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      Myocardial blood flow quantification by Rb-82 cardiac PET/CT: A detailed reproducibility study between two semi-automatic analysis programs

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          Abstract

          Background

          Several analysis software packages for myocardial blood flow (MBF) quantification from cardiac PET studies exist, but they have not been compared using concordance analysis, which can characterize precision and bias separately. Reproducible measurements are needed for quantification to fully develop its clinical potential.

          Methods

          Fifty-one patients underwent dynamic Rb-82 PET at rest and during adenosine stress. Data were processed with PMOD and FlowQuant (Lortie model). MBF and myocardial flow reserve (MFR) polar maps were quantified and analyzed using a 17-segment model. Comparisons used Pearson’s correlation ρ (measuring precision), Bland and Altman limit-of-agreement and Lin’s concordance correlation ρ c = ρ· C b ( C b measuring systematic bias).

          Results

          Lin’s concordance and Pearson’s correlation values were very similar, suggesting no systematic bias between software packages with an excellent precision ρ for MBF (ρ = 0.97, ρ c = 0.96, C b = 0.99) and good precision for MFR (ρ = 0.83, ρ c = 0.76, C b = 0.92). On a per-segment basis, no mean bias was observed on Bland-Altman plots, although PMOD provided slightly higher values than FlowQuant at higher MBF and MFR values ( P < .0001).

          Conclusions

          Concordance between software packages was excellent for MBF and MFR, despite higher values by PMOD at higher MBF values. Both software packages can be used interchangeably for quantification in daily practice of Rb-82 cardiac PET.

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          Most cited references29

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          A concordance correlation coefficient to evaluate reproducibility.

          L Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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            Quantification of myocardial blood flow with 82Rb dynamic PET imaging.

            The PET tracer (82)Rb is commonly used to evaluate regional perfusion defects for the diagnosis of coronary artery disease. There is limited information on the quantification of myocardial blood flow and flow reserve with this tracer. The goal of this study was to investigate the use of a one-compartment model of (82)Rb kinetics for the quantification of myocardial blood flow. Fourteen healthy volunteers underwent rest and dipyridamole stress imaging with both (13)N-ammonia and (82)Rb within a 2-week interval. Myocardial blood flow was estimated from the time-activity curves measured with (13)N-ammonia using a standard two-compartment model. The uptake parameter of the one-compartment model was estimated from the time-activity curves measured with (82)Rb. To describe the relationship between myocardial blood flow and the uptake parameter, a nonlinear extraction function was fitted to the data. This function was then used to convert estimates of the uptake parameter to flow estimates. The extraction function was validated with an independent data set obtained from 13 subjects with documented evidence of coronary artery disease (CAD). The one-compartment model described (82)Rb kinetics very well (median R-square = 0.98). The flow estimates obtained with (82)Rb were well correlated with those obtained with (13)N-ammonia (r = 0.85), and the best-fit line did not differ significantly from the identity line. Data obtained from the subjects with CAD confirmed the validity of the estimated extraction function. It is possible to obtain accurate estimates of myocardial blood flow and flow reserve with a one-compartment model of (82)Rb kinetics and a nonlinear extraction function.
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              Assay Validation Using the Concordance Correlation Coefficient

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                Author and article information

                Contributors
                +41 21 314 4348 , john.prior@chuv.ch
                Journal
                J Nucl Cardiol
                J Nucl Cardiol
                Journal of Nuclear Cardiology
                Springer US (New York )
                1071-3581
                1532-6551
                21 May 2015
                21 May 2015
                2016
                : 23
                : 499-510
                Affiliations
                [ ]Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland
                [ ]University of Ottawa Heart Institute, Cardiac PET Centre, Ottawa, Canada
                Article
                151
                10.1007/s12350-015-0151-2
                4867775
                25995182
                81c2e99d-7024-4827-be83-1c6c1667a320
                © The Author(s) 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 15 November 2014
                : 7 April 2015
                Categories
                Original Article
                Custom metadata
                © American Society of Nuclear Cardiology 2016

                Cardiovascular Medicine
                software,pet,rubidium-82,quantification,myocardial perfusion,concordance,accuracy,precision,agreement,comparison

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