Adaptive Statistical Iterative Reconstruction: Assessment of Image Noise and Image Quality in Coronary CT Angiography

Abstract

OBJECTIVE: The purpose of our study was to determine the effect of Adaptive Statistical Iterative Reconstruction (ASIR) on cardiac CT angiography (CTA) signal, noise, and image quality. MATERIALS AND METHODS: We evaluated 62 consecutive patients at three sites who underwent clinically indicated cardiac CTA using an ASIR-capable 64-MDCT scanner and a low-dose cardiac CTA technique. Studies were reconstructed using filtered back projection (FBP), ASIR-FBP composites using 20-80% ASIR, and 100% ASIR. The signal and noise were measured in the aortic root and each of the four coronary arteries. Two blinded readers graded image quality on a 5-point Likert scale and determined the proportion of interpretable segments. All segments were included for analysis regardless of size. RESULTS: In comparison with FBP (0% ASIR), the use of 20%, 40%, 60%, 80%, and 100% ASIR resulted in reduced image noise between groups (-7%, -17%, -26%, -35%, and -43%, respectively; p < 0.001) without difference in signal (p = 0.60). There were significant differences between groups (0%, 20%, 40%, 60%, 80%, and 100% ASIR) in the Likert scores (1.5, 2.1, 3.7, 3.8, 2.0, and 1.1, respectively; p < 0.001) and proportion of interpretable segments (88.7%, 89.3%, 90.5%, 90.4%, 88.0%, and 87.3%, respectively; p < 0.001). Reconstruction using 40% and 60% ASIR had the highest Likert scores and largest proportion of interpretable segments. In comparison with FBP, each was associated with higher Likert scores and increased interpretable segments (p < 0.001 for all). CONCLUSION: ASIR resulted in noise reduction and significantly impacted image quality. When using a low tube current technique, cardiac CTA reconstruction using 40% or 60% ASIR significantly improved image quality and the proportion of interpretable segments compared with FBP reconstruction.