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Идёт набор NCT06406062

Artificial Intelligence-assisted System in Colonoscopy

— Наблюдательное Adenoma Colon Polyp

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: ANDOANGEL.
Кому может быть актуально
Состояния в реестре: Adenoma Colon Polyp. Базовые параметры: от 50 лет · Все.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Китай
Следующий шаг
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Официальное название

To Evaluate the Effectiveness and Safety of an Artificial Intelligence-assisted System in Colonoscopy in a Real-world Obsevational Multicenter Study

Обзор

In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control. This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control. This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study.

Вмешательства

  • Устройство ANDOANGEL
    Polyps were identified by endoscopists assisted by an AI system: rectangular box marks; Monitoring of ileocecal position: whether blindness was reached was displayed in the lower left corner of the interface. Mirror entry and exit time monitoring: the operation time is displayed in the upper left corner of the interface. Colonoscopy withdrawal speed monitoring: the relative withdrawal speed was displayed on the left side of the interface.

Первичные конечные точки

  • Adenoma detection rate [Срок оценки: During Endoscopy procesure]
Вторичные конечные точки (5)
  • Polyp detection rate [Срок оценки: During Endoscopy procesure]
  • Detection rate of serrated adenoma [Срок оценки: During Endoscopy procesure]
  • Average number of polyps per colonoscopy [Срок оценки: During Endoscopy procesure]
  • Colonoscopy time [Срок оценки: During Endoscopy procesure]
  • Proportion of over-speed frames [Срок оценки: During Endoscopy procesure]

Критерии участия

Критерии включения

  • age > 50 years old;
  • required diagnostic colonoscopy, screening colonoscopy, or follow-up colonoscopy;
  • voluntarily sign informed consent;
  • Commitment to abide by the study procedures and cooperate with the implementation of the whole process of the study.

Критерии исключения

  • have participated in other clinical trials, signed informed consent and are in the follow-up period of other clinical trials;
  • known polyposis syndrome patients;
  • patients with known IBD;
  • patients considered by the investigators to be unsuitable or unable to undergo complete digestive endoscopy and related examinations;
  • high-risk diseases or other special conditions considered by the investigator to be unsuitable for clinical trial participation.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения
Другое

Центры проведения

Китай · 1 центр
  • Renmin Hospital of Wuhan Univercity — Ухань

Идентификаторы

NCT: NCT06406062 · 2024K-K017

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗