A Model for a Linear a-Se Detector in Simulated X-Ray Breast Imaging With Monte Carlo Software

Abstract

In-silico clinical trials with digital patient models and simulated devices are an alternative to expensive and long clinical trials on patient population for testing X-ray breast imaging apparatuses. In this work, we simulated a linear-response a-Se detector as an X-ray absorber, neglecting some physical processes, such as electro-hole tracking and thermal noise. In order to tune characteristics of the simulated images toward those of the clinical scanners, the detector response curve, modulation transfer function (MTF), and normalized noise power spectrum (NNPS) were measured on a clinical mammographic unit. The same tests were replicated in-silico via a custom-made Monte Carlo code in order to define a suitable model to modify simulated images and to have realistic pixel values, noise, and spatial resolution. The proposed approach resulted to restore the slope and the magnitude of the NNPS in simulated images toward curves evaluated on a clinical scanner. Similarly, the proposed strategy for tuning noise and spatial resolution in simulated images led to a contrast-to-noise ratio (CNR) evaluated on a custom-made phantom which differed from those in measured images less than 16% in absolute value.