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Open AccessReview
Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review
by
Alexander J. Sharp
Alexander J. Sharp 1
,
Timothy R. Betts
Timothy R. Betts 2
and
Abhirup Banerjee
Abhirup Banerjee
Abhirup Banerjee is a Royal Society University Research Fellow (URF), Full Member of Faculty, and PI [...]
Abhirup Banerjee is a Royal Society University Research Fellow (URF), Full Member of Faculty, and PI in the Department of Engineering Science, University of Oxford. Dr Banerjee received his BSc (Hons) and Master degrees in Statistics and his PhD degree in Computer Science in March 2017 from the Indian Statistical Institute, Kolkata, India. He joined the University of Oxford as a Postdoctoral Researcher in the Division of Cardiovascular Medicine in August 2017, started as the URF and Faculty Member in the Department of Engineering Science in October 2022, and officially started the MultiMeDIA Lab in March 2023. His research interest spans Biomedical Engineering, Computer Science, and classical Statistics, focusing on a range of topics including Biomedical Image Analysis, Machine Learning, AI, Multimodal Imaging, Geometric Deep Learning, etc.
1,3,*
1
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, UK
2
Cardiology Department, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
3
Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2024, 13(15), 4442; https://doi.org/10.3390/jcm13154442 (registering DOI)
Submission received: 28 June 2024
/
Revised: 19 July 2024
/
Accepted: 23 July 2024
/
Published: 29 July 2024
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia associated with significant morbidity and mortality. Managing risk of stroke and AF burden are pillars of AF management. Atrial geometry has long been recognized as a useful measure in achieving these goals. However, traditional diagnostic approaches often overlook the complex spatial dynamics of the atria. This review explores the emerging role of three-dimensional (3D) atrial geometry in the evaluation and management of AF. Advancements in imaging technologies and computational modeling have enabled detailed reconstructions of atrial anatomy, providing insights into the pathophysiology of AF that were previously unattainable. We examine current methodologies for interpreting 3D atrial data, including qualitative, basic quantitative, global quantitative, and statistical shape modeling approaches. We discuss their integration into clinical practice, highlighting potential benefits such as personalized treatment strategies, improved outcome prediction, and informed treatment approaches. Additionally, we discuss the challenges and limitations associated with current approaches, including technical constraints and variable interpretations, and propose future directions for research and clinical applications. This comprehensive review underscores the transformative potential of leveraging 3D atrial geometry in the evaluation and management of AF, advocating for its broader adoption in clinical practice.
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MDPI and ACS Style
Sharp, A.J.; Betts, T.R.; Banerjee, A.
Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review. J. Clin. Med. 2024, 13, 4442.
https://doi.org/10.3390/jcm13154442
AMA Style
Sharp AJ, Betts TR, Banerjee A.
Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review. Journal of Clinical Medicine. 2024; 13(15):4442.
https://doi.org/10.3390/jcm13154442
Chicago/Turabian Style
Sharp, Alexander J., Timothy R. Betts, and Abhirup Banerjee.
2024. "Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review" Journal of Clinical Medicine 13, no. 15: 4442.
https://doi.org/10.3390/jcm13154442
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