Why the study?
The clinical spectrum of atrial fibrillation necessitates a patient-individualized approach to treatment, highlighting the need to review how cardiac computed tomography can delineate atrial structure and function across pre-, peri-, and post-procedural care.
Does cardiac computed tomography improve personalized management and procedural planning in patients with atrial fibrillation?
Does cardiac computed tomography improve personalized management and procedural planning in patients with atrial fibrillation?
Cardiac computed tomography provides detailed anatomical and structural assessment of the left atrium, which can guide personalized management, ablation planning, and risk stratification in patients with atrial fibrillation.
Hypothesis-generating for expanded cardiac CT use in AF; prospective validation needed before clinical adoption.
The clinical spectrum of atrial fibrillation means that a patient-individualized approach is required to ensure optimal treatment. Cardiac computed tomography can accurately delineate atrial structure and function and could contribute to a personalized care pathway for atrial fibrillation patients. The imaging modality offers excellent spatial resolution and has been utilised in pre-, peri- and post-procedural care for patients with atrial fibrillation. Advances in temporal resolution, acquisition times and analysis techniques suggest potential expanding roles for cardiac computed tomography in the future management of patients with atrial fibrillation. The aim of the current review is to discuss the use of cardiac computed tomography in atrial fibrillation in pre-, peri- and post-procedural settings. Potential future applications of cardiac computed tomography including atrial wall thickness assessment and epicardial fat volume quantification are discussed together with emerging analysis techniques including computational modelling and machine learning with attention paid to how these developments may contribute to a personalized approach to atrial fibrillation management.
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Bodagh et al. (2023) studied this question.
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