Purpose: 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.
Methods: 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.
Results: 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%).
Conclusion: 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.
Keywords: CT scanning; computer aided diagnosis; iterative reconstruction; lung nodule; model-based reconstruction.
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