Mandatory Reporting of Coronary Artery Calcifications Incidentally Noted on Chest Multi-Detector Computed Tomography: A Multicentre Experience.

BACKGROUND: Coronary Artery Calcifications (CACs) are associated with coronary atherosclerosis and Cardiovascular (CV) events. In "non-cardiovascular" settings, CACs can be easily detected on chest Multi-Detector Computed Tomography (MDCT). Their evaluation may help to better stratify CV risk in the general population, especially for primary prevention.

AIMS: We retrospectively evaluated the relationship between CAC distribution and CV risk, determined by Framingham Risk Score (FRS), in a cohort of patients who underwent chest MDCT performed for several clinical indications.

METHOD: We retrospectively recruited 305 patients (194 men, 111 women; mean age 70.5 years) from 3 different Italian centres. Patients with coronary stent, pacemaker and/or CV devices were excluded from the study. Circumflex Artery (LCX), Left Main Coronary Artery (LMCA), left Anterior Descending artery (LAD) and right coronary artery (RCA) were analysed.

RESULTS: From a total population of 305 patients, 119 (39%) had low FRS (<10%), 115 (38%) had intermediate FRS (10-20%), and 71 (23%) had high FRS (>20%). The study identified 842 CACs located in decreasing order as follows: RCA (34.5%), LAD (32.3%), LCX (28%) and LMCA (13%). Statistical two-step analysis subdivided patients into two clusters according to FRS (risk threshold = 12.38%): cluster I (mean 9.34) and cluster II (mean 15.09). A significant association between CAC distribution and cluster II was demonstrated. CACs were mostly detected in patients with intermediate FRS. All patients (100%) with the highest CV risk showed intermediate RCA and LMCA involvement.

CONCLUSION: Radiologists can note the distribution of CACs on a chest MDCT and should mandatorily record them in their reports. Depending on CAC presence and location, these findings may have important clinical implications, mostly in asymptomatic patients with intermediate FRS. This information may reclassify a patients' CV risk and improve clinical management.