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Cardiac Contraction Motion Compensation in Gated Myocardial Perfusion Spect: A Comparative Study Publisher Pubmed



Salehi N1, 2 ; Rahmim A3, 4 ; Fatemizadeh E5 ; Akbarzadeh A2 ; Farahani MH2 ; Farzanefar S6 ; Ay MR1, 2
Authors
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Authors Affiliations
  1. 1. Department of Medical Physics and Biomedical engineering, School of Medicine, Tehran University of Medical Science, Tehran, Iran
  2. 2. Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
  4. 4. Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
  5. 5. Electrical Engineering Department, Sharif University of Technology, Tehran, Iran
  6. 6. Department of Nuclear Medicine, Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran

Source: Physica Medica Published:2018


Abstract

Introduction: Cardiac contraction significantly degrades quality and quantitative accuracy of gated myocardial perfusion SPECT (MPS) images. In this study, we aimed to explore different techniques in motion-compensated temporal processing of MPS images and their impact on image quality and quantitative accuracy. Material and method: 50 patients without known heart condition underwent gated MPS. 3D motion compensation methods using Motion Freezing by Cedars Sinai (MF), Log-domain Diffeomorphic Demons (LDD) and Free-Form Deformation (FFD) were applied to warp all image phases to fit the end-diastolic (ED) phase. Afterwards, myocardial wall thickness, myocardial to blood pool contrast, and image contrast-to noise ratio (CNR) were measured in summed images with no motion compensation (NoMC) and compensated images (MF, LDD and FFD). Total Perfusion Defect (TPD) was derived from Cedars-Sinai software, on the basis of sex-specific normal limits. Result: Left ventricle (LV) lateral wall thickness was reduced after applying motion compensation (p < 0.05). Myocardial to blood pool contrast and CNR in compensated images were greater than NoMC (p < 0.05). TPD_LDD was in good agreement with the corresponding TPD_MF (p = 0.13). Conclusion: All methods have improved image quality and quantitative performance relative to NoMC. LDD and FFD are fully automatic and do not require any manual intervention, while MF is dependent on contour definition. In terms of diagnostic parameters LDD is in good agreement with MF which is a clinically accepted method. Further investigation along with diagnostic reference standards, in order to specify diagnostic value of each technique is recommended. © 2018 Associazione Italiana di Fisica Medica
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