false negatives would improve the performance of AI for this specific lesion subtype in the future.
Interventions
PROCEDUREproportion of colorectal lesions
Evaluation of the proportion of colorectal lesions detected by a computer-aided detection system (CADe) compared with experienced endoscopists.
Sponsors
Hospices Civils de Lyon
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* both gender patients even or older than 18 years old * patient with French Health Insurance coverage * obtaining of oral non opposition to research after loyal, clear and complete delivery of information * patients addressed to our center for colorectal lesion resection * patients presenting a colorectal lesion discovered during a diagnostic colonoscopy
Exclusion criteria
* patients with health disorders needing short procedure times * patients with no colorectal lesion * difficulty continuing colonoscopy due to poor sedation * difficulty continuing colonoscopy due to a serious adverse event * inappropriate participation after colonoscopy is completed * unwillingness to participate after colonoscopy is completed
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Evaluation of the proportion of colorectal lesions | Time point can be reached either 2 weeks after endoscopic resection or between 2-4 months later in case of surgery | Evaluation of the proportion of colorectal lesions detected by a computer-aided detection system (CADe) compared with experienced endoscopists and correlation with final histology reading. |
Countries
France
Outcome results
None listed