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Идёт набор NCT07449130

AI Assisted Screening for VHD Using Routine Chest CT Scans

— Наблюдательное Heart Valve Diseases

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
Это наблюдательное исследование: исследуемое лечение участникам по протоколу не назначают.
Кому может быть актуально
Состояния в реестре: Heart Valve Diseases. Базовые параметры: от 18 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

Artificial-Intelligence Assisted Opportunistic Screening for Valvular Heart Disease Using Non-contrast Chest CT Scans: A Prospective, Multicenter Study

Обзор

This is a prospective, multicenter study designed to validate a deep learning model for screening valvular heart diseases using routine, non-contrast chest computed tomography (CT) scans. The primary objective is to evaluate the model's diagnostic performance, with the sensitivity serving as the primary efficacy endpoint. Secondary endpoints will include other performance metrics such as area under the receiver operating characteristic curve (AUC), specificity, and accuracy, etc.

Подробное описание

This is a prospective, multicenter study designed to validate a deep learning model for screening valvular heart diseases using routine, non-contrast chest computed tomography (CT) scans from individuals in physical examination and outpatient clinics within a hospital alliance.

The primary objective is to evaluate the model's diagnostic performance, with the sensitivity serving as the primary efficacy endpoint. Secondary endpoints will include other performance metrics such as area under the receiver operating characteristic curve (AUC), specificity, and accuracy, etc.

Participants from the target populations will undergo a routine non-contrast chest CT scan. The deep learning model will analyze these images in real-time. For those identified by the model as having moderate-to-severe heart valve disease, a confirmatory echocardiogram will be performed immediately. The echocardiogram results will serve as the reference standard for diagnosis. Statistical analyses will be performed to assess the model's performance against this reference, including calculating the 95% confidence interval for the AUC.

As this study only involves standard, low-radiation diagnostic imaging procedures (non-contrast CT and echocardiography) that are part of routine clinical care, it is considered to pose no additional relevant safety risks to participants. The total study duration is estimated to be 12 months.

Первичные конечные точки

  • Sensitivity [Срок оценки: 1 year]
Вторичные конечные точки (3)
  • Area Under the Receiver Operating Characteristic Curve (AUC) [Срок оценки: 1 year]
  • Accuracy [Срок оценки: 1 year]
  • Specificity [Срок оценки: 1 year]

Критерии участия

Критерии включения

  • Age ≥ 18 years.
  • Complete electronic health record.
  • Non-contrast chest CT performed between Nov 1, 2025 - Nov 1, 2026 in any medical context (including physical exam, outpatient, inpatient, or emergency).
  • AI-predicted moderate or severe valvular heart disease, or deemed to require clinical intervention, or selected negative cases from sampling verification.

Критерии исключения

  • Poor-quality non-contrast chest CT images.
  • Incomplete clinical records, involving severe deficiencies in critical diagnostic results, treatment records, imaging data, surgical records, medical history summaries, laboratory test results, or other essential medical information.
  • Presence of prosthetic valve implants, including aortic valves (mechanical valves, bioprosthetic valves), mitral valves (transcatheter edge-to-edge repair, bioprosthetic valves, mechanical valves, annuloplasty rings), tricuspid valves (TEER clipping, bioprosthetic valves, mechanical valves, annuloplasty rings), pulmonary valves (bioprosthetic valves), etc.
  • Abnormalities or conditions deemed by the investigator to warrant exclusion from the study enrollment.

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

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения
Когортное

Центры проведения

Китай · 3 центра
  • Renmin Hospital of Wuhan University — Ухань
  • Xinjiang Uygur Autonomous Region People's Hospital — Ürümqi
  • The Second Affiliated Hospital of Zhejiang University School of Medicine — Ханчжоу

Идентификаторы

NCT: NCT07449130 · 2025-1250

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗