Jonathan Moody

Comparison and Prognostic Validation of Multiple Methods of Quantification of Myocardial Blood Flow with 82Rb PET

The quantification of myocardial blood flow (MBF) and myocardial flow reserve (MFR) using PET with 82Rb in patients with known or suspected coronary artery disease has been demonstrated to have substantial prognostic and diagnostic value. However, multiple methods for estimation of an image-derived input function and several models for the nonlinear first-pass extraction of 82Rb by myocardium have been used. We sought to compare the differences in these methods and models and their impact on prognostic assessment in a large clinical dataset. Methods: Consecutive patients (n = 2,783) underwent clinically indicated rest–stress myocardial perfusion PET with 82Rb. The input function was derived using a region of interest (ROI) semiautomatically placed in the region of the mitral valve, factor analysis, and a hybrid method that creates an ROI from factor analysis. We used 5 commonly used extraction models for 82Rb to estimate MBF and MFR. Pearson correlations, bias, and Cohen κ were computed for the various measures. The relationship between MFR/stress MBF and annual rate of cardiac mortality was estimated with spline fits using Poisson regression. Finally, incremental value was assessed with the net reclassification improvement using Cox proportional hazards regression. Results: Correlations between MFR or stress MBF measures made with the same input function derivation method were generally high, regardless of extraction model used (Pearson r > 0.90). However, correlations between measures derived with the ROI method and other methods were only moderate (Pearson r = 0.42–0.62). Importantly, substantial biases were seen for most combinations. We saw that the relationship between cardiac mortality and stress MBF was variable depending on the input function method and extraction model, whereas the relationship between MFR and risk was highly consistent. Net reclassification improvement was comparable for most methods and models for MFR but was highly variable for stress MBF. Conclusion: Although both stress MBF and MFR can improve prognostic assessment, MFR is substantially more consistent, regardless of choice of input function derivation method and extraction model used.

Precision and accuracy of clinical quantification of myocardial blood flow by dynamic PET: A technical perspective.

A number of exciting advances in PET/CT technology and improvements in methodology have recently converged to enhance the feasibility of routine clinical quantification of myocardial blood flow and flow reserve. Recent promising clinical results are pointing toward an important role for myocardial blood flow in the care of patients. Absolute blood flow quantification can be a powerful clinical tool, but its utility will depend on maintaining precision and accuracy in the face of numerous potential sources of methodological errors. Here we review recent data and highlight the impact of PET instrumentation, image reconstruction, and quantification methods, and we emphasize 82Rb cardiac PET which currently has the widest clinical application. It will be apparent that more data are needed, particularly in relation to newer PET technologies, as well as clinical standardization of PET protocols and methods. We provide recommendations for the methodological factors considered here. At present, myocardial flow reserve appears to be remarkably robust to various methodological errors; however, with greater attention to and more detailed understanding of these sources of error, the clinical benefits of stress-only blood flow measurement may eventually be more fully realized.

Characterization of 3D PET systems for accurate quantification of myocardial blood flow

Three-dimensional (3D) mode imaging is the current standard for PET/CT systems. Dynamic imaging for quantification of myocardial blood flow with short-lived tracers, such as 82Rb-chloride, requires accuracy to be maintained over a wide range of isotope activities and scanner counting rates. We proposed new performance standard measurements to characterize the dynamic range of PET systems for accurate quantitative imaging. Methods: 82Rb or 13N-ammonia (1,100–3,000 MBq) was injected into the heart wall insert of an anthropomorphic torso phantom. A decaying isotope scan was obtained over 5 half-lives on 9 different 3D PET/CT systems and 1 3D/2-dimensional PET-only system. Dynamic images (28 × 15 s) were reconstructed using iterative algorithms with all corrections enabled. Dynamic range was defined as the maximum activity in the myocardial wall with less than 10% bias, from which corresponding dead-time, counting rates, and/or injected activity limits were established for each scanner. Scatter correction residual bias was estimated as the maximum cavity blood–to–myocardium activity ratio. Image quality was assessed via the coefficient of variation measuring nonuniformity of the left ventricular myocardium activity distribution. Results: Maximum recommended injected activity/body weight, peak dead-time correction factor, counting rates, and residual scatter bias for accurate cardiac myocardial blood flow imaging were 3–14 MBq/kg, 1.5–4.0, 22–64 Mcps singles and 4–14 Mcps prompt coincidence counting rates, and 2%–10% on the investigated scanners. Nonuniformity of the myocardial activity distribution varied from 3% to 16%. Conclusion: Accurate dynamic imaging is possible on the 10 3D PET systems if the maximum injected MBq/kg values are respected to limit peak dead-time losses during the bolus first-pass transit.

Variance Estimation for Myocardial Blood Flow by Dynamic PET

The estimation of myocardial blood flow (MBF) by 13N-ammonia or 82Rb dynamic PET typically relies on an empirically determined generalized Renkin-Crone equation to relate the kinetic parameter K1 to MBF. Because the Renkin-Crone equation defines MBF as an implicit function of K1, the MBF variance cannot be determined using standard error propagation techniques. To overcome this limitation, we derived novel analytical approximations that provide first- and second-order estimates of MBF variance in terms of the mean and variance of K1 and the Renkin-Crone parameters. The accuracy of the analytical expressions was validated by comparison with Monte Carlo simulations, and MBF variance was evaluated in clinical 82Rb dynamic PET scans. For both 82Rb and 13N-ammonia, good agreement was observed between both (first- and second-order) analytical variance expressions and Monte Carlo simulations, with moderately better agreement for second-order estimates. The contribution of the Renkin-Crone relation to overall MBF uncertainty was found to be as high as 68% for 82Rb and 35% for 13N-ammonia. For clinical 82Rb PET data, the conventional practice of neglecting the statistical uncertainty in the Renkin-Crone parameters resulted in underestimation of the coefficient of variation of global MBF and coronary flow reserve by 14-49%. Knowledge of MBF variance is essential for assessing the precision and reliability of MBF estimates. The form and statistical uncertainty in the empirical Renkin-Crone relation can make substantial contributions to the variance of MBF. The novel analytical variance expressions derived in this work enable direct estimation of MBF variance which includes this previously neglected contribution.

Reply: Variation in Maximum Counting Rates During Myocardial Blood Flow Quantification Using 82Rb PET

909–4,431 kcps (Figs. 1 and 2). In 66 patients (92%), we found a maximum counting rate that was higher than 2,001 kcps, the value that we derived from our phantom study. This implies that the suggested translation to 4.6 MBq/kg may result in counting rates exceeding the 10% activity bias criteria (1) in 92% of the patients, possibly leading to biased MBF measurements. Nevertheless, our results support the use of a weight-based activity, because this resulted in simulated maximum counting rates that were independent of body weight. Applying a lower maximum injected weight–based activity than the one suggested by Renaud et al. (1) can account for the large variation in maximum counting rates encountered in patients and may prevent biased MBF measurements. To ensure accurate MBF quantification with 82Rb PET across all patients, we therefore suggest the inclusion of a correction in the translation of phantom results to the maximum weight–based activity in patients.

Resolution and noise properties of 123 I MIBG SPECT with collimator-detector response modeling

The effects of collimator-detector response (CDR) were studied for two clinical SPECT systems, the Siemens Symbia and GE Infinia, in terms of image resolution, noise properties, and activity estimation of 123I-MIBG in the heart. For each camera, Monte Carlo simulations were used to create CDR models, which were incorporated into a rotation-based projector for 3D-OS-EM SPECT reconstruction. The CDR models were used to generate simulated projections to study the degrading effects of the various CDR components, as well as the efficacy of compensating these components. In simulated images contaminated by 123I septal penetration and detector scatter, compensating the geometric response alone qualitatively restored image contrast, however, activity in the heart was significantly underestimated. The CDR models and the effect of CDR compensation were highly system-dependent. The contribution of detector scatter to activity underestimation was 8–10% for the Symbia and 18–20% for the Infinia, while the contribution of septal penetration was 30% for the Symbia and 5% for the Infinia. The simulation results were confirmed in SPECT measurements of a physical torso phantom on a Symbia SPECT/CT system. These results demonstrate that accurate activity estimation of cardiac 123IMIBG SPECT may require CDR compensation of septal penetration and detector scatter.