Идёт набор NCT07197736

DELINEATE-Prospective

— Наблюдательное Valve Disease, Aortic Mitral Regurgitation (MR) Aortic Stenosis Valvular Heart Disease

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: Valve Disease, Aortic, Mitral Regurgitation (MR), Aortic Stenosis, Valvular Heart Disease. 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: США
Следующий шаг: Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →

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Официальное название

Deep Learning for Echo Analysis, Tracking, and Evaluation Prospective Evaluation (DELINEATE-Prospective)

Обзор

Heart disease is the leading cause of death in the United States, and echocardiography (or "echo") is the most common way doctors look at the heart. Echo is safe, painless, and can detect major heart problems, including weak heart pumping and valve disease. Valve disease, especially aortic stenosis (narrowing) and mitral regurgitation (leakage), is common in older adults but often goes undiagnosed. While echo is the main tool for finding valve problems, it takes time, requires expert training, and results can vary between readers. Recent advances in artificial intelligence (AI), especially deep learning (DL), have shown promise in automatically analyzing heart images. However, past research hasn't fully tackled key echo techniques-like color Doppler and spectral Doppler-that are crucial for measuring how blood moves through heart valves. AI tools also face challenges in being used in everyday medical practice because of workflow issues, lack of real-world testing, and concerns about how the algorithms make decisions. At Columbia University Irving Medical Center, researchers have built a large database of heart tests over the last six years and developed AI programs to analyze echocardiograms. The current study will test whether providing AI analysis to cardiologists in real time during echo reading can make the process faster and more consistent.

Подробное описание

In a prior Columbia University study, a series of deep learning algorithms analyzing echocardiograms is in development. These algorithms include, but are not limited to, algorithms that enable view classification, structure identification, left ventricle (LV) dimension measurements, Left Ventricular Ejection Fraction (LVEF) determination, left atrium (LA) volume assessments, and valvular heart disease diagnosis. Briefly, these algorithms are based on architectures shown to be useful in image and video analysis, including ones specific to echocardiography interpretation. Algorithms based off these architectures can be generalized to interpretation of video-based echocardiogram data such as valvular regurgitation assessment. As part of this study protocol, these models will continue to be developed using patient echocardiogram data. This study aims to create an automated, end-to-end system that can deliver deep learning analyses of echocardiograms to the interpreting cardiologist in real-time. If successful, this program could enable improvements in echocardiography reading efficiency and reliability.

Первичные конечные точки

Proportion of Clinically Meaningful Reclassification by Panel Review [Срок оценки: 18 months]

Вторичные конечные точки (4)

Proportion of Cases with AI-Based Reclassification Leading to a Change in Clinical Management [Срок оценки: 18 months]
Proportion of Cases with AI-Based Reclassification Leading to Referral to a Valve Specialist or Surgeon [Срок оценки: 18 months]
Proportion of Cases with AI-Based Reclassification Leading to a Change in Frequency of Follow-Up Echocardiography [Срок оценки: 18 months]
Proportion of Cases with AI-Based Reclassification Leading to Referral for Further Testing (TEE or Cardiac MRI) [Срок оценки: 18 months]

Критерии участия

Критерии включения

Attending cardiologist employed by Columbia University, ColumbiaDoctors, or NewYork Presbyterian Hospital who reads transthoracic echocardiograms in the Columbia echocardiography laboratory
Provided informed consent to take part in the questionnaires or pivotal study