Joint cardiac and respiratory motion correction and super-resolution reconstruction in coronary PET/CT

Abstract

Coronary artery disease is marked by the development of chronic inflammation in the vascular arteries that is associated with coronary plaques. Positron emission tomography (PET) is capable of detecting inflammation through activated macrophage uptake of FDG. Unfortunately, in conventional cardiac PET, respiratory and cardiac motion during acquisition leads to severe blurring of the resulting images and an effective spatial resolution inadequate for plaque detection and localization. In this paper, we extend our previous image-domain approach to a fully integrated, data-domain method that starts from the observed projection data and performs a model-based inversion and motion correction of all the data to create a high-resolution focused cardiac image. We term the new approach Data-domain Cardiac Shape Tracking and Adjustment for Respiration or D-CSTAR. In contrast to existing image domain methods the image reconstruction and motion correction steps are not separated. Unlike current data domain methods both cardiac and respiratory motions are compensated for. In D-CSTAR, cardiac motion parameters are estimated from X-ray CT images acquired in a breath-hold state. This cardiac motion information is incorporated in a unified PET reconstruction functional which jointly estimates and corrects for respiratory motion, compensates for phase aligned cardiac motion, and super-resolves the image. The technique is presented and applied to simulated cardiac PET/CT data corresponding to the XCAT phantom with both cardiac and respiratory cycles. The results show a marked qualitative and quantitative improvement when compared to conventional and existing PET methods.