Extended graphical model for analysis of dynamic contrast-enhanced MRI

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Model discovery approach enables non-invasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition

The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an 125Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter Ktrans alone or Ktrans in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σTUV) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of 125Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the Ktrans MRI parameter as a covariate on the PBPK parameters QTU and σTUV decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.

Vessel wall characterization using quantitative MRI: what's in a number?

The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

Dynamic Contrast-Enhanced MRI to Study Atherosclerotic Plaque Microvasculature

Rupture of a vulnerable atherosclerotic plaque of the carotid artery is an important underlying cause of clinical ischemic events, such as stroke. Abundant microvasculature has been identified as an important aspect contributing to plaque vulnerability. Plaque microvasculature can be studied non-invasively with dynamic contrast-enhanced (DCE-)MRI in animals and patients. In recent years, several DCE-MRI studies have been published evaluating the association between microvasculature and other key features of plaque vulnerability (e.g., inflammation and intraplaque hemorrhage), as well as the effects of novel therapeutic interventions. The present paper reviews this literature, focusing on DCE-MRI methods of acquisition and analysis of atherosclerotic plaques, the current state and future potential of DCE-MRI in the evaluation of plaque microvasculature in clinical and preclinical settings.

Analysis of Multicontrast Carotid Plaque MR Imaging

Plaque imaging by MR imaging provides a wealth of information on the characteristics of individual plaque that may reveal vulnerability to rupture, likelihood of progression, or optimal treatment strategy. T1-weighted and T2-weighted images among other options reveal plaque morphology and composition. Dynamic contrast-enhanced-MR imaging reveals plaque activity. To extract this information, image processing tools are needed. Numerous approaches for analyzing such images have been developed, validated against histologic gold standards, and used in clinical studies. These efforts are summarized in this article.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Fitting the two-compartment model in DCE-MRI by linear inversion

PURPOSE

Model fitting of dynamic contrast-enhanced-magnetic resonance imaging-MRI data with nonlinear least squares (NLLS) methods is slow and may be biased by the choice of initial values. The aim of this study was to develop and evaluate a linear least squares (LLS) method to fit the two-compartment exchange and -filtration models.

METHODS

A second-order linear differential equation for the measured concentrations was derived where model parameters act as coefficients. Simulations of normal and pathological data were performed to determine calculation time, accuracy and precision under different noise levels and temporal resolutions. Performance of the LLS was evaluated by comparison against the NLLS.

RESULTS

The LLS method is about 200 times faster, which reduces the calculation times for a 256 × 256 MR slice from 9 min to 3 s. For ideal data with low noise and high temporal resolution the LLS and NLLS were equally accurate and precise. The LLS was more accurate and precise than the NLLS at low temporal resolution, but less accurate at high noise levels.

CONCLUSION

The data show that the LLS leads to a significant reduction in calculation times, and more reliable results at low noise levels. At higher noise levels the LLS becomes exceedingly inaccurate compared to the NLLS, but this may be improved using a suitable weighting strategy. Magn Reson Med 76:998-1006, 2016. © 2015 Wiley Periodicals, Inc.

Dual energy computed tomography quantification of carotid plaques calcification: comparison between monochromatic and polychromatic energies with pathology correlation

PURPOSE

We compared carotid plaque calcification detection sensitivity and apparent cross-sectional area on CT as a function of CT beam energy using conventional CT techniques and virtual mono-energetic CT images generated from dual-energy acquisitions.

METHODS & MATERIALS

Five ex-vivo carotid endarterectomy (CEA) specimens were imaged with dual-energy computed tomography. Virtual monochromatic spectrum (VMS) CT images were reconstructed at energies between 40-140 keV. The same specimens were imaged using conventional polyenergetic spectrum (PS) CT with peak beam energies 80, 100, 120, and 140 kVp. The histological calcium areas on each corresponding CEA specimen were traced manually on digitized images of Toluidine-Blue/Basic-Fuchsin stained plastic sections.

RESULTS

40 keV VMS CT images provided high detection sensitivity (97 %) similar to conventional PS CT images (~96 %). The calcification size measured on CT decreased systematically with increasing CT beam energy; the rate of change was larger for the VMS images than for PS images.

CONCLUSION

From a single dual-energy CT, multiple VMS-CT images can be generated, yielding equivalent detection sensitivity and size correlations as conventional PS-CT in CEA calcification imaging. VMS-CT at 80-100 keV provided the most accurate estimates of calcification size, as compared to histology, but detection sensitivity was reduced for smaller calcifications on these images.

KEY POINTS

• Calcifications depicted at 80-100 keV were most similar to the histology standard. • Conventional polychromatic images demonstrated excellent correlation with plaque size at pathology. • Conventional polychromatic images systematically overestimate plaque size. • Plaque calcifications can be missed on high energy monochromatic images.

Scan-rescan reproducibility of quantitative assessment of inflammatory carotid atherosclerotic plaque using dynamic contrast-enhanced 3T CMR in a multi-center study

BACKGROUND

The aim of this study is to investigate the inter-scan reproducibility of kinetic parameters in atherosclerotic plaque using dynamic contrast-enhanced (DCE) cardiovascular magnetic resonance (CMR) in a multi-center setting at 3T.

METHODS

Carotid arteries of 51 subjects from 15 sites were scanned twice within two weeks on 3T scanners using a previously described DCE-CMR protocol. Imaging data with protocol compliance and sufficient image quality were analyzed to generate kinetic parameters of vessel wall, expressed as transfer constant (K trans ) and plasma volume (v p ). The inter-scan reproducibility was evaluated using intra-class correlation coefficient (ICC) and coefficient of variation (CV). Power analysis was carried out to provide sample size estimations for future prospective study.

RESULTS

Ten (19.6%) subjects were found to suffer from protocol violation, and another 6 (11.8%) had poor image quality (n=6) in at least one scan. In the 35 (68.6%) subjects with complete data, the ICCs of K trans and v p were 0.65 and 0.28, respectively. The CVs were 25% and 62%, respectively. The ICC and CV for v p improved to 0.73 and 28% in larger lesions with analyzed area larger than 25 mm2. Power analysis based on the measured CV showed that 50 subjects per arm are sufficient to detect a 20% difference in change of K trans over time between treatment arms with 80% power without consideration of the dropout rate.

CONCLUSION

The result of this study indicates that quantitative measurement from DCE-CMR is feasible to detect changes with a relatively modest sample size in a prospective multi-center study despite the limitations. The relative high dropout rate suggested the critical needs for intensive operator training, optimized imaging protocol, and strict quality control in future studies.

Atherosclerotic plaque inflammation quantification using dynamic contrast-enhanced (DCE) MRI

Inflammation plays an important role in atherosclerosis. Given the increasing interest in using in-vivo imaging methods to study the physiology and treatment effects in atherosclerosis, noninvasive intraplaque inflammation quantitative method is needed. Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) has been proposed and validated to quantitatively characterize atherosclerotic plaque inflammation. Recent studies have optimized the imaging protocol, pharmacokinetic modeling techniques. All of these technical advances further promoted DCE-MRI to clinical investigations in plaque risk assessment and therapeutic response monitor. Although larger clinical studies are still needed, DCE-MRI has been proven to be a promising tool to reveal more about intraplaque inflammation by in vivo quantitative inflammation imaging.

Three-dimensional dynamic contrast enhanced imaging of the carotid artery with direct arterial input function measurement

PURPOSE

Kinetic analysis using dynamic contrast enhanced MRI to assess neovascularization of carotid plaque requires images with high spatial and temporal resolution. This work demonstrates a new three-dimensional (3D) dynamic contrast enhanced imaging sequence, which directly measures the arterial input function with high temporal resolution yet maintains the high spatial resolution required to identify areas of increased adventitial neovascularity.

THEORY AND METHODS

The sequence consists of multiple rapid acquisitions of a saturation prepared dynamic 3D gradient recalled echo (GRE) sequence temporally interleaved with multiple acquisitions of a 2D slice. The saturation recovery time was adjusted to maintain signal linearity with the very different contrast agent concentrations in the 2D slice and 3D volume. The K(trans) maps were obtained from the 3D dynamic contrast measurements while the 2D slice was used to obtain the arterial input function. Calibration and dynamic studies are presented.

RESULTS

For contrast agent concentrations up to 5 mM, a saturation recovery time for the 2D slice of 20 ms resulted in less than a 10% deviation from the desired linear response of signal intensity with contrast agent concentration. The corresponding saturation recovery time of 83 ms for the 3D volume maintained less than a 10% deviation from the linear response up to contrast agent concentrations of 2 mM while a contrast agent concentration of 5 mM had almost a 30% deviation. There was a significant improvement in signal attenuation (9 ± 3% versus 23 ± 5% at 40 cm/s) when flow compensation was added to the slice select gradients. For patient studies, volume transfer and plasma fraction maps were calculated with data from the proposed sequence.

CONCLUSION

This work demonstrated a novel sequence for 3D dynamic contrast enhanced imaging with a simultaneously acquired 2D slice that directly measures the arterial input function with high temporal resolution. Acquisition parameters can be adjusted to accommodate the full range of contrast agent concentration values to be encountered and the kinetic parameters obtained were consistent with expected values.

Suitability of pharmacokinetic models for dynamic contrast-enhanced MRI of abdominal aortic aneurysm vessel wall: a comparison

Purpose

Increased microvascularization of the abdominal aortic aneurysm (AAA) vessel wall has been related to AAA progression and rupture. The aim of this study was to compare the suitability of three pharmacokinetic models to describe AAA vessel wall enhancement using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Materials and Methods

Patients with AAA underwent DCE-MRI at 1.5 Tesla. The volume transfer constant (K^trans), which reflects microvascular flow, permeability and surface area, was calculated by fitting the blood and aneurysm vessel wall gadolinium concentration curves. The relative fit errors, parameter uncertainties and parameter reproducibilities for the Patlak, Tofts and Extended Tofts model were compared to find the most suitable model. Scan-rescan reproducibility was assessed using the interclass correlation coefficient and coefficient of variation (CV). Further, the relationship between K^trans and AAA size was investigated.

Results

DCE-MRI examinations from thirty-nine patients (mean age±SD: 72±6 years; M/F: 35/4) with an mean AAA maximal diameter of 49±6 mm could be included for pharmacokinetic analysis. Relative fit uncertainties for K^trans based on the Patlak model (17%) were significantly lower compared to the Tofts (37%) and Extended Tofts model (42%) (p<0.001). K^trans scan-rescan reproducibility for the Patlak model (ICC = 0.61 and CV = 22%) was comparable with the Tofts (ICC = 0.61, CV = 23%) and Extended Tofts model (ICC = 0.76, CV = 22%). K^trans was positively correlated with maximal AAA diameter (Spearman’s ρ = 0.38, p = 0.02) using the Patlak model.

Conclusion

Using the presented imaging protocol, the Patlak model is most suited to describe DCE-MRI data of the AAA vessel wall with good K^trans scan-rescan reproducibility.

Water exchange-minimizing DCE-MRI protocol to detect changes in tumor vascular parameters: effect of bevacizumab/paclitaxel combination therapy

OBJECTIVE

The purpose of this study was to assess changes in the tumor microvasculature induced by combination antiangiogenic therapy in MCF-7 breast tumor mouse models, using a noninvasive DCE-MRI method that minimizes the effect of water exchange.

MATERIALS AND METHODS

3D quantitative DCE-MRI images were acquired with a heavily T1-weighted saturation recovery gradient echo sequence with a recovery delay of 20 ms. Tumor vascular volume (VV) and vascular permeability-surface area product (PS) were obtained through a linear regression of the albumin-Gd-DTPA-enhanced dynamic image intensity on MCF-7 breast tumor mouse models treated with combination bevacizumab/paclitaxel therapy.

RESULTS

Measured tumor VV values were significantly higher than the values that have been reported previously using quantitative T1 mapping, and are in good agreement with micro-CT (computed tomography) results reported earlier from other tumor models. A trend of decreasing tumor PS was detected in the group of MCF-7 tumor bearing mice treated with the bevacizumab/paclitaxel combination regimen.

CONCLUSION

VV and PS maps obtained by a heavily T1-weighted acquisition protocol revealed the large peripheral blood vessels as well as the permeable areas within the tumor. A 12-day/three-dose combination treatment of bevacizumab and paclitaxel resulted in delayed tumor growth and a trend of decreasing tumor vascular permeability surface area product.

Relationship between particulate matter exposure and atherogenic profile in "Ground Zero" workers as shown by dynamic contrast enhanced MR imaging

In this pilot study, we hypothesize that dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has the potential to evaluate differences in atherosclerosis profiles in patients subjected to high (initial dust cloud) and low (after 13 September 2001) particulate matter (PM) exposure. Exposure to PM may be associated with adverse health effects leading to increased morbidity. Law enforcement workers were exposed to high levels of particulate pollution after working at "Ground Zero" and may exhibit accelerated atherosclerosis. 31 subjects (28 male) with high (n = 19) or low (n = 12) exposure to PM underwent DCE-MRI. Demographics (age, gender, family history, hypertension, diabetes, BMI, and smoking status), biomarkers (lipid profiles, hs-CRP, BP) and ankle-brachial index (ABI) measures (left and right) were obtained from all subjects. Differences between the high and low exposures were compared using independent samples t test. Using linear forward stepwise regression with information criteria model, independent predictors of increased area under curve (AUC) from DCE-MRI were determined using all variables as input. Confidence interval of 95 % was used and variables with p > 0.1 were eliminated. p < 0.05 was considered significant. Subjects with high exposure (HE) had significantly higher DCE-MRI AUC uptake (increased neovascularization) compared to subjects with lower exposure (LE). (AUC: 2.65 ± 0.63 HE vs. 1.88 ± 0.69 LE, p = 0.016). Except for right leg ABI, none of the other parameters were significantly different between the two groups. Regression model indicated that only HE to PM, CRP > 3.0 and total cholesterol were independently associated with increased neovascularization (in decreasing order of importance, all p < 0.026). HE to PM may increase plaque neovascularization, and thereby potentially indicate worsening atherogenic profile of "Ground Zero" workers.

Dynamic contrast-enhanced MR imaging of carotid atherosclerotic plaque: model selection, reproducibility, and validation

PURPOSE

To compare four known pharmacokinetic models for their ability to describe dynamic contrast material-enhanced magnetic resonance (MR) imaging of carotid atherosclerotic plaques, to determine reproducibility, and to validate the results with histologic findings.

MATERIALS AND METHODS

The study was approved by the institutional medical ethics committee. Written informed consent was obtained from all patients. Forty-five patients with 30%-99% carotid stenosis underwent dynamic contrast-enhanced MR imaging. Plaque enhancement was measured at 16 time points at approximately 25-second image intervals by using a gadolinium-based contrast material. Pharmacokinetic parameters (volume transfer constant, K(trans); extracellular extravascular volume fraction, v(e); and blood plasma fraction, v(p)) were determined by fitting a two-compartment model to plaque and blood gadolinium concentration curves. The relative fit errors and parameter uncertainties were determined to find the most suitable model. Sixteen patients underwent imaging twice to determine reproducibility. Carotid endarterectomy specimens from 16 patients who were scheduled for surgery were collected for histologic validation. Parameter uncertainties were compared with the Wilcoxon signed rank test. Reproducibility was assessed by using the coefficient of variation. Correlation with histologic findings was evaluated with the Pearson correlation coefficient.

RESULTS

The mean relative fit uncertainty (±standard error) for K(trans) was 10% ± 1 with the Patlak model, which was significantly lower than that with the Tofts (20% ± 1), extended Tofts (33% ± 3), and extended graphical (29% ± 3) models (P < .001). The relative uncertainty for v(p) was 20% ± 2 with the Patlak model and was significantly higher with the extended Tofts (46% ± 9) and extended graphical (35% ± 5) models (P < .001). The reproducibility (coefficient of variation) for the Patlak model was 16% for K(trans) and 26% for v(p). Significant positive correlations were found between K(trans) and the endothelial microvessel content determined on histologic slices (Pearson ρ = 0.72, P = .005).

CONCLUSION

The Patlak model is most suited for describing carotid plaque enhancement. Correlation with histologic findings validated K(trans) as an indicator of plaque microvasculature, and the reproducibility of K(trans) was good.

Progression of experimental lesions of atherosclerosis: assessment by kinetic modeling of black-blood dynamic contrast-enhanced MRI

Pharmacokinetic modeling of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) is used to noninvasively characterize neovasculature and inflammation in atherosclerotic vessels by estimating perfusion characteristics, such as fractional plasma volume vp and transfer constant Ktrans. DCE-MRI has potential to study the evolution of nascent lesions involving early pathological changes. However, currently used bright-blood DCE-MRI approaches are difficult to apply to small lesions because of the difficulty in separating the signal in the thin vessel wall from the adjacent lumen. By suppressing the lumen signal, black-blood DCE-MRI techniques potentially provide a better tool for early atherosclerotic lesion assessment. However, whether black-blood DCE-MRI can detect temporal changes in physiological kinetic parameters has not been investigated for atherosclerosis. This study of balloon-injured New Zealand White rabbits used a reference-region-based pharmacokinetic model of black-blood DCE-MRI to evaluate temporal changes in early experimental atherosclerotic lesions of the abdominal aorta. Six rabbits were imaged at 3 and 6 months after injury. Ktrans was found to increase from 0.10±0.03 min(-1) to 0.14±0.05 min(-1) (P=0.01). In histological analysis of all twelve rabbits, Ktrans showed a significant correlation with macrophage content (R=0.70, P=0.01). These results suggest black-blood DCE-MRI and a reference-region kinetic model could be used to study plaque development and therapeutic response in vivo.

Voxel-wise quantification of myocardial perfusion by cardiac magnetic resonance. Feasibility and methods comparison

The purpose of this study is to enable high spatial resolution voxel-wise quantitative analysis of myocardial perfusion in dynamic contrast-enhanced cardiovascular MR, in particular by finding the most favorable quantification algorithm in this context. Four deconvolution algorithms--Fermi function modeling, deconvolution using B-spline basis, deconvolution using exponential basis, and autoregressive moving average modeling--were tested to calculate voxel-wise perfusion estimates. The algorithms were developed on synthetic data and validated against a true gold-standard using a hardware perfusion phantom. The accuracy of each method was assessed for different levels of spatial averaging and perfusion rate. Finally, voxel-wise analysis was used to generate high resolution perfusion maps on real data acquired from five patients with suspected coronary artery disease and two healthy volunteers. On both synthetic and perfusion phantom data, the B-spline method had the highest error in estimation of myocardial blood flow. The autoregressive moving average modeling and exponential methods gave accurate estimates of myocardial blood flow. The Fermi model was the most robust method to noise. Both simulations and maps in the patients and hardware phantom showed that voxel-wise quantification of myocardium perfusion is feasible and can be used to detect abnormal regions.