Myocardial perfusion imaging: Lessons learned and work to be done-update

Cardiolog

Predictors of 1-year compliance with adaptive servoventilation in patients with heart failure and sleep disordered breathing: preliminary data from the ADVENT-HF trial

Despite its effectiveness in suppressing sleep disordered breathing (SDB), positive airway pressure therapy (PAP) is not always well tolerated by patients and long-term adherence can be problematic. Recently, two multicentre, randomised clinical trials (RCTs) tested the effects of PAP for patients with cardiovascular disease and co-existing SDB on morbidity and mortality with negative outcomes [1, 2]. Relatively poor adherence to PAP therapy (mean 3.7 and 3.3 h·day-1, respectively) in these two trials might have contributed to their poor results. Indeed, higher PAP use per day is associated with better clinical outcomes than lower use [3]

Model-based factor analysis of dynamic sequences of cardiac positron emission tomography

Abstract - Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique physiology. In this work we present a novel method that combines physiological models of factor relationships into the decomposition process. A one-compartment model describes the exchange between blood and myocardium. Two models are compared for describing the relationship between right and left blood chambers of the heart and are validated using simulation data and serial 82Rb imaging with variable infusion durations. Superior results are achieved in the simulation data using the gamma-variate (GV) model compared to the shifted-gamma-variate model (SGV). However, no significant differences in reproducibility of structures were observed in the 82Rb images. Model-based factor analysis using the GV model and the one-compartment model is a promising approach for decomposition of Rb dynamic PET images

A minimal factor overlap method for resolving ambiguity in factor analysis of dynamic cardiac PET

Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique physiology. Each tissue is represented by a time-activity profile (factor) and an associated spatial distribution (structure). Decomposition is based on non-negative constraints of both the factors and structures; however, additional constraints are required to achieve a unique solution. In this work we present a novel method (minimal factor overlap - MFO) and compare its performance to a previously publishe

Kinetic model-based factor analysis of dynamic sequences for 82-rubidium cardiac positron emission tomography

Purpose: Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique temporal signatures to improve quantification of physiological function. In this work, the authors present a novel kinetic model-based (MB) method that includes physiological models of factor relationships within the decomposition process. The physiological accuracy of MB decomposed 82Rb cardiac PET images is evaluated using simulated and experimental data. Precision of myocardial blood flow (MBF) measurement is also evaluated. Methods: A gamma-variate model was used to describe the transport of 82Rb in arterial blood from the right to left ventricle, and a one-compartment model to describe the exchange between blood and myocardium. Simulations of canine and rat heart imaging were performed to evaluate parameter estimation errors. Arterial blood sampling in rats and 11CO blood pool imaging in dogs were used to evaluate factor and structure accuracy. Variable infusion duration studies in canine were used to evaluate MB structure and global MBF reproducibility. All results were compared to a previously published minimal structure overlap (MSO) method. Results: Canine heart simulations demonstrated that MB has lower root-mean-square error (RMSE) than MSO for both factor (0.2% vs 0.5%, p<0.001 MB vs MSO, respectively) and structure (3.0% vs 4.7%, p<0.001) estimations, as with rat heart simulations (factors: 0.2% vs 0.9%, p<0.001 and structures: 3.0% vs 6.7%, p<0.001). MB blood factors compared to arterial blood samples in rats had lower RMSE than MSO (1.6% vs 2.2%, p=0.025). There was no difference in the RMSE of blood structures compared to a 11CO blood pool image in dogs (8.5% vs 8.8%, p=0.23). Myocardial structures were more reproducible with MB than with MSO (RMSE=3.9% vs 6.2%, p<0.001), as were blood structures (RMSE=4.9% vs 5.6%, p=0.006). Finally, MBF values tended to be more reproducible with MB compared to MSO (CV=10% vs 18%, p=0.16). The execution time of MB was, on average, 2.4 times shorter than MSO (p<0.001) due to fewer free parameters. Conclusions: Kinetic model-based factor analysis can be used to provide physiologically accurate decomposition of 82Rb dynamic PET images, and may improve the precision of MBF quantification

Intra-and inter-operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-82 pet and a highly automated analysis program

Background: Changes in myocardial blood flow between rest and stress states are commonly used to diagnose coronary artery disease. Relative myocardial perfusion imaging (MPI) is used routinely while myocardial blood flow quantification (MBF) may improve the sensitivity for detection of early disease. The ratio of flow at stress and rest (S/R) and their difference (S-R) have both been proposed as a means to detect regions with reduced myocardial flow reserve (MFR). In this study, we describe a highly automated method to calculate regional and global rest, stress, S/R, and S-R polar maps of the left ventricle myocardium. Methods: We measured the inter-and intra-operator variability using two randomized datasets (n = 30 each) for each of two operators (novice and expert) with correlation and Bland-Altman reproducibility coefficient (RPC%) analyses. Results: S-R MBF had less inter-operator dependent variability than S/R (RPC% = 5.0% vs 12.6%, P <.001). While there was no difference in intra-operator variability with S-R MBF (novice vs expert RPC% = 6.4% vs 5.9%, P = ns), variability was higher in the noviceoperator for S/R (RPC% = 16.8% vs 8.5% respectively, P <.001), suggesting that S-R may be preferred for detecting small changes in MFR. The novice operator's intervention pattern became more similar to that of the expert in the later dataset, emphasizing the need for adequate training and quality assurance. Conclusion: The proposed method results in low operator-dependent variability, suitable for routine use. Copyrigh

Anatomic versus physiologic assessment of coronary artery disease: Guiding management decisions using positron-emission tomography (PET) as a physiologic tool

Angiographic severity of coronary artery stenosis has historically been the primary guide to revascularization or medical management of coronary artery disease. However, physiologic severity defined by coronary pressure and/or flow has resurged into clinical prominence as a potential, fundamental change from anatomic- to physiologically-guided management. This review addresses clinical coronary physiology - pressure and flow - as clinical tools for treating patients. We clarify the basic concepts that hold true for whatever technology measures coronary physiology directly and reliably, here focusing on positron emission tomography (PET) and its interplay with intracoronary measurements