Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors.

Abstract

Background: Coronary artery disease (CAD) is the third leading cause of death worldwide, so prevention and early diagnosis play important roles to reduce mortality and morbidity. Traditional risk-score assessments were used to find the at-risk patients in order to prevent or early treatment of CAD. Adding imaging data to traditional risk-score systems will able us to find these patients more confidently and reduce the probable mismanagements.

Main text: Measuring the vascular calcification by coronary artery calcium (CAC) score can prepare valuable data for this purpose. Using CAC became more popular in recent years. The most applicable method to evaluate CAC is Agatston scoring using computed tomography (CT) scanning. Patients are classified into several subgroups: no evidence of CAD (score 0), mild CAD (score 1-10), minimal CAD (score 11-100), moderate CAD (score 101-400), and severe CAD (score > 400) and higher than1000 as the extreme risk of CVD events.

Conclusions: CAC assessment was recommended in the patients older than 40 years old with CAD risk factors, the ones with stable angina, borderline-to-intermediate-risk group, etc. According to the results of the CAC the patients may be candidate for further evaluation for needing revascularization, medical treatment, or routine follow-up. Adding artificial intelligence (AI) to CAC will prepare more data and can increase the reliability of our approach to the patients promising a bright future to improve this technology.