Improved myocardial perfusion PET imaging with MRI assisted reconstruction incorporating multi-resolution joint entropy.
Myocardial perfusion (MP) PET imaging plays an important role in risk assessment and stratification of patients with coronary artery disease. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction method incorporating a wavelet-based joint entropy (WJE) prior for MP PET imaging. Using the XCAT phantom, we first simulated three MP PET datasets, one with normal perfusion and the other two with non-transmural and transmural regionally reduced perfusion of the left ventricular myocardium. We then simulated MP PET datasets of the three cases with respiratory and cardiac (RC) motion to represent realistic clinical situations. Moreover, two MR image datasets of the same subjects without and with RC motion were simulated without the perfusion defect correspondence. Using the simulated data, the proposed method was evaluated quantitatively in terms of noise-contrast tradeoff, and compared with the post-smoothed maximum-likelihood and the conventional MAP methods. The detectability of perfusion defects with various myocardial coverage was also evaluated through receiver operating characteristic analysis using the channelized Hotelling observer. The results demonstrated that the WJE-MAP method improved the noise-contrast tradeoff, leading to significantly enhanced defect detectability over the other two methods in the non-transmural defects, while maintaining comparable performance in the transmural defect. In addition to the simulation study, the proposed method was further evaluated on the acquired PET/MRI data of a Jaszczak phantom with cold rods. Compared with the other two methods, the WJE-MAP method improved the tradeoff between noise and contrast in the smaller rods, thereby indicating its clinical potential for improving defect detectability in MP PET/MR imaging.