Author: Jing-Tzyh Alan Chiang, Andrew Karellas, Thomas C Larsen, Hsin Wu Tseng, Srinivasan Vedantham 👨🔬
Affiliation: Department of Biomedical Engineering, The University of Arizona, Department of Medical Imaging, The University of Arizona 🌍
Purpose: To investigate the performance of dedicated breast computed tomography (BCT) for the the tasks of detection of soft tissue lesions and microcalcifications using cascaded systems analysis. The objective was to identify which of the two tasks may need more attention for improvement.
Methods: Signal and noise were propagated through the imaging chain using a cascaded systems model to obtain modulation transfer function and noise power spectrum. Two imaging tasks were considered, a cylindrical object simulating a soft tissue mass lesion of 4 mm diameter, and a cluster of microcalcifications modeled as 0.22 mm diameter spheres. Detectability indices using three numerical observer models were obtained for various X-ray detector scintillator thickness and acquisition conditions at a fixed 4.5 mGy mean glandular dose (MGD), which corresponds to the average MGD reported for mammography by ACRIN-DMIST.
Results: Detectability index trends are reversed between soft tissue lesion and microcalcification cluster for the range of X-ray tube voltages and filtration studied, indicating a potential need for compromise. However, for the 150 combinations studied (6 kV settings × 5 Cu beam filter thickness × 5 CsI:Tl scintillator thickness) and for each of the 3 numerical observer models, there was not a single instance where the detectability index for the microcalcification cluster exceeded that for the soft tissue lesion.
Conclusion: When the lesion type is unknown, such as during breast cancer screening, it is more appropriate to optimize the BCT system parameters for the task of detecting a microcalcification cluster, as the detectability index for the soft tissue lesion exceeded that for the microcalcification cluster for all conditions investigated.