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      Single-scan rest/stress imaging with 99mTc-Sestamibi and cadmium zinc telluride-based SPECT for hyperemic flow quantification: A feasibility study evaluated with cardiac magnetic resonance imaging

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          Abstract

          Introduction

          We aimed to evaluate whether the hyperemic myocardial blood flow (MBF) can be estimated using cadmium zinc telluride (CZT)-based single-photon emission computed tomography (SPECT) cameras with a single, rapid rest/stress dynamic scan. Dynamic contrast-enhanced (DCE) cardiac magnetic resonance imaging (MRI) was used as a reference modality for flow measurement.

          Materials and methods

          The proposed protocol included both the rest and stress acquisitions within a 24-min scan. Patients were first injected with 99mTc-Sestamibi at the resting state. Sixty minutes after the first injection, the subject was positioned via scintigraphy, after which the list-mode data acquisition was initiated and continued for 24 minutes. Five minutes after data acquisition was initiated, a stressed state was induced via dipyridamole infusion, after which a second dose of 99mTc-Sestamibi was injected. Dynamic SPECT images were reconstructed for all subjects, who also underwent T1-weighted cardiac DCE-MRI performed on days other than those of the SPECT studies. MBF values were estimated for the rest and stress MRI studies, and for the stress portion of the SPECT study. The SPECT-measured hyperemic MBF was compared with the MR-measured hyperemic MBF and coronary flow reserve (CFR), based on the regions of interest.

          Results

          A total of 30 subjects were included in this study. The hyperemic MBF estimated from SPECT showed a strong correlation with the MR-measured hyperemic MBF (r 2 = 0.76) and a modest correlation with the MR-measured CFR (r 2 = 0.56). Using MR-measured CFR <1.3 as a cutoff for coronary stenosis, we found that the SPECT-measured hyperemic MBF served as a useful clinical index with 94% sensitivity, 90% specificity, and 93% accuracy.

          Conclusions

          Hyperemic MBF can be measured with a rapid, single-scan rest/stress study with CZT-based SPECT cameras.

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          Most cited references38

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          A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors.

          A generalized expectation-maximization (GEM) algorithm is developed for Bayesian reconstruction, based on locally correlated Markov random-field priors in the form of Gibbs functions and on the Poisson data model. For the M-step of the algorithm, a form of coordinate gradient ascent is derived. The algorithm reduces to the EM maximum-likelihood algorithm as the Markov random-field prior tends towards a uniform distribution. Three different Gibbs function priors are examined. Reconstructions of 3-D images obtained from the Poisson model of single-photon-emission computed tomography are presented.
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            Does quantification of myocardial flow reserve using rubidium-82 positron emission tomography facilitate detection of multivessel coronary artery disease?

            Relative myocardial perfusion imaging (MPI) is the standard imaging approach for the diagnosis and prognostic work-up of coronary artery disease (CAD). However, this technique may underestimate the extent of disease in patients with 3-vessel CAD. Positron emission tomography (PET) is also able to quantify myocardial blood flow. Rubidium-82 ((82)Rb) is a valid PET tracer alternative in centers that lack a cyclotron. The aim of this study was to assess whether assessment of myocardial flow reserve (MFR) measured with (82)Rb PET is an independent predictor of severe obstructive 3-vessel CAD.
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              Models for computer simulation studies of input functions for tracer kinetic modeling with positron emission tomography.

              In tracer kinetic modeling with Positron Emission Tomography (PET), the direct measurement (piecewise linear approximation) of plasma time-activity curve of tracer (PTAC) is often used as the input function to estimate regional physiological parameters. However, no explicit general model is available for PTAC itself, which limits the further study of the effects of PTAC, such as PTAC measurement noise or PTAC sampling schedules, on the physiological parameters estimation. A PTAC model is proposed in this paper and compared with other four possible candidates. Eight sets of [18F]-fluoro-2-deoxy-D-glucose (FDG) experimental data were used to test the models and several statistical criteria were used to validate their adequacy. An application of the model to improve the estimation of local cerebral metabolic rate of glucose (LCMRGlc) is presented. This model is also expected to be useful for generating realistic PTAC curves in computer simulation studies of other tracers and their kinetic modeling characteristics.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Resources
                Role: Data curationRole: InvestigationRole: Resources
                Role: Data curation
                Role: Data curation
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                17 August 2017
                2017
                : 12
                : 8
                : e0183402
                Affiliations
                [1 ] Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan
                [2 ] Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taiwan
                [3 ] Department of Nuclear Medicine, Chang Gung Memorial Hospital, Linkou, Taiwan
                [4 ] Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan
                [5 ] Center for Advanced Molecular Imaging and Translation & Cyclotron Center, Chang Gung Memorial Hospital, Linkou, Taiwan
                [6 ] Department of Cardiology, Chang Gung Memorial Hospital, Linkou, Taiwan
                University of Alabama at Birmingham, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ‡ These authors also contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-1039-7983
                Article
                PONE-D-16-47422
                10.1371/journal.pone.0183402
                5560722
                28817662
                407b8586-60c5-4dd2-86a2-433cb660233a
                © 2017 Fang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 December 2016
                : 14 July 2017
                Page count
                Figures: 8, Tables: 2, Pages: 17
                Funding
                Funded by: Chang Gung Memorial Hospital, Linkou (TW)
                Award ID: CMRPD2B0092-93
                Award Recipient :
                Funded by: Chang Gung Memorial Hospital, Linkou (TW)
                Award ID: CMPRG3B0741-742
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
                Award ID: 104-2221-E-006-271-MY2
                Award Recipient :
                This work was financially supported by research grants CMRPD2B0092-93 and CMPRG3B0741-742 from the Chang Gung Memorial Hospital, Linkou, Taiwan and by research grant 104-2221-E-006-271-MY2 from Ministry of Science and Technology, Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Website of Chang Gung Memorial Hospital is https://www.cgmh.org.tw/. Website of Ministry of Science and Technology, Taiwan is https://www.most.gov.tw/.
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