Improved myocardial perfusion PET imaging with MRI assisted reconstruction incorporating multi-resolution joint entropy

Abstract

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.

Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction

“…Bowsher et al pioneered the incorporation of MRI information into PET reconstruction to estimate 18 F-FDG distributions in rat flank tumors (Bowsher et al 2004). Wang et al proposed a reconstruction method for myocardial perfusion PET imaging that utilizes the joint entropy between features of PET and MRI images derived from wavelet transform as a regularization before enhancing the quality of PET image reconstruction (Wang et al 2018). Additionally, due to this correlation, joint reconstruction of PET-MRI becomes imperative.…”

Improved low-dose positron emission tomography image reconstruction using deep learned prior

“…Earlier techniques applied segmented anatomical images in MAP reconstruction to encourage smoothness within the anatomical regions and boundaries in the functional image (Lipinski et al 1997, Baete et al 2004. Recent studies use the similarity measure between the functional and anatomical images to formulate the prior, which does not rely on segmentation or labeling of the anatomical images (Nuyts 2007, Tang and Rahmim 2009, Wang et al 2018. These algorithms quantitatively improved PET image reconstruction in terms of the noise-bias and noise-contrast tradeoffs as well as the lesion detectability.…”