Simultaneous reduction of radiation dose and scatter-to-primary ratio using a truncated detector and advanced
Hsin Wu Tseng1, Zhiyang Fu1, Srinivasan Vedantham1,2
1Department of Medical Imaging, The University of Arizona, Tucson, AZ, United States of America.
Abstract:
Objective. To determine the minimum detector width along the fan-angle direction in offset-detector cone-beam breast CT for multiple advanced reconstruction algorithms and to investigate the effect on radiation dose, scatter, and image quality.Approach.Complete sinograms (m×n= 1024 × 768 pixels) of 30 clinical breast CT datasets previously acquired on a clinical-prototype cone-beam breast CT system were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm and served as the reference. Complete sinograms were retrospectively truncated to varying widths to understand the limits of four image reconstruction algorithms-FDK with redundancy weighting (FDK-W), compressed-sensing based FRIST, fully-supervised MS-RDN, and self-supervised AFN. Upon determining the truncation limits, numerical phantoms generated by segmenting the reference reconstructions into skin, adipose, and fibroglandular tissues were used to determine the radiation dose and scatter-to-primary ratio (SPR) using Monte Carlo simulations.Main results.FDK-W, FRIST, and MS-RDN showed artifacts whenm< 596, whereas AFN reconstructed images without artifacts form> = 536. Reducing the detector width reduced signal-difference to noise ratio (SDNR) for FDK-W, whereas FRIST, MS-RDN and AFN maintained or improved SDNR. Reference reconstruction and AFN withm= 536 had similar quantitative measures of image quality.Significance.For the 30 cases, AFN withm= 536 reduced the radiation dose and SPR by 37.85% and 33.46%, respectively, compared to the reference. Qualitative and quantitative image quality indicate the feasibility of AFN for offset-detector cone-beam breast CT. Radiation dose and SPR were simultaneously reduced with a 536 × 768 detector and when used in conjunction with AFN algorithm had similar image quality as the reference reconstruction.


