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Bangaldesh Journal of Cardivascular Medicine
2023, Volume 1, Issue 2 : 1-9
Research Article
CT Coronary Angiography for Procedural Planning: Advancing Precision in Contemporary Cardiovascular Interventions
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1
Global Cardiovascular Institute, Boston, USA
2
Department of Cardiology, Global Cardiovascular Institute, Boston, USA
3
Division of Cardiovascular Imaging, Royal Heart Centre, London, United Kingdom
4
Center for Advanced Cardiac Research, Melbourne, Australia
Abstract

Background

Computed Tomography Coronary Angiography (CTCA) has emerged as a cornerstone non-invasive imaging modality for the evaluation of coronary artery disease (CAD) and procedural planning in cardiovascular interventions. Technological advancements have significantly improved spatial resolution, image acquisition speed, and diagnostic accuracy, making CTCA indispensable for preprocedural assessment in coronary and structural heart interventions.

Objective

To review the role of CT coronary angiography in procedural planning, discuss its applications across cardiovascular interventions, evaluate current evidence, and explore future developments.

Methods

A comprehensive review of contemporary literature, clinical trials, professional society guidelines, and technological advancements was conducted focusing on CTCA applications in procedural planning.

Results

CTCA provides detailed anatomical information regarding coronary stenosis, plaque morphology, vessel dimensions, calcification burden, and spatial relationships of cardiac structures. It has become essential in planning percutaneous coronary intervention (PCI), transcatheter aortic valve replacement (TAVR), left atrial appendage closure (LAAC), transcatheter mitral interventions, and coronary artery bypass grafting (CABG). Integration with artificial intelligence and computational modeling further enhances procedural precision.

Conclusion

CT coronary angiography plays a critical role in procedural planning across a broad range of cardiovascular interventions. Continued innovations in image processing, AI-assisted analysis, and virtual procedural simulation are expected to further improve patient outcomes.

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