Preliminary clinical evaluation of a cardiac motion vector field estimation method from 4D cardiac-gated myocardial perfusion PET images

305 Objectives: We have developed a new set of cardiac motion vector field (CMVF) estimation, analysis and display methods from 4D cardiac-gated (CG) myocardial perfusion (MP) PET images. The goal of this work is to evaluate the methods using 4D CG-MP PET images obtained from different reconstruction and analysis methods from patients with normal and known cardiac motion (CM) abnormalities. We acquired list-mode 4D CG-MP PET data from six patients with normal global ejection fractions (EF) and three patients with known CM abnormalities. The datasets were reconstructed using the standard image reconstruction provided by the vendor and with a new, in-house developed 4D image reconstruction method with respiratory motion (RM) and CM compensation. Specifically, the RM estimation and compensation were applied based on an equal count-based, data-driven gating method. The RM compensated data were reconstructed into CG PET images with a given number of equal time intervals, e.g., 8, 16 and 24, over each cardiac cycle. A reference frame PET image at the center of the heart cycle was then generated from the smoothed CG images using the Groupwise registration method, and the reference frame was transformed back to the individual CG images with the corresponding set of CMVF estimates. The final CM-compensated images showed significantly improved image resolution and lower image noise fluctuations as compared to the CG images obtained from the vendor method. The CMVF estimation is based on the traditional optical flow method for motion estimation and was applied to the 4D CG-MP PET images to estimate the CMVF between selected cardiac frames. The entire heart including both the left and right ventricles was used in the CM estimation. The radial, longitudinal and tangential components of the 3D CMVF over the left ventricle was grouped and displayed in a 13-segment and the standard 17-segment polar plots between each adjacent CG frames over the cardiac cycle. The data were further analyzed and the three components of the 3D CMVF in each segment were averaged and plotted as a function of time over the cardiac cycle. In general, the 3D CMVF estimates from the 4D CG-MP PET images with RM & CM motion compensation show more consistent patterns with less variations over time than those from the images without the compensations. The radial and longitudinal components also show more consistent changes between segments than the tangential component. Further, the 13-segment results show a general CM pattern and the 17-segment results show the CM in more detail, without the effect of noise variations. In patients with known CM abnormalities, the 3D CMVF shows asynchronized beating heart motion in certain segments, which is consistent with clinical findings. In typical normal patients, the components of the 3D CMVF demonstrate synchronized beating heart motion among all segments. In one patient with normal global EF, our results indicate a small but noticeable asynchronized motion among segments along the septal wall. A re-examination of the 4D CG-MP PET images confirms the finding. The developed 3D CMVF estimation, may hold promise for accurate characterization of CM and detection of CM abnormalities from 4D CG-MP PET images. The improved image quality obtained with RM and CM compensation provide more accurate estimations than quality obtained without compensation. The additional quantitative ‘cardiomics’ information of the left ventricular motion, in conjunction with perfusion information, from the same 4D CG-MP PET images may add additional important diagnostic information in subclinical and clinical manifest cardiac diseases.