Using Echocardiography and Patient Data to Diagnose Causes of Heart Diseases Like Hypokinetic Cardiomyopathy and Left Ventricular Hypertrophy

What this Trial Is About

Researchers are studying how advanced analysis of echocardiogram images combined with patient data can help diagnose the causes of certain heart diseases. This study focuses on building accurate and explainable artificial intelligence AI models to predict the origin of cardiac conditions, particularly hypokinetic cardiomyopathy and left ventricular hypertrophy, using echocardiographic information. The goal is to develop digital tools that improve understanding and diagnosis of heart disease causes. The study includes two groups of patients one with hypokinetic cardiomyopathy where heart function is reduced but the cause is unclear, and another with left ventricular hypertrophy, a condition where the heart muscle is thickened due to various potential causes. Researchers will use echocardiographic data and patient clinical information collected during routine care, such as cardiac CT, MRI, or coronary angiography, to train and test AI algorithms. These algorithms will learn from 80% of the collected data and be evaluated on the remaining 20%. Participants will provide echocardiogram images of sufficient quality for analysis. The researchers will compare AI-based diagnoses with those made by physicians using additional tests to evaluate AI accuracy. The main measure is how well the AI predicts the cause of heart disease compared to standard medical diagnosis. The study does not involve treatment changes and will continue until 2027, with participants contributing data for AI development and validation.

Etiological DiagnOsis of caRdiac Diseases Based on echoCardiograpHIc Images and Clinical Data.