Title :
Regularized Image Reconstruction Algorithms for Dual-Isotope Myocardial Perfusion SPECT (MPS) Imaging Using a Cross-Tracer Prior
Author :
He, Xin ; Cheng, Lishui ; Fessler, Jeffrey A. ; Frey, Eric C.
Author_Institution :
Russell H. Morgan Dept. of Radiol. & Radiol. Sci., Johns Hopkins Univ., Baltimore, MD, USA
fDate :
6/1/2011 12:00:00 AM
Abstract :
In simultaneous dual-isotope myocardial perfusion SPECT (MPS) imaging, data are simultaneously acquired to determine the distributions of two radioactive isotopes. The goal of this work was to develop penalized maximum likelihood (PML) algorithms for a novel cross-tracer prior that exploits the fact that the two images reconstructed from simultaneous dual-isotope MPS projection data are perfectly registered in space. We first formulated the simultaneous dual-isotope MPS reconstruction problem as a joint estimation problem. A cross-tracer prior that couples voxel values on both images was then proposed. We developed an iterative algorithm to reconstruct the MPS images that converges to the maximum a posteriori solution for this prior based on separable surrogate functions. To accelerate the convergence, we developed a fast algorithm for the cross-tracer prior based on the complete data OS-EM (COSEM) framework. The proposed algorithm was compared qualitatively and quantitatively to a single-tracer version of the prior that did not include the cross-tracer term. Quantitative evaluations included comparisons of mean and standard deviation images as well as assessment of image fidelity using the mean square error. We also evaluated the cross tracer prior using a three-class observer study with respect to the three-class MPS diagnostic task, i.e., classifying patients as having either no defect, reversible defect, or fixed defects. For this study, a comparison with conventional ordered subsets-expectation maximization (OS-EM) reconstruction with postfiltering was performed. The comparisons to the single-tracer prior demonstrated similar resolution for areas of the image with large intensity changes and reduced noise in uniform regions. The cross-tracer prior was also superior to the single-tracer version in terms of restoring image fidelity. Results of the three-class observer study showed that the proposed cross-tracer prior and the convergent algorithms improved the im- ge quality of dual-isotope MPS images compared to OS-EM.
Keywords :
convergence of numerical methods; image registration; maximum likelihood estimation; medical image processing; radioactive tracers; single photon emission computed tomography; COSEM framework; PML algorithms; complete data OS-EM framework; convergence acceleration; cross tracer prior; dual isotope MPS SPECT; fixed defects; joint estimation problem; maximum a posteriori solution; myocardial perfusion SPECT imaging; no defect; penalized maximum likelihood algorithms; radioactive isotope distributions; regularized image reconstruction algorithms; reversible defect; simultaneous dual isotope MPS projection data; Estimation; Image quality; Image reconstruction; Imaging; Isotopes; Joints; Pixel; Dual isotope imaging; emission computed tomography; joint estimation; maximum a posteriori (MAP) reconstruction; Algorithms; Computer Simulation; Coronary Circulation; Heart; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Likelihood Functions; Models, Cardiovascular; Myocardial Perfusion Imaging; Myocardium; Phantoms, Imaging; Radioisotopes; Radiopharmaceuticals; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique; Tomography, Emission-Computed, Single-Photon;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2010.2087031