Kinetic modeling and multi-atlas based segmentation of 18F labeled myocardial PET

Abstract

Introduction: Absolute quantification of regional myocardial blood flow (MBF) and myocardial flow reserve (MFR) on PET scans enables comprehensive evaluation of asymptomatic and symptomatic coronary artery disease (CAD). The development of 18F-labeled MPI tracers was motivated by the limitations of the existing MPI agents for PET. (18F-fluoropentyl)triphenylphosphonium salt (18F-FPTP) is a new promising myocardial PET imaging tracer. It shows high accumulation in cardiomyocytes and rapid clearance from liver. We performed compartmental analysis of 18F-FPTP PET images in rat and evaluated two linear analyses: linear least-squares (LLS) and a basis function method (BFM) for generating parametric images. The minimum dynamic scan duration for kinetic analysis was also investigated and computer simulation undertaken. In this study, we proposed a new atlas-based segmentation for 18F- labeled myocardial PET. One atlas template with the most similar distribution as a source PET image is selected from a pool of template candidates and then pre-build myocardial ROIs of the template is used to segment the source PET image. Methods: 18F-FPTP dynamic PET (18 min) and computed tomography (CT) images were acquired from rats with myocardial infarction (MI) (n=12). Regions of interest (ROIs) were on the left ventricle, normal myocardium, and MI region. Two-compartment (K1 and k2

2C2P) and three-compartment (K1, k2 and k3

3C3P) models with irreversible uptake were compared for goodness-of-fit. Partial volume and spillover correction terms (Va and α=1 − Va) were also incorporated. LLS and BFM were applied to ROI- and voxel-based kinetic parameter estimations. Results were compared with the standard ROI-based nonlinear least-squares (NLS) results of the corresponding compartment model. A simulation explored statistical properties of the estimation methods. The multi-atlas based segmentation method was performed in 18F-FPTP PET image to find best matching template image to each source image by comparing the similarities between the images. And the polarmap was constructed for comparison. Results: The 2C2P model was most suitable for describing 18F-FPTP kinetics. Average K1, k2, and Va values were, respectively, 6.8 (ml/min/g), 1.1 (min-1), and 0.44 in normal myocardium and 1.4 (ml/min/g), 1.1 (min-1), and 0.32, in MI tissue. Ten minutes of data was sufficient for the estimation. LLS and BFM estimations correlated well with NLS values for the ROI level (K1: y = 1.06x + 0.13, r2 = 0.96 and y = 1.13x + 0.08, r2 = 0.97) and voxel level (K1: y = 1.22x − 0.30, r2 = 0.90 and y= 1.26x + 0.00, r2 = 0.92). Regional distribution of kinetic parametric images (αK1, K1, k2, Va) was physiologically relevant. LLS and BFM showed more robust characteristics than NLS in the simulation. In multi-atlas segmentation, the correlation (r2) between the normalized source image and the best selected template image was an average of 0.95 in the source individual -space evaluation and 0.92 in the template-space evaluation. The ROIs of the selected template were well matched to the myocardium regions of the normalized source image. Further evaluation using perfusion parametric image showed similar polarmap and highly-correlated average values (r2=0.92) in 362-segment ROIs. Conclusions: Fast kinetics and highly specific uptake of 18F-FPTP by myocardium enabled quantitative analysis with the 2C2P model using only the initial 10 min of data. LLS and BFM were feasible for estimating voxel-wise parameters. These two methods will be useful for quantitative evaluation of 18F-FPTP distribution in myocardium and in further studies with different conditions, disease models, and species. The proposed multi-atlas based segmentation showed its potential as an adequate method by sufficiently well used pre-build template ROI in segmentation and it seems to be appropriate for other 18F-labeled myocardial PET imaging.