Myocardial Blood Flow Estimates Research Articles

Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks.

Cardiac computed tomography (CT) acquisitions for perfusion assessment can be performed in a dynamic or static mode. Either method may be used for a variety of clinical tasks, including (1)stratifying patients into categories of ischemia and (2)using a quantitative myocardial blood flow (MBF) estimate to evaluate disease severity. In this simulation study, we compare method performance on these classification and quantification tasks for matched radiation dose levels and for different flow states, patient sizes, and injected contrast levels. Under conditions simulated, the dynamic method has low bias in MBF estimates (0 to [Formula: see text]) compared to linearly interpreted static assessment (0.45 to [Formula: see text]), making it more suitable for quantitative estimation. At matched radiation dose levels, receiver operating characteristic analysis demonstrated that the static method, with its high bias but generally lower variance, had superior performance ([Formula: see text]) in stratifying patients, especially for larger patients and lower contrast doses [area under the curve [Formula: see text] to 96 versus 0.86]. We also demonstrate that static assessment with a correctly tuned exponential relationship between the apparent CT number and MBF has superior quantification performance to static assessment with a linear relationship and to dynamic assessment. However, tuning the exponential relationship to the patient and scan characteristics will likely prove challenging. This study demonstrates that the selection and optimization of static or dynamic acquisition modes should depend on the specific clinical task.

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images.

Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3±19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5±28.3mL/min/100g and 78.3±25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.

Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging.

Patient motion is a common problem during dynamic positron emission tomography (PET) scans for quantification of myocardial blood flow (MBF). The purpose of this study was to quantify the prevalence of body motion in a clinical setting and evaluate with realistic phantoms the effects of motion on blood flow quantification, including CT attenuation correction (CTAC) artifacts that result from PET-CT misalignment. A cohort of 236 sequential patients was analyzed for patient motion under resting and peak stress conditions by two independent observers. The presence of motion, affected time-frames, and direction of motion was recorded; discrepancy between observers was resolved by consensus review. Based on these results, patient body motion effects on MBF quantification were characterized using the digital NURBS-based cardiac-torso phantom, with characteristic time activity curves (TACs) assigned to the heart wall (myocardium) and blood regions. Simulated projection data were corrected for attenuation and reconstructed using filtered back-projection. All simulations were performed without noise added, and a single CT image was used for attenuation correction and aligned to the early- or late-frame PET images. In the patient cohort, mild motion of 0.5 ± 0.1 cm occurred in 24% and moderate motion of 1.0 ± 0.3 cm occurred in 38% of patients. Motion in the superior/inferior direction accounted for 45% of all detected motion, with 30% in the superior direction. Anterior/posterior motion was predominant (29%) in the posterior direction. Left/right motion occurred in 24% of cases, with similar proportions in the left and right directions. Computer simulation studies indicated that errors in MBF can approach 500% for scans with severe patient motion (up to 2 cm). The largest errors occurred when the heart wall was shifted left toward the adjacent lung region, resulting in a severe undercorrection for attenuation of the heart wall. Simulations also indicated that the magnitude of MBF errors resulting from motion in the superior/inferior and anterior/posterior directions was similar (up to 250%). Body motion effects were more detrimental for higher resolution PET imaging (2 vs 10 mm full-width at half-maximum), and for motion occurring during the mid-to-late time-frames. Motion correction of the reconstructed dynamic image series resulted in significant reduction in MBF errors, but did not account for the residual PET-CTAC misalignment artifacts. MBF bias was reduced further using global partial-volume correction, and using dynamic alignment of the PET projection data to the CT scan for accurate attenuation correction during image reconstruction. Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts.

Quantitative myocardial perfusion PET parametric imaging at the voxel-level

Quantitative myocardial perfusion (MP) PET has the potential to enhance detection of early stages of atherosclerosis or microvascular dysfunction, characterization of flow-limiting effects of coronary artery disease (CAD), and identification of balanced reduction of flow due to multivessel stenosis. We aim to enable quantitative MP-PET at the individual voxel level, which has the potential to allow enhanced visualization and quantification of myocardial blood flow (MBF) and flow reserve (MFR) as computed from uptake parametric images. This framework is especially challenging for the 82Rb radiotracer. The short half-life enables fast serial imaging and high patient throughput; yet, the acquired dynamic PET images suffer from high noise-levels introducing large variability in uptake parametric images and, therefore, in the estimates of MBF and MFR. Robust estimation requires substantial post-smoothing of noisy data, degrading valuable functional information of physiological and pathological importance. We present a feasible and robust approach to generate parametric images at the voxel-level that substantially reduces noise without significant loss of spatial resolution. The proposed methodology, denoted physiological clustering, makes use of the functional similarity of voxels to penalize deviation of voxel kinetics from physiological partners. The results were validated using extensive simulations (with transmural and non-transmural perfusion defects) and clinical studies. Compared to post-smoothing, physiological clustering depicted enhanced quantitative noise versus bias performance as well as superior recovery of perfusion defects (as quantified by CNR) with minimal increase in bias. Overall, parametric images obtained from the proposed methodology were robust in the presence of high-noise levels as manifested in the voxel time-activity-curves.

136 Quantification of Septal and Whole Slice Myocardial Blood Flow by Myocardial Perfusion CMR is Similar in Healthy Volunteers

Introduction First pass myocardial perfusion CMR allows quantification of myocardial blood flow (MBF). MBF estimation with whole-heart tissue response may be useful in a variety of systemic diseases, but can be limited by suboptimal imaging in one or more segments. The interventricular septum (IVS) offers an attractive target for MBF imaging, as it offers higher signal and less partial volume artefact from blood pool. It has been proposed that T1 measurements taken from the IVS are more reliable than measurements form an entire short axis slice. We hypothesised that MBF estimation from the IVS would be similar to whole-heart estimation. Methods Nine healthy volunteers underwent CMR at 3.0T (Philips Achieva TX, 32 channel receiver coil). First-pass perfusion imaging in three short-axis LV slices was performed during administration of 0.075 mmol/L/kg of gadobutrol at basal, mid-ventricular and apical short-axis slices. This protocol was performed following 3 min of 140 mcg/kg/min adenosine for stress perfusion and repeated 15 min later at rest. MBF estimation was performed using Fermi deconvolution (PMI v.0.4, [Sourbron, 2009]) with basal blood pool providing the arterial input. Tissue response with whole mid-ventricular myocardium and limited IVS contours were compared. Myocardial perfusion reserve (MPR) was calculated by dividing stress MBF by rest MBF. Adequate haemodynamic response was defined as heart rate increase ≥10/min or blood pressure decrease ≤10 mmHg or presence of significant chest discomfort or dyspnoea. Results Mean age was 42 ± 11, 7 males (78%). All patients had adequate haemodynamic response. Whole-heart MBF estimation was 358 ± 137 ml/100 ml/min at stress and 137 ± 48 ml/100 ml/min at rest. Septal MBF was 374 ± 144 ml/100 ml/min at stress and 145 ± 60 at rest. Whole-heart MPR was 2.8 ± 1.02 and septal MPR was 2.81 ± 1.05. There was excellent agreement between whole-heart and septal MBF estimates at stress (r = 0.98; p Conclusion Limited septal quantification of MBF is similar to whole-heart ROI. This technique may simplify MBF estimation for those with suboptimal imaging outside of the septum or low myocardial signal.

Assessment of absolute Tc-99m tetrofosmin retention in the myocardium as an index of myocardial blood flow and coronary flow reserve by gated-SPECT/CT: a feasibility study

Estimation of myocardial blood flow (MBF) and coronary flow reserve (CFR) by SPECT myocardial perfusion imaging (MPI) remains challenging. Our aim was to approximate MBF and CFR by quantifying the absolute Tc-99m tetrofosmin retention in the myocardium via gated-SPECT/CT MPI. Tracer retention was calculated on the basis of the microsphere kinetic model and served as an index of MBF at stress and rest (sMBFi, rMBFi). CFR was given by the sMBFi/rMBFi ratio. A planar first-pass acquisition during dipyridamole stress and at rest provided the data for tracer input determination. The input was represented by the integral of a gamma variate fitted on the time-activity curve of the left ventricle. Gated-SPECT/CT was performed 1 h post tracer injection and myocardial activity was measured in attenuation-corrected transaxial slices by a threshold VOI. The input was also compensated for tissue attenuation by measuring the distance from the centre of the left ventricle to the body surface on fused SPECT/CT slices. Input and uptake results were adjusted for planar-SPECT counting geometry differences by the aid of a phantom experiment. Thirty-nine subjects with low probability of coronary artery disease (CAD), age lower than 75 years and normal MPI (control group) were compared with 57 patients with documented CAD (CAD group). CFR and sMBFi values of CAD patients (1.39 ± 0.37 and 1.42 ± 0.35 ml/min/g) were considerably lower (p < 0.0001) than controls (1.68 ± 0.25 and 1.72 ± 0.37 ml/min/g). Significant difference in CFR (p = 0.03) was also noted between CAD patients with normal MPI (1.48 ± 0.38) and controls. However, sMBFi managed to discriminate certain CAD subgroups (normal MPI/ischemia/scar/scar and ischemia) more efficiently than CFR. Maximum heart rate-blood pressure product (RPP) during stress was an independent predictor of sMBFi and CFR. The other independent CFR correlates were resting RPP and diabetes mellitus, while sMBFi was associated with age, sex, smoking, and stress perfusion defects. Despite the low myocardial extraction fraction of Tc-99m tetrofosmin, an approximation of MBF and CFR is feasible with gated-SPECT/CT MPI. These flow indices together were able to discriminate CAD patients from controls and stratify different patient subgroups.

Variance Estimation for Myocardial Blood Flow by Dynamic PET.

The estimation of myocardial blood flow (MBF) by (13)N-ammonia or (82)Rb 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 (82)Rb dynamic PET scans. For both (82)Rb and (13)N-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 (82)Rb and 35% for (13)N-ammonia. For clinical (82)Rb 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.

Sinogram smoothing techniques for myocardial blood flow estimation from dose-reduced dynamic computed tomography.

Dynamic contrast-enhanced computed tomography (CT) could provide an accurate and widely available technique for myocardial blood flow (MBF) estimation to aid in the diagnosis and treatment of coronary artery disease. However, one of its primary limitations is the radiation dose imparted to the patient. We are exploring techniques to reduce the patient dose by either reducing the tube current or by reducing the number of temporal frames in the dynamic CT sequence. Both of these dose reduction techniques result in noisy data. In order to extract the MBF information from the noisy acquisitions, we have explored several data-domain smoothing techniques. In this work, we investigate two specific smoothing techniques: the sinogram restoration technique in both the spatial and temporal domains and the use of the Karhunen-Loeve (KL) transform to provide temporal smoothing in the sinogram domain. The KL transform smoothing technique has been previously applied to dynamic image sequences in positron emission tomography. We apply a quantitative two-compartment blood flow model to estimate MBF from the time-attenuation curves and determine which smoothing method provides the most accurate MBF estimates in a series of simulations of different dose levels, dynamic contrast-enhanced cardiac CT acquisitions. As measured by root mean square percentage error (% RMSE) in MBF estimates, sinogram smoothing generally provides the best MBF estimates except for the cases of the lowest simulated dose levels (tube current = 25 mAs, 2 or 3 s temporal spacing), where the KL transform method provides the best MBF estimates. The KL transform technique provides improved MBF estimates compared to conventional processing only at very low doses (<7 mSv). Results suggest that the proposed smoothing techniques could provide high fidelity MBF information and allow for substantial radiation dose savings.

Quantitative assessment of magnetic resonance derived myocardial perfusion measurements using advanced techniques: microsphere validation in an explanted pig heart system.

BackgroundCardiovascular Magnetic Resonance (CMR) myocardial perfusion imaging has the potential to evolve into a method allowing full quantification of myocardial blood flow (MBF) in clinical routine. Multiple quantification pathways have been proposed. However at present it remains unclear which algorithm is the most accurate. An isolated perfused, magnetic resonance (MR) compatible pig heart model allows very accurate titration of MBF and in combination with high-resolution assessment of fluorescently-labeled microspheres represents a near optimal platform for validation. We sought to investigate which algorithm is most suited to quantify myocardial perfusion by CMR at 1.5 and 3 Tesla using state of the art CMR perfusion techniques and quantification algorithms.MethodsFirst-pass perfusion CMR was performed in an MR compatible blood perfused pig heart model. We acquired perfusion images at physiological flow (“rest”), reduced flow (“ischaemia”) and during adenosine-induced hyperaemia (“hyperaemia”) as well as during coronary occlusion. Perfusion CMR was performed at 1.5 Tesla (n = 4 animals) and at 3 Tesla (n = 4 animals). Fluorescently-labeled microspheres and externally controlled coronary blood flow served as reference standards for comparison of different quantification strategies, namely Fermi function deconvolution (Fermi), autoregressive moving average modelling (ARMA), exponential basis deconvolution (Exponential) and B-spline basis deconvolution (B-spline).ResultsAll CMR derived MBF estimates significantly correlated with microsphere results. The best correlation was achieved with Fermi function deconvolution both at 1.5 Tesla (r = 0.93, p < 0.001) and at 3 Tesla (r = 0.9, p < 0.001). Fermi correlated significantly better with the microspheres than all other methods at 3 Tesla (p < 0.002). B-spline performed worse than Fermi and Exponential at 1.5 Tesla and showed the weakest correlation to microspheres (r = 0.74, p < 0.001). All other comparisons were not significant. At 3 Tesla exponential deconvolution performed worst (r = 0.49, p < 0.001).ConclusionsCMR derived quantitative blood flow estimates correlate with true myocardial blood flow in a controlled animal model. Amongst the different techniques, Fermi function deconvolution was the most accurate technique at both field strengths. Perfusion CMR based on Fermi function deconvolution may therefore emerge as a useful clinical tool providing accurate quantitative blood flow assessment.

Quantification of Myocardial Blood Flow in Absolute Terms Using 82Rb PET Imaging: The RUBY-10 Study

ObjectivesThe purpose of this study was to compare myocardial blood flow (MBF) and myocardial flow reserve (MFR) estimates from rubidium-82 positron emission tomography (82Rb PET) data using 10 software packages (SPs) based on 8 tracer kinetic models. BackgroundIt is unknown how MBF and MFR values from existing SPs agree for 82Rb PET. MethodsRest and stress 82Rb PET scans of 48 patients with suspected or known coronary artery disease were analyzed in 10 centers. Each center used 1 of 10 SPs to analyze global and regional MBF using the different kinetic models implemented. Values were considered to agree if they simultaneously had an intraclass correlation coefficient >0.75 and a difference <20% of the median across all programs. ResultsThe most common model evaluated was the Ottawa Heart Institute 1-tissue compartment model (OHI-1-TCM). MBF values from 7 of 8 SPs implementing this model agreed best. Values from 2 other models (alternative 1-TCM and Axially distributed) also agreed well, with occasional differences. The MBF results from other models (e.g., 2-TCM and retention) were less in agreement with values from OHI-1-TCM. ConclusionsSPs using the most common kinetic model—OHI-1-TCM—provided consistent results in measuring global and regional MBF values, suggesting that they may be used interchangeably to process data acquired with a common imaging protocol.

Effects of tracer arrival time on the accuracy of high-resolution (voxel-wise) myocardial perfusion maps from contrast-enhanced first-pass perfusion magnetic resonance.

First-pass perfusion cardiac magnetic resonance(CMR) allows the quantitative assessment of myocardial blood flow(MBF). However, flow estimates are sensitive to the delay between the arterial and myocardial tissue tracer arrival time (tOnset) and the accurate estimation of MBF relies on the precise identification of tOnset . The aim of this study is to assess the sensitivity of the quantification process to tOnset at voxel level. Perfusion data were obtained from series of simulated data, a hardware perfusion phantom, and patients. Fermi deconvolution has been used for analysis. A novel algorithm, based on sequential deconvolution,which minimizes the error between myocardial curves and fitted curves obtained after deconvolution, has been used to identify the optimal tOnset for each region. Voxel-wise analysis showed to be more sensitive to tOnset compared to segmental analysis. The automated detection of the tOnset allowed a net improvement of the accuracy of MBF quantification and in patients the identification of perfusion abnormalities in territories that were missed when a constant user-selected tOnset was used. Our results indicate that high-resolution MBF quantification should be performed with optimized tOnset values at voxel level.

Simulation Evaluation of Quantitative Myocardial Perfusion Assessment from Cardiac CT.

Contrast enhancement on cardiac CT provides valuable information about myocardial perfusion and methods have been proposed to assess perfusion with static and dynamic acquisitions. There is a lack of knowledge and consensus on the appropriate approach to ensure 1) sufficient diagnostic accuracy for clinical decisions and 2) low radiation doses for patient safety. This work developed a thorough dynamic CT simulation and several accepted blood flow estimation techniques to evaluate the performance of perfusion assessment across a range of acquisition and estimation scenarios. Cardiac CT acquisitions were simulated for a range of flow states (Flow = 0.5, 1, 2, 3 ml/g/min, cardiac output = 3,5,8 L/min). CT acquisitions were simulated with a validated CT simulator incorporating polyenergetic data acquisition and realistic x-ray flux levels for dynamic acquisitions with a range of scenarios including 1, 2, 3 sec sampling for 30 sec with 25, 70, 140 mAs. Images were generated using conventional image reconstruction with additional image-based beam hardening correction to account for iodine content. Time attenuation curves were extracted for multiple regions around the myocardium and used to estimate flow. In total, 2,700 independent realizations of dynamic sequences were generated and multiple MBF estimation methods were applied to each of these. Evaluation of quantitative kinetic modeling yielded blood flow estimates with an root mean square error (RMSE) of ∼0.6 ml/g/min averaged across multiple scenarios. Semi-quantitative modeling and qualitative static imaging resulted in significantly more error (RMSE = ∼1.2 and ∼1.2 ml/min/g respectively). For quantitative methods, dose reduction through reduced temporal sampling or reduced tube current had comparable impact on the MBF estimate fidelity. On average, half dose acquisitions increased the RMSE of estimates by only 18% suggesting that substantial dose reductions can be employed in the context of quantitative myocardial blood flow estimation. In conclusion, quantitative model-based dynamic cardiac CT perfusion assessment is capable of accurately estimating MBF across a range of cardiac outputs and tissue perfusion states, outperforms comparable static perfusion estimates, and is relatively robust to noise and temporal subsampling.

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g)−1, cardiac output = 3, 5, 8 L min−1). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This suggests that there is no particular advantage between quantitative estimation methods nor to performing dose reduction via tube current reduction compared to temporal sampling reduction. These data are important for optimizing implementation of cardiac dynamic CT in clinical practice and in prospective CT MBF trials.

Impact of errors in determining the start of myocardial enhancement during quantitative first pass perfusion cardiovascular magnetic resonance imaging

Background Several studies have shown the potential of semi-quantitative and fully-quantitative analysis of cardiovascular magnetic resonance (CMR) perfusion images in the diagnosis of coronary artery disease (CAD). However, estimates of myocardial blood flow (MBF) rely on accurate selection of important timing parameters. In this study, we evaluate how the identification of the timing of the Start of Myocardial Enhancement (SME) affects MBF quantification. We hypothesize that incorrectly selecting the SME can adversely affect quantification of the MBF. Methods 20 patients, including 10 with significant CAD (defined as ≥70% stenosis of a major epicardial artery on invasive coronary angiography), underwent regadenoson stress perfusion imaging using a steady-state free precession dual sequence technique followed by rest perfusion imaging. Motion corrected CMR perfusion images were quantified using model constrained deconvolution to obtain MBF estimates (in mL/min/g). Manual selection of SME was used as a reference start time. To evaluate how the timing of SME affects MBF, we systematically and intentionally shifted SME before and after the reference start time (-2, -1.5, -1, -0.5, 0.5, 1, 1.5, 2 second offsets were evaluated). A normal and a stenotic sector were identified from the myocardial signal intensity curves for each study with significant CAD. Results A SME ≥1 second later than the reference SME resulted in a significant overestimation of MBF (p < 0.001), with mean MBF ≥25% than with the reference SME except in the normal sector for rest. The later SME was shifted, the more MBF was overestimated. Delaying SME by 2 seconds led to MBF estimates up to 3 times higher than when the reference SME was used (Figure 1). In both normal (Figure 1) and stenotic sectors, a SME 0.5 second after the reference resulted in significantly higher (p < 0.001) stress and rest MBF values. However, a SME 1.0 second or more before the reference SME didn’t result in significant change of MBF estimates in both stress and rest studies (p = NS for both normal and stenotic sectors). Conclusions

Quantification of septal and whole slice myocardial blood flow by myocardial perfusion CMR is similar in healthy volunteers

Background First pass myocardial perfusion CMR allows quantification of myocardial blood flow (MBF). MBF estimation with whole-heart tissue response may be useful in a variety of systemic diseases, but can be limited by suboptimal imaging in one or more segments. The interventricular septum (IVS) offers an attractive target for MBF imaging, as it offers higher signal and less partial volume artefact from blood pool. It has been proposed that T1 measurements taken from the IVS are more reliable than measurements from an entire short axis slice. We hypothesised that MBF estimation from the IVS would be similar to whole-heart estimation.

Which quantitative perfusion estimation model is better at diagnosing myocardial ischaemia? A CE-MARC sub-study

Methods This was a retrospective sub-study using data from the CE-MARC trial (Greenwood et al., Lancet, 2012). A 50 patient sample of patients were selected such that the distribution of risk factors and disease status within the sample was representative of the full CE-MARC cohort. Quantitative myocardial blood flow (MBF) estimates were obtained from the MRI data using four previously proposed models, commonly used in the quantitative cardiac perfusion literature. These models were: Fermiconstrained deconvolution, model independent deconvolution, the uptake model and the one compartment model. Myocardial Perfusion Reserve (MPR) ratios were calculated from the ratio of stress to rest MBF estimates. The presence of myocardial ischaemia was assessed using the consensus diagnosis of invasive, quantitative X-ray angiography and myocardial Single Photon Computed Tomography (SPECT) imaging. This provided a unique gold-standard combining independent anatomical and functional diagnostic measures. Receiver Operator Characteristic (ROC) curves were generated for each perfusion model using 1) the MPR, and 2) the stress MBF as the diagnostic measure. A DeLong, DeLong, Clarke-Pearson comparison was used to test for statistically significant differences in the Area Under the Curve (AUC) values of the four models.

Interobserver reproducibility of fully quantitative pixel-wise analysis of clinical CMR perfusion imaging

Background Quantitative first pass cardiac magnetic resonance (CMR) perfusion imaging has shown excellent interobserver agreement at a sector level in healthy volunteers and patients. In this study, we compare the myocardial blood flow (MBF) estimates in sector-wise and pixel-wise analysis. We also study the interobserver variability in pixel-wise MBF estimates from patients with coronary artery disease (CAD). Methods

Absolute myocardial flow quantification with 82Rb PET/CT: comparison of different software packages and methods

In clinical cardiac (82)Rb PET, globally impaired coronary flow reserve (CFR) is a relevant marker for predicting short-term cardiovascular events. However, there are limited data on the impact of different software and methods for estimation of myocardial blood flow (MBF) and CFR. Our objective was to compare quantitative results obtained from previously validated software tools. We retrospectively analyzed cardiac (82)Rb PET/CT data from 25 subjects (group 1, 62 ± 11 years) with low-to-intermediate probability of coronary artery disease (CAD) and 26 patients (group 2, 57 ± 10 years; P=0.07) with known CAD. Resting and vasodilator-stress MBF and CFR were derived using three software applications: (1) Corridor4DM (4DM) based on factor analysis (FA) and kinetic modeling, (2) 4DM based on region-of-interest (ROI) and kinetic modeling, (3) MunichHeart (MH), which uses a simplified ROI-based retention model approach, and (4) FlowQuant (FQ) based on ROI and compartmental modeling with constant distribution volume. Resting and stress MBF values (in milliliters per minute per gram) derived using the different methods were significantly different: using 4DM-FA, 4DM-ROI, FQ, and MH resting MBF values were 1.47 ± 0.59, 1.16 ± 0.51, 0.91 ± 0.39, and 0.90 ± 0.44, respectively (P<0.001), and stress MBF values were 3.05 ± 1.66, 2.26 ± 1.01, 1.90 ± 0.82, and 1.83 ± 0.81, respectively (P<0.001). However, there were no statistically significant differences among the CFR values (2.15 ± 1.08, 2.05 ± 0.83, 2.23 ± 0.89, and 2.21 ± 0.90, respectively; P=0.17). Regional MBF and CFR according to vascular territories showed similar results. Linear correlation coefficient for global CFR varied between 0.71 (MH vs. 4DM-ROI) and 0.90 (FQ vs. 4DM-ROI). Using a cut-off value of 2.0 for abnormal CFR, the agreement among the software programs ranged between 76 % (MH vs. FQ) and 90 % (FQ vs. 4DM-ROI). Interobserver agreement was in general excellent with all software packages. Quantitative assessment of resting and stress MBF with (82)Rb PET is dependent on the software and methods used, whereas CFR appears to be more comparable. Follow-up and treatment assessment should be done with the same software and method.

Optimized dynamic framing for PET-based myocardial blood flow estimation

An optimal experiment design methodology was developed to select the framing schedule to be used in dynamic positron emission tomography (PET) for estimation of myocardial blood flow using 82Rb. A compartment model and an arterial input function based on measured data were used to calculate a D-optimality criterion for a wide range of candidate framing schedules. To validate the optimality calculation, noisy time-activity curves were simulated, from which parameter values were estimated using an efficient and robust decomposition of the estimation problem. D-optimized schedules improved estimate precision compared to non-optimized schedules, including previously published schedules. To assess robustness, a range of physiologic conditions were simulated. Schedules that were optimal for one condition were nearly-optimal for others. The effect of infusion duration was investigated. Optimality was better for shorter than for longer tracer infusion durations, with the optimal schedule for the shortest infusion duration being nearly optimal for other durations. Together this suggests that a framing schedule optimized for one set of conditions will also work well for others and it is not necessary to use different schedules for different infusion durations or for rest and stress studies. The method for optimizing schedules is general and could be applied in other dynamic PET imaging studies.

091 QUANTITATIVE THREE-DIMENSIONAL CARDIOVASCULAR MAGNETIC RESONANCE MYOCARDIAL PERFUSION IMAGING IN SYSTOLE AND DIASTOLE AT 3.0 T

Introduction Two-dimensional (2D) perfusion-CMR has been shown to have greater diagnostic accuracy than single-photon emission CT but remains limited by a lack of complete myocardial coverage. Three-dimensional (3D) whole-heart myocardial perfusion CMR addresses this limitation and has recently been shown to be clinically feasible. However, the feasibility and potential clinical utility of quantitative 3D perfusion measurements, as already shown with 2D-perfusion-CMR and positron emission tomography, has yet to be evaluated. The purpose of this study was to establish the feasibility of quantitative 3D-perfusion-CMR to detect coronary artery disease (CAD). Additionally, as 3D-perfusion-CMR offers the opportunity to select the phase of acquisition, a secondary objective was to determine differences between systolic and diastolic estimates of myocardial blood flow (MBF). Methods 35 patients underwent 3D-perfusion-CMR (Philips 3T Achieva TX) with data acquired at both end-systole and mid-diastole (figure 1). Systolic and diastolic perfusion images were analysed in separate reporting sessions in random order. Image quality (0=non-diagnostic, 1=poor, 2=adequate and 3=excellent) and the occurrence of artefact related to respiratory-motion, k-t reconstruction or dark-rim artefact (0=none, 1=mild, 2=moderate and 3=severe) were scored. MBF and myocardial perfusion reserve (MPR) were estimated on a per patient and per territory basis by Fermi function deconvolution. CAD was defined as luminal stenosis ≥70% on quantitative coronary angiography. Results 38 coronary territories had significant CAD. MPR had a high diagnostic accuracy for the detection of CAD, in both systole and diastole (area under curve: 0.92 vs 0.94; p=0.41) (figure 2). At rest, systolic and diastolic MBF estimates were similar—in both normal and diseased territories (no CAD: 1.24±0.15 vs 1.25±0.15 ml/g/min, p=0.27; CAD 1.24±0.15 vs 1.26±0.14 ml/g/min, p=0.20). At stress, diastolic MBF estimates were significantly greater than systolic estimates (no CAD: 3.21±0.50 vs 2.75±0.42 ml/g/min, p Conclusions We have shown that quantitative 3D-perfusion-CMR is feasible and can be used to detect CAD with high diagnostic accuracy. Image quality and less artefact, make systole the preferred phase for acquisition in 3D-perfusion-CMR. Finally, there were significant differences in systolic and diastolic MBF estimates and therefore the phase of acquisition should always be stated in future quantitative studies.