The objective of this study was to compare the detectability of simulated objects within a dense breast phantom using high energy x-rays for phase sensitive breast imaging in comparison with a conventional imaging system. A 5 cm thick phantom was used which represented a compressed breast consisting of 70% glandular and 30% adipose tissue ratio in non-uniform background. The phantom had a 6 × 6 matrix of holes with milled depths ranging from 1 to 0.1 mm and diameters ranging from 4.25 to 0.25 mm representing simulated tumors. The in-line phase sensitive prototype was equipped with a micro-focus x-ray source and a flat panel detector with a 50 μm pixel pitch, both mounted on an optical rail. Phase contrast image of the phantom was acquired at 120 kVp, 4.5 mAs at source to object distance (SOD) of 68 cm and source to image detector distance (SIDD) of 170 cm with a geometric magnification (M) of 2.5. A 2.5 mm aluminum (Al) filter was used for beam hardening. The conventional image was acquired using the same porotype with the phantom in contact with the detector at 40 kVp, 12.5 mAs under SID = 68 cm. The mean glandular dose (Dg) for both the acquisitions was 1.3 mGy. The observer study and CNR analyses indicated that the phase contrast image had higher disk detectability as compared to the conventional image. The edge enhancement provided by the phase sensitive images warrants in identifying boundaries of malignant tissues and in providing optimal results in phase retrieval process. The potential demonstrated by this study for imaging a dense breast with a high energy phase sensitive x-ray imaging to improve tumor detection in warrants further investigation of this technique.
Muhammad U. Ghani, Molly D. Wong, Di Wu, Bin Zheng, Wei Chen, Laurie L. Fajardo, Xizeng Wu, and Hong Liu, "Detectability comparison of simulated objects within a dense breast phantom using high energy x-ray phase sensitive and conventional imaging systems," Proc. SPIE 10065, Biophotonics and Immune Responses XII, 100650K (Presented at SPIE BiOS: January 31, 2017; Published: 20 February 2017); https://doi.org/10.1117/12.2252447.
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