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

Abstract

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. 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. 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). 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.