Myocardial Fibrosis in Hypertrophic Cardiomyopathy: Leveraging Quantitative Imaging and Artificial Intelligence for...

Area of Science:

• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Hypertrophic cardiomyopathy (HCM) is a genetic heart disease linked to myocardial fibrosis.
• Myocardial fibrosis severity is a key predictor of adverse outcomes like sudden cardiac death and heart failure.
• Current HCM management is shifting towards a multidimensional approach integrating imaging, molecular, and functional assessments.

Purpose of the Study:

• To discuss advancements in multimodal imaging for HCM.
• To review AI-driven innovations in HCM diagnostics and risk stratification.
• To highlight the integration of imaging and AI for improved clinical decision-making and patient care.

Main Methods:

• Comprehensive review of multimodal imaging technologies in HCM.
• Analysis of artificial intelligence applications in HCM diagnostics and prognostication.
• Exploration of AI-based predictive modeling for risk stratification and therapeutic guidance.

Main Results:

• Multimodal imaging offers enhanced characterization beyond morphology.
• AI facilitates intelligent diagnostics, precise risk stratification, and personalized therapies.
• Integration of imaging and AI transforms HCM management into a data-driven framework.

Conclusions:

• Advancements in imaging and AI are revolutionizing hypertrophic cardiomyopathy care.
• An integrated approach optimizes early detection, intervention, and prevention strategies.
• AI-powered analytics and precision medicine enhance clinical decision-making for HCM patients.