Study on the impact of artificial intelligence on adenoma detection rate

Detection Capability of Computer-Aided Detection for Depressed-Type and Laterally Spreading Colorectal Tumors: A Retrospective Study Utilizing Existing Endoscopic Data - AI Study

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000055836

Enrollment

430

Registered

2024-10-18

Start date

2024-01-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

colorectal polyps

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Inclusion Criteria: 1 Patients who underwent colonoscopy at the Digestive Disease Center, Showa University Northern Yokohama Hospital, between January 1, 2020, and December 31, 2023. 2 Patients who did not express a refusal to participate in this study. 3 Patients aged 20 years or older at the time of examination.

Exclusion criteria

Exclusion criteria: Exclusion Criteria: 1 Patients with inflammatory bowel disease (IBD). 2 Patients with colorectal polyposis.

Design outcomes

Primary

Measure	Time frame
Based on endoscopic data from patients who underwent colonoscopy at our institution between January 1, 2020, and December 31, 2023, we will compare the adenoma detection rate (ADR) between single monitor and dual monitor systems. Additionally, we will assess the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of EB-EYE in detecting depressed-type and laterally spreading tumors. Patient characteristics (age, sex, date of examination), lesion characteristics (tumor size, gross type, location, pathological diagnosis), and the adenoma detection rate (ADR) with and without the use of EB-EYE during this period will also be evaluated.	—

Measure

Time frame

Based on endoscopic data from patients who underwent colonoscopy at our institution between January 1, 2020, and December 31, 2023, we will compare the adenoma detection rate (ADR) between single monitor and dual monitor systems. Additionally, we will assess the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of EB-EYE in detecting depressed-type and laterally spreading tumors. Patient characteristics (age, sex, date of examination), lesion characteristics (tumor size, gross type, location, pathological diagnosis), and the adenoma detection rate (ADR) with and without the use of EB-EYE during this period will also be evaluated.

—

Countries

Japan

Contacts

Public ContactYutaro Ide

Showa University Northern Yokohama Hospital Digestive Disease Center

yuutarou-ide@med.showa-u.ac.jp0459497000

Outcome results