Estimation and comparison of cancer incidence risk using two algorithms in multi-slice CT systems for patients undergoing coronary CT angiography

The increasing use of Coronary CT Angiography (CCTA) raises concerns regarding radiation exposure and its associated cancer risks. This study aims to evaluate the effectiveness of the Siemens CARE kV algorithm in reducing radiation doses and cancer incidence risk compared to the Automatic Exposure Control (AEC) algorithm in adult patients undergoing CCTA. This retrospective study involved a cohort of 101 patients, comprising 55 women and 46 men, who underwent Siemens single-source 1 × 64-slice Multi-Detector CT (Somatom Definition AS) for CCTA. Demographic data and radiation dose parameters, including Computed Tomography Dose Index (CTDIvol) and Dose-Length Product (DLP) were recorded. Effective and organ doses were calculated using ImPACT software, and Lifetime Attributable Risk (LAR) was estimated based on BEIR VII data. The Effective Doses (EDs) for AEC and CARE kV algorithms were 9.59 ± 3.84 mSv and 8.04 ± 3.99 mSv, respectively. The cancer incidence risk was significantly lower for the CARE kV algorithm, with LAR estimates of 7.27 ± 4.01 per 100,000 populations compared to 13.88 ± 10.76 for AEC. The CARE kV algorithm demonstrated a 27.07% reduction in LAR. The findings suggest that the CARE kV algorithm provides a significant reduction in radiation exposure and associated cancer risks compared to the AEC algorithm. These results support the optimization of CT protocols to enhance patient safety while maintaining diagnostic efficacy.