Evaluation of automatic tube current modulation in a CT scanner using a customised homogeneous phantom

<i>Objective.</i>The introduction of automatic tube current modulation (ATCM) has resulted in complex relationships between scanner parameters, patient body habitus, radiation dose, and image quality. ATCM adjusts tube current based on x-ray attenuation variations in the scan region, and overall patient dose depends on a combination of factors. This work aims to develop mathematical models that predict CT radiation dose and image noise in terms of attenuating diameter and all relevant scanner parameters.<i>Approach.</i>A homogenous phantom, equipped with the features to conduct discrete and continuous adaption tests, was developed to model ATCM in a Philips CT scanner. Scanner parameters were varied based on theoretical dose relationships, and a MATLAB script was developed to extract data from DICOM images. R statistical software was employed for data analysis, plotting, and regression modelling.<i>Main Results.</i>Phantom data provided the following insights: Median tube current decreased by 81% as tube potential varied from 80 kVp to 140 kVp. Doubling the DoseRight Index (DRI) from 12 to 24, at 24 cm diameter, produced a 294% increase in mA and a 46% decrease in noise. Mean mA increased by 53% whilst mean noise increased by 5.7% as helical pitch increased from 0.6 to 0.925. Changing rotation time from 0.33s to 0.75s gave a 56% reduction in mean mA and no change in image noise. Increasing detector collimation (<i>n × T</i>) resulted in higher tube currents and lower output image noise values, as<i>n</i>and<i>T</i>were varied independently. Interpreting these results to apply transformations relevant to each independent variable produced models for tube current and noise with adjusted R-squared values of 0.965 and 0.912, respectively.<i>Significance.</i>The models developed more accurately predict radiation dose and image quality for specific patients and scanner settings. They provide imaging professionals with a practical tool to optimize scan protocols according to patient diameters and clinical objectives.