AI for Calcium Scoring

TL;DR

This paper reviews AI-based methods for calcium scoring in CT scans, highlighting recent advances that improve speed and reproducibility, and discusses future research directions in this field.

Contribution

It provides a comprehensive overview of AI techniques for calcium scoring, emphasizing recent innovations and potential future developments.

Findings

AI methods enable faster calcium scoring

AI improves reproducibility of measurements

AI techniques are expanding in clinical applications

Abstract

Calcium scoring, a process in which arterial calcifications are detected and quantified in CT, is valuable in estimating the risk of cardiovascular disease events. Especially when used to quantify the extent of calcification in the coronary arteries, it is a strong and independent predictor of coronary heart disease events. Advances in artificial intelligence (AI)-based image analysis have produced a multitude of automatic calcium scoring methods. While most early methods closely follow standard calcium scoring accepted in clinic, recent approaches extend this procedure to enable faster or more reproducible calcium scoring. This chapter provides an introduction to AI for calcium scoring, and an overview of the developed methods and their applications. We conclude with a discussion on AI methods in calcium scoring and propose potential directions for future research.