Impact of multidetector computed tomography scan parameters, novel reconstruction settings, and lung nodule...

Novel CT reconstruction techniques strive to maintain image quality and processing efficiency. The purpose of this study is to investigate the impact of a newer hybrid iterative reconstruction technique, Adaptive Statistical Iterative Reconstruction-V (ASIR-V), in combination with various CT scan parameters on the semi-automated quantification using various lung nodules.

A chest phantom embedded with eight spherical objects was scanned using varying CT parameters such as tube current and ASIR-V levels. We calculated absolute percentage error (APE) and mean APE (MAPE) using differences between the semi-automated measured diameters and known dimensions. Predictive variables were assessed using a multivariable general linear model. The linear regression slope coefficients (β) were reported to demonstrate effect size and directionality.

The APE of the semi-automated measured diameters was higher in ground-glass than solid nodules (β = 9.000, p < 0.001). APE had an inverse relationship with nodule diameter (mm; β = -3.499, p < 0.001) and tube current (mA; β = -0.006, p < 0.001). MAPE did not vary based on the ASIR-V level (range: 5.7%-13.1%).

Error is dominated by nodule characteristics with a small effect of tube current. Regardless of phantom size, nodule size accuracy is not affected by tube voltage or ASIR-V level, maintaining accuracy while maximizing radiation dose reduction.