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Bengs S, Warnock GI, Portmann A, Mikail N, Rossi A, Ahmed H, Etter D, Treyer V, Gisler L, Pfister SK, Jie CVML, Meisel A, Keller C, Liang SH, Schibli R, Mu L, Buechel RR, Kaufmann PA, Ametamey SM, Gebhard C, Haider A. Rest/stress myocardial perfusion imaging by positron emission tomography with 18F-Flurpiridaz: A feasibility study in mice. J Nucl Cardiol 2023; 30:62-73. [PMID: 35484467 PMCID: PMC9984310 DOI: 10.1007/s12350-022-02968-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 03/15/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Myocardial perfusion imaging by positron emission tomography (PET-MPI) is the current gold standard for quantification of myocardial blood flow. 18F-flurpiridaz was recently introduced as a valid alternative to currently used PET-MPI probes. Nonetheless, optimum scan duration and time interval for image analysis are currently unknown. Further, it is unclear whether rest/stress PET-MPI with 18F-flurpiridaz is feasible in mice. METHODS Rest/stress PET-MPI was performed with 18F-flurpiridaz (0.6-3.0 MBq) in 27 mice aged 7-8 months. Regadenoson (0.1 µg/g) was used for induction of vasodilator stress. Kinetic modeling was performed using a metabolite-corrected arterial input function. Image-derived myocardial 18F-flurpiridaz uptake was assessed for different time intervals by placing a volume of interest in the left ventricular myocardium. RESULTS Tracer kinetics were best described by a two-tissue compartment model. K1 ranged from 6.7 to 20.0 mL·cm-3·min-1, while myocardial volumes of distribution (VT) were between 34.6 and 83.6 mL·cm-3. Of note, myocardial 18F-flurpiridaz uptake (%ID/g) was significantly correlated with K1 at rest and following pharmacological vasodilation for all time intervals assessed. However, while Spearman's coefficients (rs) ranged between 0.478 and 0.681, R2 values were generally low. In contrast, an excellent correlation of myocardial 18F-flurpiridaz uptake with VT was obtained, particularly when employing the averaged myocardial uptake from 20 to 40 min post tracer injection (R2 ≥ 0.98). Notably, K1 and VT were similarly sensitive to pharmacological vasodilation induction. Further, mean stress-to-rest ratios of K1, VT, and %ID/g 18F-flurpiridaz were virtually identical, suggesting that %ID/g 18F-flurpiridaz can be used to estimate coronary flow reserve (CFR) in mice. CONCLUSION Our findings suggest that a simplified assessment of relative myocardial perfusion and CFR, based on image-derived tracer uptake, is feasible with 18F-flurpiridaz in mice, enabling high-throughput mechanistic CFR studies in rodents.
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Affiliation(s)
- Susan Bengs
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Geoffrey I Warnock
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Angela Portmann
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Nidaa Mikail
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Alexia Rossi
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Hazem Ahmed
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Dominik Etter
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
| | - Livio Gisler
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Stefanie K Pfister
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA
| | - Caitlin V M L Jie
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Alexander Meisel
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Claudia Keller
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Steven H Liang
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA
| | - Roger Schibli
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Linjing Mu
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Ronny R Buechel
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
| | - Philipp A Kaufmann
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
| | - Simon M Ametamey
- Institute of Pharmaceutical Sciences, ETH Zurich, 8093, Zurich, Switzerland
| | - Catherine Gebhard
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland
| | - Ahmed Haider
- Department of Nuclear Medicine, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland.
- Center for Molecular Cardiology, University of Zurich, 8952, Schlieren, Switzerland.
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
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Cuddy-Walsh SG, deKemp RA, Ruddy TD, Wells RG. Improved precision of SPECT myocardial blood flow using a net tracer retention model. Med Phys 2022; 50:2009-2021. [PMID: 36565461 DOI: 10.1002/mp.16186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 11/08/2022] [Accepted: 12/05/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Noninvasive quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR) provides incremental benefit to relative myocardial perfusion imaging (MPI) to diagnose and manage heart disease. MBF can be measured with single-photon emission computed tomography (SPECT) but the uncertainty in the measured values is high. Standardization and optimization of protocols for SPECT MBF measurements will improve the consistency of this technique. One element of the processing protocol is the choice of kinetic model used to analyze the dynamic image series. PURPOSE This study evaluates if a net tracer retention model (RET) will provide a better fit to the acquired data and greater test-retest precision than a one-compartment model (1CM) for SPECT MBF, with (+MC) and without (-MC) manual motion correction. METHODS Data from previously acquired rest-stress MBF studies (31 SPECT-PET and 30 SPECT-SPECT) were reprocessed ± MC. Rate constants (K1) were extracted using 1CM and RET, +/-MC, and compared pairwise with standard PET MBF measurements using cross-validation to obtain calibration parameters for converting SPECT rate constants to MBF and to assess the goodness-of-fit of the calibration curves. Precision (coefficient of variation of test re-test relative differences, COV) of flow measurements was computed for 1CM and RET ± MC using data from the repeated SPECT MBF studies. RESULTS Both the RET model and MC improved the goodness-of-fit of the SPECT MBF calibration curves to PET. All models produced minimal bias compared with PET (mean bias < 0.6%). The SPECT-SPECT MBF COV significantly improved from 34% (1CM+MC) to 28% (RET+MC, P = 0.008). CONCLUSION The RET+MC model provides a better calibration of SPECT to PET and blood flow measurements with better precision than the 1CM, without loss of accuracy.
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Affiliation(s)
- Sarah G Cuddy-Walsh
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada
| | - Robert A deKemp
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.,Division of Cardiology, University of Ottawa, Ottawa, Ontario, Canada
| | - Terrence D Ruddy
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.,Division of Cardiology, University of Ottawa, Ottawa, Ontario, Canada
| | - R Glenn Wells
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.,Division of Cardiology, University of Ottawa, Ottawa, Ontario, Canada
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