The ultimate way to assess the performance of imaging systems is a clinical trial. Due to its limitation by cost and duration, several research groups are investigating the potential to replace clinical trials in part with virtual clinical trials (VCT) as a more efficient alternative. In this paper, we propose a VCT design to compare the microcalcification (μcalc) detection performance in full field digital mammography (FFDM) and digital breast tomosynthesis (DBT). Digital breast phantoms with uniform and breast-texture like backgrounds and digital μcalcs were created. The μcalcs had diameters ranging from 100μm to 600μm and their attenuation properties were varied to be equivalent to 20% to 60% of the attenuation of Aluminum at 22keV. FFDM and DBT image acquisitions according to the nominal topology of a commercial imaging system were simulated with a software x-ray imaging platform. Projection images were processed with commercial image processing and reconstruction algorithms. Microcalcification detection performance was estimated by an objective taskbased assessment using channelized Hotelling observers (CHO) with Laguerre-Gauss channels and by a human observer. For DBT, single-slice (CHO3ss) and a multi-slice CHO (CHO3msa) model observers were considered. Model and human observers performed a lesion-known-statistically and location-known exactly rating-scale detection task. The decision outcomes were used as input to a receiver operating characteristic analysis and the area under the curve was used as the figure-of-merit. Using our VCT set-up, the performance of the CHO and the human observer seems to be fairly well linearly correlated. There is a trend that µcalc detection performance in DBT is higher than in FFDM.
Zhijin Li, Agnès Desolneux, Serge Muller, Pablo Milioni de Carvalho, and Ann-Katherine Carton, "Comparison of microcalcification detectability in FFDM and DBT using a virtual clinical trial," Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 105770D (Presented at SPIE Medical Imaging: February 11, 2018; Published: 7 March 2018); https://doi.org/10.1117/12.2293619.
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