1*Assistant Professor, Department of Radiological Imaging Techniques, Rayat Bahra University, Kharar, Punjab, India. Email: shiprasaroj789@gmail.com (Corresponding Author)
2Assistant Professor, Department of Radiological Imaging Techniques, Midnapore City College, West Bengal, India
3Assistant Professor, Department of Radiological Imaging Techniques, Rayat Bahra University, Kharar, Punjab, India
4Assistant Professor, Department of Radiological Imaging Techniques, Rayat Bahra University, Kharar, Punjab, India
5Assistant Professor, Department of Radiological Imaging Techniques, Saraswati College of Pharmacy, SGC Group, Gharuan, Mohali, Punjab, India
6Assistant Professor, Department of Microbiology, Swami Vivekanand Institute of Engineering and Technology, Banur, India
7Professor, Department of Radiology, Rayat Bahra University, Kharar, Punjab, India
Background: Coronary Artery Calcium Scoring (CACS), using the Agatston score in particular, is commonly utilized in early detection and assessment of coronary artery disease (CAD). ECG-gated CT scans have historically complemented the procedure using technologies such as EBCT, MDCT, and DSCT. Although effective, these methods are challenged by accuracy and efficiency.
AI Integration: Techniques have been revolutionized with advancements in artificial intelligence (AI), especially with deep learning techniques such as convolutional neural networks (CNNs). These technologies now make it possible to conduct fully automated calcium scoring from gated and non-gated CT scans with increased speed and accuracy. AI also makes it possible to derive complex imaging characteristics, including lesion location and density, improving cardiovascular risk prediction. New models integrating clinical, anatomical, and imaging data are assisting in making more personalized treatment plans.
Challenges and Future Directions: Yet, challenges like data unpredictability, limited clarity of AI algorithms, and data privacy and fairness issues persist. In spite of that, AI incorporation represents a significant leap in cardiovascular imaging, with ongoing exploration and regulation essential for safety and efficacy in clinical practice.
Keywords: Coronary Artery disease; cardiovascular disease; Artificial intelligence; Deep learning; Multidetector Computed Tomography; Electron Beam Computed Tomography
How to cite this article: Saroj S, Rana S, Kiran K, Jalal RB, Sharma P, Thakur P, Gupta LK. Overview of Machine Learning and AI Algorithms is Being Integrated into Coronary Artery Calcium Scoring. Int J Drug Deliv Technol. 2026;16(13s): 658-670. DOI: 10.25258/ijddt.16.13s.73
Source of support: Nil.
Conflict of interest: None