Purpose: We are developing a high-resolution CMOS detector-based cone-beam breast CT (CBBCT) system with offset-detector geometry. The purpose is to estimate the mean glandular dose (MGD) for offset-detector geometry using clinical datasets that provide for heterogeneous tissue distribution and real shape and compare it to the reference geometry using a centered detector.
Methods: 30 clinical breast CT datasets acquired on a CBBCT system with a 40x30-cm centered (no offset) detector (1024×768 pixels) were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm. The images were segmented into skin, adipose, and fibroglandular tissues. The segmented breast models were imported to a Monte Carlo simulation toolkit (GATE 8.0) and were assigned Hammerstein’s elemental compositions. Three imaging geometries were considered: (1) 40x30-cm centered detector corresponding to acquisition geometry as reference; (2) 30x30-cm detector with 5cm offset; and (3) 25x30-cm detector with 7.5cm offset. MC simulations were conducted with 49kV (1.39mm HVL), 0.3x0.3-mm focal spot, and with 10E6 photons. The normalized glandular dose coefficient (DgNCT) was obtained for each geometry and breast. MGD was obtained as the product of DgNCT and the measured air kerma at the axis-of-rotation.
Results: The coefficient of variation was less than 0.7%. For the 30 clinical breast CT datasets, the mean±SD and the median (inter-quartile range) of the MGD (mGy) were 9.63±2.84 and 8.99 (7.68–11.31) for the 40x30-cm reference geometry, 8.19±2.62 and 7.70 (6.74–8.86) for the 30x30-cm detector with 5cm offset, and 5.35±1.39 and 5.15 (4.22–5.94) for the 25x30-cm detector with 7.5cm offset. The median computational time for MC simulations was approximately 40 minutes for each case.
Conclusion: This study demonstrates the potential for dose reduction using offset-detector geometry with heterogeneous tissue distribution and real breast shapes. The estimated dose reduction for the 30x30-cm detector with 5cm offset and the 25x30-cm detector with 7.5cm offset were 14.8% and 44.4%, respectively.
Not Applicable / None Entered.