⭐️⭐️⭐️⭐️⭐️ "A total no brainer"

⭐️⭐️⭐️⭐️⭐️ "Love this, so easy."

Spots is the easy way to track your skin, mole and cancer changes.

Spots Global Cancer Trial Database for Computer-aided Detection During Screening Colonoscopy

The following info and data is provided "as is" to help patients around the globe.
We do not endorse or review these studies in any way.

Trial Identification

Brief Title: Computer-aided Detection During Screening Colonoscopy

Official Title: Real-time Computer-aided Polyp/Adenoma Detection During Screening Colonoscopy: a Single-center Crossover Trial

Study ID: NCT05734820

Study Description

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.

Eligibility

Minimum Age: 45 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Instituto Ecuatoriano de Enfermedades Digestivas (IECED), Guayaquil, Guayas, Ecuador

Contact Details

Name: Carlos Robles-Medranda, MD FASGE

Affiliation: Instituto Ecuatoriano de Enfermedades Digestivas (IECED)

Role: PRINCIPAL_INVESTIGATOR

Useful links and downloads for this trial

Clinicaltrials.gov

Google Search Results

Logo

Take Control of Your Skin and Body Changes Today.

Try out Spots for free, set up only takes 2 mins.

spots app storespots app store

Join others from around the world: