Sensitivity of quantitative myocardial dynamic contrast-enhanced MRI to saturation pulse efficiency, noise and t1 measurement error: Comparison of nonlinearity correction methods

Role of pulmonary perfusion magnetic resonance imaging for the diagnosis of pulmonary hypertension: A review

Among five types of pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) is the only curable form, but prompt and accurate diagnosis can be challenging. Computed tomography and nuclear medicine-based techniques are standard imaging modalities to non-invasively diagnose CTEPH, however these are limited by radiation exposure, subjective qualitative bias, and lack of cardiac functional assessment. This review aims to assess the methodology, diagnostic accuracy of pulmonary perfusion imaging in the current literature and discuss its advantages, limitations and future research scope.

AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance

Aims

One of the major challenges in the quantification of myocardial blood flow (MBF) from stress perfusion cardiac magnetic resonance (CMR) is the estimation of the arterial input function (AIF). This is due to the non-linear relationship between the concentration of gadolinium and the MR signal, which leads to signal saturation. In this work, we show that a deep learning model can be trained to predict the unsaturated AIF from standard images, using the reference dual-sequence acquisition AIFs (DS-AIFs) for training.

Methods and results

A 1D U-Net was trained, to take the saturated AIF from the standard images as input and predict the unsaturated AIF, using the data from 201 patients from centre 1 and a test set comprised of both an independent cohort of consecutive patients from centre 1 and an external cohort of patients from centre 2 (n = 44). Fully-automated MBF was compared between the DS-AIF and AI-AIF methods using the Mann-Whitney U test and Bland-Altman analysis. There was no statistical difference between the MBF quantified with the DS-AIF [2.77 mL/min/g (1.08)] and predicted with the AI-AIF (2.79 mL/min/g (1.08), P = 0.33. Bland-Altman analysis shows minimal bias between the DS-AIF and AI-AIF methods for quantitative MBF (bias of -0.11 mL/min/g). Additionally, the MBF diagnosis classification of the AI-AIF matched the DS-AIF in 669/704 (95%) of myocardial segments.

Conclusion

Quantification of stress perfusion CMR is feasible with a single-sequence acquisition and a single contrast injection using an AI-based correction of the AIF.

Impact of the Choice of Native T1 in Pixelwise Myocardial Blood Flow Quantification

BACKGROUND

Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium.

PURPOSE

To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values.

STUDY TYPE

Prospective.

SUBJECTS

Fifteen patients with chronic coronary heart disease.

FIELD STRENGTH/SEQUENCE

3T; modified Look-Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid-ventricular short-axis slice in systole and diastole.

ASSESSMENT

MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population-averaged blood and myocardial, subject-specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series.

STATISTICAL TESTS

The relationships between MBF parameters derived by different methods were analyzed by Bland-Altman analysis; corresponding mean values were compared by t-test.

RESULTS

Using subject-specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population-averaged T1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed (P < 0.05). If regional instead of global T1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = -0.03 mL/(min·g), -7% of mean MBF, P < 0.05) but higher in segments without perfusion deficits (bias = 0.01 mL/(min·g), 1% of mean MBF, P < 0.05).

DATA CONCLUSION

Whereas cardiac phase-specific T1 values have a minor impact on MBF estimates, subject-specific and myocardial segment-specific T1 values substantially affect MBF quantification.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 3.

Cardiovascular Determinants of Aerobic Exercise Capacity in Adults With Type 2 Diabetes

OBJECTIVE

To assess the relationship between subclinical cardiac dysfunction and aerobic exercise capacity (peak VO₂) in adults with type 2 diabetes (T2D), a group at high risk of developing heart failure.

RESEARCH DESIGN AND METHODS

Cross-sectional study. We prospectively enrolled a multiethnic cohort of asymptomatic adults with T2D and no history, signs, or symptoms of cardiovascular disease. Age-, sex-, and ethnicity-matched control subjects were recruited for comparison. Participants underwent bioanthropometric profiling, cardiopulmonary exercise testing, and cardiovascular magnetic resonance with adenosine stress perfusion imaging. Multivariable linear regression analysis was undertaken to identify independent associations between measures of cardiovascular structure and function and peak VO₂.

RESULTS

A total of 247 adults with T2D (aged 51.8 ± 11.9 years, 55% males, 37% black or south Asian ethnicity, HbA_1c 7.4 ± 1.1% [57 ± 12 mmol/mol], and duration of diabetes 61 [32-120] months) and 78 control subjects were included. Subjects with T2D had increased concentric left ventricular remodeling, reduced myocardial perfusion reserve (MPR), and markedly lower aerobic exercise capacity (peak VO₂ 18.0 ± 6.6 vs. 27.8 ± 9.0 mL/kg/min; P < 0.001) compared with control subjects. In a multivariable linear regression model containing age, sex, ethnicity, smoking status, and systolic blood pressure, only MPR (β = 0.822; P = 0.006) and left ventricular diastolic filling pressure (E/e') (β = -0.388; P = 0.001) were independently associated with peak VO₂ in subjects with T2D.

CONCLUSIONS

In a multiethnic cohort of asymptomatic people with T2D, MPR and diastolic function are key determinants of aerobic exercise capacity, independent of age, sex, ethnicity, smoking status, or blood pressure.

Hierarchical Bayesian myocardial perfusion quantification

Myocardial blood flow can be quantified from dynamic contrast-enhanced magnetic resonance (MR) images through the fitting of tracer-kinetic models to the observed imaging data. The use of multi-compartment exchange models is desirable as they are physiologically motivated and resolve directly for both blood flow and microvascular function. However, the parameter estimates obtained with such models can be unreliable. This is due to the complexity of the models relative to the observed data which is limited by the low signal-to-noise ratio, the temporal resolution, the length of the acquisitions and other complex imaging artefacts. In this work, a Bayesian inference scheme is proposed which allows the reliable estimation of the parameters of the two-compartment exchange model from myocardial perfusion MR data. The Bayesian scheme allows the incorporation of prior knowledge on the physiological ranges of the model parameters and facilitates the use of the additional information that neighbouring voxels are likely to have similar kinetic parameter values. Hierarchical priors are used to avoid making a priori assumptions on the health of the patients. We provide both a theoretical introduction to Bayesian inference for tracer-kinetic modelling and specific implementation details for this application. This approach is validated in both in silico and in vivo settings. In silico, there was a significant reduction in mean-squared error with the ground-truth parameters using Bayesian inference as compared to using the standard non-linear least squares fitting. When applied to patient data the Bayesian inference scheme returns parameter values that are in-line with those previously reported in the literature, as well as giving parameter maps that match the independant clinical diagnosis of those patients.

Porous medium 3D flow simulation of contrast media washout in cardiac MRI reflects myocardial injury

PURPOSE

Myocardial blood-flow simulation based on laws of fluid mechanics is a valuable tool for understanding tissue behavior. Our aim is to evaluate the ability of a porous-media flow model approach to reflect disturbed washout of contrast media (CM) from the myocardium as observed by cardiovascular MR.

METHODS

A coupled advection-diffusion model is used to describe the CM flow in the vascular and extravascular space as separate compartments. Their exchange of CM is controlled by the exchange rate ExR , which in turn determines the washout behavior. We fitted simulations to CM concentration measurements, derived from T₁ maps of the midventricular slice. The CM concentration was extracted from 18 patients with myocarditis in the acute phase and during follow-up after 6 months. The results were compared with 18 sex- and age-matched controls. For each subject, the measurements were acquired before and during the first 10 minutes at 5 time points after CM administration, representing CM washout. Image registration was applied to compensate for motion between different time points.

RESULTS

Eight matched data sets had to be excluded due to low registration quality. Processing was successful in n = 10 matched data sets of acute and healed myocarditis as well as controls. Significant differences in ExR were observed when comparing patients with acute myocarditis to controls (P < .001), to their follow-up (P < .05), and the follow-up to controls (P < .05).

CONCLUSION

Our study suggests the feasibility of using the proposed porous-medium flow framework for the simulation of pathologic myocardial tissue.

Myocardial perfusion quantification using simultaneously acquired 13 NH3 -ammonia PET and dynamic contrast-enhanced MRI in patients at rest and stress

PURPOSE

Systematic differences with respect to myocardial perfusion quantification exist between DCE-MRI and PET. Using the potential of integrated PET/MRI, this study was conceived to compare perfusion quantification on the basis of simultaneously acquired ¹³ NH₃ -ammonia PET and DCE-MRI data in patients at rest and stress.

METHODS

Twenty-nine patients were examined on a 3T PET/MRI scanner. DCE-MRI was implemented in dual-sequence design and additional T₁ mapping for signal normalization. Four different deconvolution methods including a modified version of the Fermi technique were compared against ¹³ NH₃ -ammonia results.

RESULTS

Cohort-average flow comparison yielded higher resting flows for DCE-MRI than for PET and, therefore, significantly lower DCE-MRI perfusion ratios under the common assumption of equal arterial and tissue hematocrit. Absolute flow values were strongly correlated in both slice-average (R²  = 0.82) and regional (R²  = 0.7) evaluations. Different DCE-MRI deconvolution methods yielded similar flow result with exception of an unconstrained Fermi method exhibiting outliers at high flows when compared with PET.

CONCLUSION

Thresholds for Ischemia classification may not be directly tradable between PET and MRI flow values. Differences in perfusion ratios between PET and DCE-MRI may be lifted by using stress/rest-specific hematocrit conversion. Proper physiological constraints are advised in model-constrained deconvolution.

A comparison of cardiovascular magnetic resonance and single photon emission computed tomography (SPECT) perfusion imaging in left main stem or equivalent coronary artery disease: a CE-MARC substudy

BACKGROUND

Assessment of left main stem (LMS) stenosis has prognostic and therapeutic implications. Data on assessment of LMS disease by cardiovascular magnetic resonance (CMR) and single photon emission computed tomography (SPECT) are limited. CE-MARC is the largest prospective comparison of CMR and SPECT against quantitative invasive coronary angiography (QCA) for detection of coronary artery disease (CAD), and provided the framework for this evaluation. The aims of this study were to compare diagnostic accuracy of visual and quantitative perfusion CMR to SPECT in patients with LMS stable CAD.

METHODS

Fifty-four patients from the CE-MARC study were included: 27 (4%) with significant LMS or LMS-equivalent disease on QCA, and 27 age/sex-matched patients with no flow-limiting CAD. All patients underwent multi-parametric CMR, SPECT and QCA. Performance of visual and quantitative perfusion CMR by Fermi-constrained deconvolution to detect LMS disease was compared with SPECT.

RESULTS

Of 27 patients in the LMS group, 22 (81%) had abnormal CMR and 16 (59%) had abnormal SPECT. All patients with abnormal CMR had abnormal perfusion by visual analysis. CMR demonstrated significantly higher area under the curve (AUC) for detection of disease (0.95; 0.85-0.99) over SPECT (0.63; 0.49-0.76) (p = 0.0001). Global mean stress myocardial blood flow (MBF) by CMR in LMS patients was significantly lower than controls (1.77 ± 0.72 ml/g/min vs. 3.28 ± 1.20 ml/g/min, p < 0.001). MBF of <2.08 ml/g/min had sensitivity of 78% and specificity of 85% for diagnosis of LMS disease, with an AUC (0.87; 0.75-0.94) not significantly different to visual CMR analysis (p = 0.18), and more accurate than SPECT (p = 0.003).

CONCLUSION

Visual stress perfusion CMR had higher diagnostic accuracy than SPECT to detect LMS disease. Quantitative perfusion CMR had similar performance to visual CMR perfusion analysis.

Estimating extraction fraction and blood flow by combining first-pass myocardial perfusion and T1 mapping results

Background

Quantifying myocardial perfusion is complicated by the complexity of pharmacokinetic model being used and the reliability of perfusion parameter estimates. More complex modeling provides more information about the underlying physiology, but too many parameters in complex models introduce a new problem of reliable estimation. To overcome the problem of multiple parameters, we have developed a technique that combines knowledge from two different cardiac magnetic resonance (MR) imaging techniques: dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and T1 mapping. Using extracellular volume (ECV) estimates from T1 mapping may allow more robust model parameter estimates.

Methods

Simulations and human scans were performed. The myocardial perfusion scans used an ungated saturation recovery prepared TurboFLASH pulse sequence. Four short-axis (SA) slices were acquired after a single saturation pulse with a saturation recovery time of ~25 ms before the first slice. Gadoteridol was injected and ~240 frames were acquired over a minute with shallow breathing and no electrocardiograph (ECG) gating. This was followed 20±5 minutes later by an injection of regadenoson to induce hyperemia. The data were acquired using an under-sampled golden angle radial acquisition. Modified look-locker inversion recovery (MOLLI) T1 mapping was performed in 3 slices pre- and post-contrast. The pre- and post-contrast T1 maps were used for ECV estimation. Quantification of perfusion was done using a 4-parameter model with additional information about ECV supplied during model fitting. Phase contrast scans of the coronary sinus (CS) were acquired at rest and immediately after the stress perfusion acquisition to estimate global flow.

Results

Without ECV information, the 5-parameter model fails to converge to a unique solution and often gives incorrect estimates for the perfusion parameters. The myocardial blood flow (MBF) estimates during rest and stress were 0.9±0.1 and 2.3±0.6 mL/min/g, respectively. The extraction fraction estimates were 0.49±0.04 and 0.34±0.05 during rest and stress, respectively.

Conclusions

These results show that it is possible to successfully fit a dynamic perfusion model with an extraction fraction parameter by using information from T1 mapping scans. This hybrid approach is especially important when the 5-parameter model alone fails to converge on a unique solution. This work is a good example of exploiting information overlaps between various cardiac MR imaging techniques.

Analysis of spatiotemporal fidelity in quantitative 3D first-pass perfusion cardiovascular magnetic resonance

BACKGROUND

Whole-heart first-pass perfusion cardiovascular magnetic resonance (CMR) relies on highly accelerated image acquisition. The influence of undersampling on myocardial blood flow (MBF) quantification has not been systematically investigated yet. In the present work, the effect of spatiotemporal scan acceleration on image reconstruction accuracy and MBF error was studied using a numerical phantom and validated in-vivo.

METHODS

Up to 10-fold scan acceleration using k-t PCA and k-t SPARSE-SENSE was simulated using the MRXCAT CMR numerical phantom framework. Image reconstruction results were compared to ground truth data in the k-f domain by means of modulation transfer function (MTF) analysis. In the x-t domain, errors pertaining to specific features of signal intensity-time curves and MBF values derived using Fermi model deconvolution were analysed. In-vivo first-pass CMR data were acquired in ten healthy volunteers using a dual-sequence approach assessing the arterial input function (AIF) and myocardial enhancement. 10x accelerated 3D k-t PCA and k-t SPARSE-SENSE were compared and related to non-accelerated 2D reference images.

RESULTS

MTF analysis revealed good recovery of data upon k-t PCA reconstruction at 10x undersampling with some attenuation of higher temporal frequencies. For 10x k-t SPARSE-SENSE the MTF was found to decrease to zero at high spatial frequencies for all temporal frequencies indicating a loss in spatial resolution. Signal intensity-time curve errors were most prominent in AIFs from 10x k-t PCA, thereby emphasizing the need for separate AIF acquisition using a dual-sequence approach. These findings were confirmed by MBF estimation based on AIFs from fully sampled and undersampled simulations. Average in-vivo MBF estimates were in good agreement between both accelerated and the fully sampled methods. Intra-volunteer MBF variation for fully sampled 2D scans was lower compared to 10x k-t PCA and k-t SPARSE-SENSE data.

CONCLUSION

Quantification of highly undersampled 3D first-pass perfusion CMR yields accurate MBF estimates provided the AIF is obtained using fully sampled or moderately undersampled scans as part of a dual-sequence approach. However, relative to fully sampled 2D perfusion imaging, intra-volunteer variation is increased using 3D approaches prompting for further developments.

Interstudy repeatability of self-gated quantitative myocardial perfusion MRI

PURPOSE

To evaluate the interstudy repeatability of multislice quantitative cardiovascular magnetic resonance myocardial blood flow (MBF), myocardial perfusion reserve (MPR), and extracellular volume (ECV). A unique saturation recovery self-gated acquisition was used for the perfusion scans.

MATERIALS AND METHODS

An ungated golden angle radial turboFLASH pulse sequence was used to scan 10 subjects on two separate days on a 3T scanner. A single saturation pulse was followed by a set of four slices. Rest and hyperemia scans were acquired during free breathing. The images were reconstructed using an iterative algorithm with spatiotemporal constraints. The ungated images were retrospectively binned (self-gated) into near-systole and near-diastole. Deformable registration was performed to adjust for respiratory and residual cardiac motion, and the data were fit with a Fermi model to estimate the interstudy repeatability of quantitative self-gated MBF and MPR.

RESULTS

The coefficient of variation (CoV) of the territorial MPR using the self-gated near-systole data was 18.6%. The self-gated near-diastole data gave less good CoV of MPR, equal to 46.2%. For MBFs, and using smaller (segmental) regions, the CoVs were 20.1% and 22.7% for the estimation of myocardial blood flow at stress and rest, respectively, using the self-gated near-systole data. The self-gated near-diastole data gave CoV = 48.6% and 44.9% for stress and rest.

CONCLUSION

The self-gated free-breathing technique for quantification of myocardial blood flow showed good repeatability for near-systole, with results comparable to published studies on interstudy repeatability of quantitative myocardial perfusion MRI using ECG-gating and breath-holds. Self-gated near-diastole data results were less repeatable. J. Magn. Reson. Imaging 2016;43:1369-1378.

Quantitative three-dimensional myocardial perfusion cardiovascular magnetic resonance with accurate two-dimensional arterial input function assessment

BACKGROUND

Quantification of myocardial perfusion from first-pass cardiovascular magnetic resonance (CMR) images at high contrast agent (CA) dose requires separate acquisition of blood pool and myocardial tissue enhancement. In this study, a dual-sequence approach interleaving 2D imaging of the arterial input function with high-resolution 3D imaging for myocardial perfusion assessment is presented and validated for low and high CA dose.

METHODS

A dual-sequence approach interleaving 2D imaging of the aortic root and 3D imaging of the whole left ventricle using highly accelerated k-t PCA was implemented. Rest perfusion imaging was performed in ten healthy volunteers after administration of a Gadolinium-based CA at low (0.025 mmol/kg b.w.) and high dose (0.1 mmol/kg b.w.). Arterial input functions extracted from the 2D and 3D images were analysed for both doses. Myocardial contrast-to-noise ratios (CNR) were compared across volunteers and doses. Variations of myocardial perfusion estimates between volunteers and across myocardial territories were studied.

RESULTS

High CA dose imaging resulted in strong non-linearity of the arterial input function in the 3D images at peak CA concentration, which was avoided when the input function was derived from the 2D images. Myocardial CNR was significantly increased at high dose compared to low dose, with a 2.6-fold mean CNR gain. Most robust myocardial blood flow estimation was achieved using the arterial input function extracted from the 2D image at high CA dose. In this case, myocardial blood flow estimates varied by 24% between volunteers and by 20% between myocardial territories when analysed on a per-volunteer basis.

CONCLUSION

Interleaving 2D imaging for arterial input function assessment enables robust quantitative 3D myocardial perfusion imaging at high CA dose.

A model-based reconstruction technique for quantitative myocardial perfusion imaging

PURPOSE

To reduce saturation effects in the arterial input function (AIF) estimation of quantitative myocardial first-pass saturation recovery perfusion imaging by employing a model-based reconstruction.

THEORY AND METHODS

Imaging was performed with a saturation recovery prepared radial FLASH sequence. A model-based reconstruction was applied for reconstruction. By exploiting prior knowledge about the relaxation process, an image series with different saturation recovery times was reconstructed. By evaluating images with an effective saturation time of approximately 3 ms, saturation effects in the AIF determination were reduced. In a volunteer study, this approach was compared with a standard prebolus technique.

RESULTS

In comparison to the low-dose injection of a prebolus acquisition, saturation effects were further reduced in the AIFs determined using the model-based approach. These effects, which were clearly visible for all six volunteers, were reflected in a statistically significant difference of up to 20% in the absolute perfusion values.

CONCLUSION

The application of model-based reconstruction algorithms in quantitative myocardial perfusion imaging promises a significant improvement of the AIF determination. In addition to greatly reducing saturation effects that occur even for the prebolus methods, only a single bolus has to be applied. Magn Reson Med 76:880-887, 2016. © 2015 Wiley Periodicals, Inc.