Applicazioni dell’intelligenza artificiale nell’imaging cardiovascolare: vantaggi, limiti e sfide future

Artificial intelligence (AI) is rapidly transforming cardiovascular imaging, offering innovative solutions to enhance diagnostic precision, prognostic accuracy, and therapeutic decision-making. This review explores the role of AI in cardiovascular imaging, highlighting its applications, advantages, limitations, and future challenges. The discussion is structured by imaging modalities, including echocardiography, cardiac and coronary computed tomography, cardiac magnetic resonance, and nuclear cardiology. For each modality, we examine AI's contributions across the patient care continuum: from patient selection and image acquisition to quantitative and qualitative analysis, interpretation support, prognostic stratification, therapeutic guidance, and integration with other clinical data. AI applications demonstrate significant potential to streamline workflows, improve diagnostic accuracy, and provide advanced insights for complex clinical scenarios. However, several limitations must be addressed. Many AI algorithms are developed using data from single, high-expertise centers, raising concerns about their generalizability to routine clinical practice. In some cases, these algorithms may even produce misleading results. Additionally, the "black box" nature of certain AI systems poses challenges for cardiologists, making discrepancies difficult to interpret or rectify. Importantly, AI should be seen as a complementary tool rather than a replacement for cardiologists, designed to expedite routine tasks and allow clinicians to focus on complex cases. Future challenges include fostering clinician involvement in algorithm development and extending AI implementation to peripheral healthcare centers. This approach aims to enhance accessibility, understanding, and applicability of AI in everyday clinical practice, ultimately democratizing its benefits and ensuring equitable integration into healthcare systems.