Abstract
PURPOSE: The purpose of this study was to assess the effect of obesity and iterative reconstruction on the ability to reduce exposure by studying the accuracy for detection of low-contrast low-attenuation (LCLA) liver lesions on computed tomography (CT) using a phantom model. METHODS: A phantom with four unique LCLA liver lesions (5- to 15-mm spheres, -24 to -6 HU relative to 90-HU background) was scanned without ("thin" phantom) and with ("obese" phantom) a 5-cm thick fat-attenuation ring at 150 mAs (thin phantom) and 450 mAs (obese phantom) standard exposures and at 33% and 67% exposure reductions. Images were reconstructed using standard filtered back projection (FBP) and with iterative reconstruction (Adaptive Model-Based Iterative Reconstruction strength 3, ADMIRE). A noninferiority analysis of lesion detection was performed. RESULTS: Mean area under the curve (AUC) values for lesion detection were significantly higher for the thin phantom than for the obese phantom regardless of exposure level (P < 0.05) for both FBP and ADMIRE. At 33% exposure reduction, AUC was noninferior for both FBP and ADMIRE strength 3 (P < 0.0001). At 67% exposure reduction, AUC remained noninferior for the thin phantom (P < 0.0035), but was no longer noninferior for the obese phantom (P ≥ 0.7353). There were no statistically significant differences in AUC between FBP and ADMIRE at any exposure level for either phantom. CONCLUSIONS: Accuracy for lesion detection was not only significantly lower in the obese phantom at all relative exposures, but detection accuracy decreased sooner while reducing the exposure in the obese phantom. There was no significant difference in lesion detection between FBP and ADMIRE at equivalent exposure levels for either phantom.