Konstantinos Kaloudis

Bader Medical Institute of London, United Kingdom

Title: AI-Driven Cardiac Imaging: Enhancing Diagnostic Accuracy in Contemporary Cardiovascular Practice

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Biography

Konstantinos Kaloudis is a London-based consultant cardiologist with extensive NHS and private practice experience. He specialises in advanced cardiac imaging, including stress echo, transoesophageal echo, and CT coronary angiography. Trained in Milan and Athens, he has led echo departments and contributed to heart failure services. He is active in teaching and research, holds Level 2 cardiac CT accreditation, and is a member of the European Association of Cardiovascular Imaging. 

Abstract

Artificial Intelligence (AI) is rapidly redefining the landscape of cardiac imaging, offering new opportunities for improved diagnostic accuracy, consistency, and workflow efficiency. This presentation aims to evaluate the clinical impact of AI-enhanced imaging in cardiology, focusing on echocardiography, cardiac computed tomography (CT), and magnetic resonance imaging (MRI).

The primary objective of this presentation is to highlight the most relevant and validated applications of AI across cardiac imaging modalities, assess their contribution to diagnostic precision, and explore their potential integration into routine clinical workflows. Through a combination of literature review, real-world case examples, and comparative performance metrics, this presentation will demonstrate how AI can support, but not replace, clinical decision-making in high-stakes cardiovascular environments.

Methods include the analysis of peer-reviewed studies and registries evaluating AI tools in image acquisition, chamber quantification, valvular assessment, tissue characterization, and coronary plaque detection. Where available, data from large-scale clinical validation trials are used to support claims of improved reproducibility and diagnostic yield. Case illustrations will be drawn from both vendor-based and open-source AI applications currently in use or undergoing regulatory approval.

Results show consistent evidence that AI-driven platforms can reduce inter-observer variability, enhance measurement precision in parameters like ejection fraction or strain rate, and shorten time to diagnosis in both acute and chronic cardiac conditions. Particularly notable improvements are observed in the interpretation of cardiac CT and MRI datasets, where AI algorithms assist in automated segmentation and risk stratification.

In conclusion, AI is not merely a technological advancement but a practical clinical ally in modern cardiology. By strengthening diagnostic pathways and supporting early detection, AI has the potential to transform imaging from a descriptive tool into a predictive engine. This presentation will equip clinicians with an up-to-date understanding of how to safely and effectively implement AI in their imaging practice, and where the next breakthroughs are likely to occur.