Grating-based phase contrast mammography can help facilitate breast cancer diagnosis, as several research works have demonstrated. To translate this technique to the clinics, it has to be adapted to cover a large field of view within a limited exposure time and with a clinically acceptable radiation dose. This indicates that a straightforward approach would be to install a grating interferometer (GI) into a commercial mammography device. We developed a wave propagation based optimization method to select the most convenient GI designs in terms of phase and dark-field sensitivities for the Philips Microdose Mammography (PMM) setup. The phase sensitivity was defined as the minimum detectable breast tissue electron density gradient, whereas the dark-field sensitivity was defined as its corresponding signal-to-noise Ratio (SNR). To be able to derive sample-dependent sensitivity metrics, a visibility reduction model for breast tissue was formulated, based on previous research works on the dark-field signal and utilizing available Ultra-Small-Angle X-ray Scattering (USAXS) data and the outcomes of measurements on formalin-fixed breast tissue specimens carried out in tube-based grating interferometers. The results of this optimization indicate the optimal scenarios for each metric are different and fundamentally depend on the noise behavior of the signals and the visibility reduction trend with respect to the system autocorrelation length. In addition, since the inter-grating distance is constrained by the space available between the breast support and the detector, the best way we have to improve sensitivity is to count on a small G2 pitch.
Carolina Arboleda Clavijo, Zhentian Wang, Thomas Köhler, Udo van Stevendaal, Gerhard Martens, Matthias Bartels, Pablo Villanueva-Perez, Ewald Roessl, and Marco Stampanoni, "Design of a sensitive grating-based phase contrast mammography prototype (Conference Presentation)," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 1013218 (Presented at SPIE Medical Imaging: February 15, 2017; Published: 2 May 2017); https://doi.org/10.1117/12.2253875.5361821903001.
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