Stress Perfusion

Cardiovascular diseases are the leading cause of death worldwide, responsible for about 30% of all deaths. This substantial burden highlights the need for accurate diagnostic tools that help doctors detect heart disease early and understand it more fully. Recent advances in medical imaging offer promising opportunities to improve how heart conditions are diagnosed and treated. One important development in computed tomography (CT), a widely used imaging technique, is photon counting computed tomography (PCCT). PCCT produces clearer and more detailed images of the heart while using lower radiation doses and smaller amounts of contrast agent, the dye injected into the bloodstream to make body tissues more visible. As PCCT is still a relatively new technology, its full potential in clinical heart imaging has not yet been fully explored. This study includes patients with narrowing of the aortic valve, a condition that reduces blood flow from the heart and often requires treatment. These patients undergo cardiac CT before receiving a minimally invasive valve replacement procedure called transcatheter aortic valve implantation (TAVI). The study evaluates two diagnostic applications of PCCT: Functional assessment: Blood flow to the heart muscle is examined during stress imaging, when the heart works harder, to determine whether narrowed coronary arteries significantly limit blood supply. Tissue characterization: The heart muscle is analyzed to detect scarring or fibrosis by measuring the extracellular volume (ECV), the space between cells. If successful, PCCT could provide detailed anatomical, functional, and tissue information in a single non invasive examination, offering a "one stop shop" for comprehensive heart assessment.

Dilated cardiomyopathy (DCM) is a common and serious heart disease characterized by left ventricular enlargement and impaired pumping function, with adverse prognosis (including heart failure, arrhythmia, heart-related hospitalization, and death) being a major concern for patients. Currently, a critical gap exists in accurately predicting which DCM patients are at high risk of these severe outcomes, limiting targeted clinical care. This observational, non-invasive study aims to develop and validate a clinical prediction model for early risk warning of adverse prognosis in DCM patients. The model integrates multi-parameter stress perfusion cardiac magnetic resonance (MP stress perfusion CMR)-a safe, high-resolution imaging technique that assesses cardiac structure, function, blood perfusion, and tissue damage under mild stress-and standard clinical data (e.g., age, gender, blood pressure, and routine heart test results). The model will be trained and tested using follow-up data from hundreds of DCM patients, with the analysis identifying patterns in CMR and clinical data associated with adverse outcomes. Once validated for accuracy, the model will provide doctors with personalized risk scores to prioritize care for high-risk patients (e.g., early intervention, close monitoring) and avoid over-treatment for lower-risk individuals. Beyond clinical application, the study will enhance understanding of DCM progression, laying the groundwork for improved diagnostic tools, more effective treatments, and better strategies to prevent DCM-related complications, ultimately improving patient quality of life and reducing mortality.