Abstract
Purpose
18F-labeled myocardial flow agents are becoming available for clinical application but the ∼2 hour half-life of 18F complicates their clinical application for rest-stress measurements. The goal of this work is to evaluate in a pig model a single-scan method which provides quantitative rest-stress blood flow in less than 15 minutes.
Methods
Single-scan rest-stress measurements were made using 18F-Flurpiridaz. Nine scans were performed in healthy pigs and seven scans were performed in injured pigs. A two-injection, single-scan protocol was used in which an adenosine infusion was started 4 minutes after the first injection of 18F-Flurpiridaz and followed either 3 or 6 minutes later by a second radiotracer injection. In two pigs, microsphere flow measurements were made at rest and during stress. Dynamic images were reoriented into the short axis view, and regions of interest (ROIs) for the 17 myocardial segments were defined in bull’s eye fashion. PET data were fitted with MGH2, a kinetic model with time varying kinetic parameters, in which blood flow changes abruptly with the introduction of adenosine. Rest and stress myocardial blood flow (MBF) were estimated simultaneously.
Results
The first 12–14 minutes of rest-stress PET data were fitted in detail by the MGH2 model, yielding MBF measurement with a mean precision of 0.035 ml/min/cc. Mean myocardial blood flow across pigs was 0.61 ± 0.11 mL/min/cc at rest and 1.06 ± 0.19 mL/min/cc at stress in healthy pigs and 0.36 ± 0.20 mL/min/cc at rest and 0.62 ± 0.24 mL/min/cc at stress in the ischemic area. Good agreement was obtained with microsphere flow measurement (slope = 1.061 ± 0.017, intercept = 0.051 ± 0.017, mean difference 0.096 ± 0.18 ml/min/cc).
Conclusion
Accurate rest and stress blood flow estimation can be obtained in less than 15 min of PET acquisition. The method is practical and easy to implement suggesting the possibility of clinical translation.
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Acknowledgements
This work was supported by the following grant: R01HL110241. The authors thank Kevin Cordaro, Victoria Douglas and Julia Scotton for animal preparation, handling and monitoring and Dr. Moses Wilks and Dr. Eline Verwer for their help during experimental measurements. The authors are also very grateful to Dr Moussa Mansour for letting them use his facility for the pig preparation and surgery.
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This study was funded by R01HL110241.
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Nicolas J. Guehl declares that he has no conflict of interest. Marc D. Normandin declares that he has no conflict of interest. Dustin W. Wooten declares that he has no conflict of interest. Guy Rozen declares that he has no conflict of interest. Arkadiusk Sitek declares that he has no conflict of interest. Jeremy Ruskin declares that he has no conflict of interest. Timothy M. Shoup declares that he has no conflict of interest. Leon M. Ptaszek declares that he has no conflict of interest. Georges El Fakhri declares that he has no conflict of interest. Nathaniel M. Alpert declares that he has no conflict of interest.
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This article does not contain any studies with human participants performed by any of the authors.
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
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Nicolas J. Guehl and Marc D. Normandin contributed equally to this work.
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Supplemental Fig. 1
Arterial whole blood sample measurements (ART WB) and PET measurements in the LV chamber. (JPG 176 kb)
Supplemental Fig. 2
Relative error on the estimation of K 1 plotted against K 1 estimates for the 17 segments and all studies. The bold line corresponds to the fit of σ(K 1 )/K 1 = a /K1, where a was estimated to be 0.035. (JPG 3469 kb)
Supplemental Fig. 3
Standard perfusion images generated from the kinetic parameters. The top row shows the perfusion images at rest and the bottom row during stress. Left to right columns are short axis, horizontal axis and vertical axis views, respectively. (JPG 9255 kb)
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Guehl, N.J., Normandin, M.D., Wooten, D.W. et al. Single-scan rest/stress imaging: validation in a porcine model with 18F-Flurpiridaz. Eur J Nucl Med Mol Imaging 44, 1538–1546 (2017). https://doi.org/10.1007/s00259-017-3684-6
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DOI: https://doi.org/10.1007/s00259-017-3684-6