Noise indices adjusted to body mass index and an iterative reconstruction algorithm maintain image quality on low-dose contrast-enhanced liver CT

OBJECTIVES: Since body mass index (BMI) affects medical imaging quality or noise due to penetration of the radiation through bodies with varying sizes, this study aims to investigate and determine the optimal BMI-adjusted noise index (NI) setting on the contrast-enhanced liver CT scans obtained using 3D Smart mA technology with adaptive statistical iterative reconstruction (ASIR 2.0) algorithm. MATERIALS AND METHODS: A total of 320 patients who had contrast-enhanced liver CT scans were divided into two equal-sized groups: A (18.5 kg/m 2 ≤BMI<24.9 kg/m 2 ) and B (24.9 kg/m 2 ≤ BMI ≤34.9 kg/m 2 ). The two groups were randomly divided into four subgroups with an NI of 11, 13, 15, and 17. All images were reconstructed with 50% ASIR 2.0. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated after the late arterial, portal venous, and equilibrium phases were completed. Images were evaluated by two radiologists using a subjective 0 –5 scale. Mean CT dose index of volume, dose-length product, and effective dose (ED) were calculated and compared using one-way ANOVA. RESULTS: In group A, the best-quality images obtained at the lowest ED were scanned at an NI of 15 in the late arterial phase, and at an NI of 17 in the portal venous and equilibrium phases. In group B, the best results were obtained at an NI of 13 in the late arterial phase, and at an NI of 15 in the portal venous and equilibrium phases. CONCLUSION: Adjusting NI and iterative reconstruction algorithm based on body mass index can help improve image quality on contrast-enhanced liver CT scans, even at low radiation dose.