Radiation Dose Reduction in CT Myocardial Perfusion Imaging Using SMART-RECON

In this paper, a newly developed statistical model-based image reconstruction [referred to as Simultaneous Multiple Artifacts Reduction in Tomographic RECONstruction (SMART-RECON)] is applied to low dose computer tomography (CT) myocardial perfusion imaging (CT-MPI). This method uses the nuclear norm of the spatial-temporal image matrix of the CT-MPI images as a regularizer, rather than a conventional spatial regularizer that incorporates image smoothness, edge preservation, or spatial sparsity into the reconstruction. In addition to providing the needed noise reduction for low-dose CT-MPI, SMART-RECON provides images with spatial resolution and noise power spectrum (NPS) properties, which are independent of contrast and dose levels. Both numerical simulations and in vivo animal studies were performed to validate the proposed method. In these studies, it was found that: 1) quantitative accuracy of perfusion maps in CT-MPI was well maintained for radiation dose level as low as 10 mAs per image frame, compared with the reference standard of 200 mAs for conventional filtered backprojection; 2) flow-occluded myocardium in the porcine heart was well delineated by SMART-RECON at 10 mAs per frame when compared with model-based image reconstruction using spatial total variation (TV) as the regularizer (referred to as TV-SIR) or spatial-temporal TV (ST-TV-SIR); the CT-MPI results were confirmed with positron-emission tomography imaging; 3) image sharpness in SMART-RECON images was nearly independent of image contrast level and radiation dose level, in stark contrast to TV-SIR and ST-TV-SIR, which displayed a strong dependence on both image contrast and radiation dose levels; and 4) the structure of the dose-normalized NPS for the SMART-RECON method did not depend on dose, while the TV-SIR and ST-TV-SIR NPS structure was dose-dependent.