Dose-efficiency quantification of computed tomography systems using a model-observer

Recent advances in computed tomography (CT) technology have considerably improved the quality of CT images and reduced radiation exposure in patients. At present, however, there is no generally accepted figure of merit (FOM) for comparing the dose efficiencies of CT systems.

(i) To establish an FOM that characterizes the quality of CT images in relation to the radiation dose by means of a mathematical model observer and (ii) to evaluate the new FOM on different CT systems and image reconstruction algorithms.

Images of a homogeneous phantom with four low-contrast inserts were acquired using three different CT systems at three dose levels and a representative protocol for CT imaging of low-contrast objects in the abdomen. The images were reconstructed using filtered-back projection and iterative algorithms. A channelized hotelling observer with difference-of-Gaussian channels was applied to compute the detectability ( $$ ). This was done for each insert and each of the considered imaging conditions from square regions of interest (ROIs) that were (semi-)automatically centered on the inserts. The estimated detectabilities ( $$ ) were averaged in the first step over the three dose levels ( $$ ), and subsequently over the four contrast inserts ( $$ ). All calculation steps included a dedicated assessment of the related uncertainties following accepted metrological guidelines.

The determined detectabilities ( $$ ) varied considerably with the contrast and diameter of the four inserts, as well as with the radiation doses and reconstruction algorithms used for image generation ( $$ = 1.3-5.5). Thus, the specification of a single detectability as an FOM is not well suited for comprehensively characterizing the dose efficiency of a CT system. A more comprehensive and robust characterization was provided by the averaged detectabilities $$ and, in particular, $$ . Our analysis reveals that the model observer analysis is very sensitive to the exact position of the ROIs.

The presented automatable software approach yielded with the weighted detectability $$ an objective FOM to benchmark different CT systems and reconstruction algorithms in a robust and reliable manner. An essential advantage of the proposed model-observer approach is that uncertainties in the FOM can be provided, which is an indispensable prerequisite for type testing.