4-D Reconstruction With Respiratory Correction for Gated Myocardial Perfusion SPECT
UMass Chan AffiliationsDepartment of Radiology, Division of Nuclear Medicine
Document TypeJournal Article
Single photon emission computed tomography
Biological and Chemical Physics
MetadataShow full item record
AbstractCardiac single photon emission computed tomography (SPECT) images are known to suffer from both cardiac and respiratory motion blur. In this paper, we investigate a 4-D reconstruction approach to suppress the effect of respiratory motion in gated cardiac SPECT imaging. In this approach, the sequence of cardiac gated images is reconstructed with respect to a reference respiratory amplitude bin in the respiratory cycle. To combat the challenge of inherent high-imaging noise, we utilize the data counts acquired during the entire respiratory cycle by making use of a motion-compensated scheme, in which both cardiac motion and respiratory motion are taken into account. In the experiments, we first use Monte Carlo simulated imaging data, wherein the ground truth is known for quantitative comparison. We then demonstrate the proposed approach on eight sets of clinical acquisitions, in which the subjects exhibit different degrees of respiratory motion blur. The quantitative evaluation results show that the 4-D reconstruction with respiratory correction could effectively reduce the effect of motion blur and lead to a more accurate reconstruction of the myocardium. The mean-squared error of the myocardium is reduced by 22%, and the left ventricle (LV) resolution is improved by 21%. Such improvement is also demonstrated with the clinical acquisitions, where the motion blur is markedly improved in the reconstructed LV wall and blood pool. The proposed approach is also noted to be effective on correcting the spill-over effect in the myocardium from nearby bowel or liver activities.
Qi W, Yang Y, Song C, Wernick MN, Pretorius PH, King MA. 4-D Reconstruction With Respiratory Correction for Gated Myocardial Perfusion SPECT. IEEE Trans Med Imaging. 2017 Aug;36(8):1626-1635. doi: 10.1109/TMI.2017.2690819. Epub 2017 Apr 4. PMID: 28391190; PMCID: PMC5595423. Link to article on publisher's site