Меню
Идёт набор NCT07411443

AI-Enhanced Imaging in Population Breast Cancer Screening

Без фазы С лечением Breast Cancer Screening

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: AI-assisted screening.
Кому может быть актуально
Состояния в реестре: Breast Cancer Screening. Базовые параметры: 35 лет — 69 лет · Женщины.
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
Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
Официальное название

Population-based Breast Cancer Screening Study Using AI-Assisted Imaging Technology

Обзор

Artificial Intelligence (AI)-assisted imaging technologies (including AI-assisted breast ultrasound and AI-assisted mammography) can effectively improve the accuracy and efficiency of breast imaging examinations, but their application in large-scale population-based breast cancer screening remains very limited. This project aims to improve the effectiveness and feasibility of breast cancer screening by addressing the core issues and bottlenecks in population-based breast cancer screening. We will conduct a prospective cluster-controlled screening trial in the general population, with district-based cluster grouping. The intervention group will undergo combined screening using AI-assisted ultrasound plus AI-assisted mammography, while the control group will receive conventional screening: breast ultrasound for initial screening and mammography for secondary screening. Based on population screening practices, we will evaluate the effectiveness of AI-assisted imaging diagnostic technology in various technical aspects of actual screening and perform cost-effectiveness analyses. This study will investigate the application of AI-assisted breast imaging technology in population-based breast cancer screening, providing scientific evidence for the large-scale implementation of AI-assisted imaging technologies. Furthermore, by combining population screening practices with model simulations, we will explore multi-dimensional breast cancer screening strategies to optimize screening approaches and technologies for the Chinese population.

Вмешательства

  • Устройство AI-assisted screening
    The intervention group will undergo combined screening using AI-assisted ultrasound plus AI-assisted mammography

Первичные конечные точки

  • The incidence of early-stage breast cancer over a one-year follow-up period, compared between women who underwent AI-assisted screening and those with routine screening [Срок оценки: From enrollment to 1-year after the end of screening]
  • The detection rate of suspicious breast lesions (including masses and calcifications) over a one-year follow-up period, compared between women who underwent AI-assisted ultrasound combined with AI-assisted mammography and those who received routine scree [Срок оценки: From enrollment to 1-year after the end of screening]

Критерии участия

Критерии включения

  • women aged 35 to 69 years, who were attending the "Two Cancers (Breast and Cervical Cancer) Screening" project, and had no history of breast cancer, including in-situ cancer, or any other cancers in the previous five years.

Критерии исключения

  • have serious cardiopulmonary insufficiency, liver or kidney insufficiency, or other systemic diseases, and a life expectancy of less than five years

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

Здоровые добровольцы: Да

Дизайн исследования

Распределение
Нерандомизированное
Модель
Параллельные группы
Маскирование
Открытое
Основная цель
Скрининг

Центры проведения

Китай · 1 центр
  • Fudan University Shanghai Cancer Center — Шанхай

Идентификаторы

NCT: NCT07411443 · 2024AI

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗