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Characterizing the normal range of myocardial blood flow with 82rubidium and 13N-ammonia PET imaging
Authors:Jennifer M. Renaud MSc  Jean N. DaSilva PhD  Rob S. B. Beanlands MD  Robert A. deKemp PhD
Affiliation:1. Department of Physics, University of Ottawa-Carleton University Institute of Physics, Ottawa, ON, Canada
2. Division of Cardiology, Molecular Function & Imaging Program, National Cardiac PET Centre, University of Ottawa Heart Institute, Ottawa, ON, Canada
Abstract:

Background

Diagnosis of coronary disease and microvascular dysfunction may be improved by comparing myocardial perfusion scans with a database defining the lower limit of normal myocardial blood flow and flow reserve (MFR). To maximize disease detection sensitivity, a small normal range is desirable. Both 13N-ammonia and 82Rb tracers are used to quantify blood flow and MFR using positron emission tomography (PET). The goal of this study was to investigate the trade-off between noise and accuracy in both 82Rb and 13N-ammonia normal databases formed using a net retention model.

Methods

Fourteen subjects with <5% risk of CAD underwent rest and stress 82Rb and 13N-ammonia dynamic PET imaging in a randomized order within 2 weeks. Myocardial blood flow was quantified using a one-compartment model for 82Rb, and a two-compartment model for 13N-ammonia. A simplified model was used to estimate tracer retention, with tracer-specific net extraction functions derived to obtain flow estimates.

Results

Normal variability of retention reserve was equivalent for both tracers (±15% globally, ±16% regionally) and was lower in comparison to compartment model results (P < .05). The two-compartment model for 13N-ammonia had the smallest normal range of global blood flow resulting in a lower limit of normal MFR = 2.2 (mean ? 2 SD).

Conclusion

These results suggest that the retention model may have higher sensitivity for detection and localization of abnormal flow and MFR using 82Rb and 13N-ammonia, whereas the 13N-ammonia two-compartment model has higher precision for absolute flow quantification.
Keywords:
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