Quantitative myocardial perfusion analysis with a dual-bolus contrast-enhanced first-pass MRI technique in humans

Comparison of dual-bolus versus dual-sequence techniques for determining myocardial blood flow and myocardial perfusion reserve by cardiac magnetic resonance stress perfusion: From the Automated Quantitative analysis of myocardial perfusion cardiac Magnetic Resonance Consortium

BACKGROUND

Quantitative stress cardiac magnetic resonance (CMR) can be performed using the dual-sequence (DS) technique or dual-bolus (DB) method. It is unknown if DS and DB produce similar results for myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). The study objective is to investigate if there are any differences between DB- and DS-derived MBF and MPR.

METHODS

Retrospective observational study with 168 patients who underwent stress CMR. DB and DS methods were simultaneously performed on each patient on the same day. Global and segmental stress MBF and rest MBF values were collected.

RESULTS

Using Bland-Altman analysis, segmental and global stress MBF values were higher in DB than DS (0.22 ± 0.60 mL/g/min, p < 0.001 and 0.20 ± 0.48 mL/g/min, p = 0.005, respectively) with strong correlation (r = 0.81, p < 0.001 for segmental and r = 0.82, p < 0.001 for global). In rest MBF, segmental and global DB values were higher than by DS (0.15 ± 0.51 mL/g/min, p < 0.001 and 0.14 ± 0.36 mL/g/min, p = 0.011, respectively) with strong correlation (r = 0.81, p < 0.001 and r = 0.77, p < 0.001). Mean difference between MPR by DB and DS was -0.02 ± 0.68 mL/g/min (p = 0.758) for segmental values and -0.01 ± 0.49 mL/g/min (p = 0.773) for global values. MPR values correlated strongly as well in both segmental and global, both (r = 0.74, p < 0.001) and (r = 0.75, p < 0.001), respectively.

CONCLUSION

There is a very good correlation between DB- and DS-derived MBF and MPR values. However, there are significant differences between DB- and DS-derived global stress and rest MBF. While MPR values did not show statistically significant differences between DB and DS methods.

MRI of cardiac involvement in COVID-19

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to a diverse pattern of myocardial injuries, including myocarditis, which is linked to adverse outcomes in patients. Research indicates that myocardial injury is associated with higher mortality in hospitalized severe COVID-19 patients (75.8% vs 9.7%). Cardiovascular Magnetic Resonance (CMR) has emerged as a crucial tool in diagnosing both ischaemic and non-ischaemic myocardial injuries, providing detailed insights into the impact of COVID-19 on myocardial tissue and function. This review synthesizes existing studies on the histopathological findings and CMR imaging patterns of myocardial injuries in COVID-19 patients. CMR imaging has revealed a complex pattern of cardiac damage in these patients, including myocardial inflammation, oedema, fibrosis, and ischaemic injury, due to coronary microthrombi. This review also highlights the role of LLC criteria in diagnosis of COVID-related myocarditis and the importance of CMR in detecting cardiac complications of COVID-19 in specific groups, such as children, manifesting multisystem inflammatory syndrome in children (MIS-C) and athletes, as well as myocardial injuries post-COVID-19 infection or following COVID-19 vaccination. By summarizing existing studies on CMR in COVID-19 patients and highlighting ongoing research, this review contributes to a deeper understanding of the cardiac impacts of COVID-19. It emphasizes the effectiveness of CMR in assessing a broad spectrum of myocardial injuries, thereby enhancing the management and prognosis of patients with COVID-19 related cardiac complications.

Myocardial Blood Flow by Magnetic Resonance in Patients With Suspected Coronary Stenosis: Comparison to PET and Invasive Physiology

BACKGROUND

Despite recent guideline recommendations, quantitative perfusion (QP) estimates of myocardial blood flow from cardiac magnetic resonance (CMR) have only been sparsely validated. Furthermore, the additional diagnostic value of utilizing QP in addition to the traditional visual expert interpretation of stress-perfusion CMR remains unknown. The aim was to investigate the correlation between myocardial blood flow measurements estimated by CMR, positron emission tomography, and invasive coronary thermodilution. The second aim is to investigate the diagnostic performance of CMR-QP to identify obstructive coronary artery disease (CAD).

METHODS

Prospectively enrolled symptomatic patients with >50% diameter stenosis on computed tomography angiography underwent dual-bolus CMR and positron emission tomography with rest and adenosine-stress myocardial blood flow measurements. Subsequently, an invasive coronary angiography (ICA) with fractional flow reserve and thermodilution-based coronary flow reserve was performed. Obstructive CAD was defined as both anatomically severe (>70% diameter stenosis on quantitative coronary angiography) or hemodynamically obstructive (ICA with fractional flow reserve ≤0.80).

RESULTS

About 359 patients completed all investigations. Myocardial blood flow and reserve measurements correlated weakly between estimates from CMR-QP, positron emission tomography, and ICA-coronary flow reserve (r<0.40 for all comparisons). In the diagnosis of anatomically severe CAD, the interpretation of CMR-QP by an expert reader improved the sensitivity in comparison to visual analysis alone (82% versus 88% [P=0.03]) without compromising specificity (77% versus 74% [P=0.28]). In the diagnosis of hemodynamically obstructive CAD, the accuracy was only moderate for a visual expert read and remained unchanged when additional CMR-QP measurements were interpreted.

CONCLUSIONS

CMR-QP correlates weakly to myocardial blood flow measurements by other modalities but improves diagnosis of anatomically severe CAD.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03481712.

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network

Background: The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. Purpose: When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. Methods: Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. Results: Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). Conclusions: Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.

Clinical implementation of a fully automated quantitative perfusion cardiovascular magnetic resonance imaging workflow with a simplified dual-bolus contrast administration scheme

This study clinically implemented a ready-to-use quantitative perfusion (QP) cardiovascular magnetic resonance (QP CMR) workflow, encompassing a simplified dual-bolus gadolinium-based contrast agent (GBCA) administration scheme and fully automated QP image post-processing. Twenty-five patients with suspected obstructive coronary artery disease (CAD) underwent both adenosine stress perfusion CMR and an invasive coronary angiography or coronary computed tomography angiography. The dual-bolus protocol consisted of a pre-bolus (0.0075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) and a main bolus (0.075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) at an infusion rate of 3 ml/s. The arterial input function curves showed excellent quality. Stress MBF ≤ 1.84 ml/g/min accurately detected obstructive CAD (area under the curve 0.79; 95% Confidence Interval: 0.66 to 0.89). Combined visual assessment of color pixel QP maps and conventional perfusion images yielded a diagnostic accuracy of 84%, sensitivity of 70% and specificity of 93%. The proposed easy-to-use dual-bolus QP CMR workflow provides good image quality and holds promise for high accuracy in diagnosis of obstructive CAD. Implementation of this approach has the potential to serve as an alternative to current methods thus increasing the accessibility to offer high-quality QP CMR imaging by a wide range of CMR laboratories.

Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR

PURPOSE

To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR).

METHODS

First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT.

RESULTS

Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods.

CONCLUSION

PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.

Simultaneous multi-slice steady-state free precession myocardial perfusion with iterative reconstruction and integrated motion compensation

PURPOSE

Simultaneous multi-slice (SMS) balanced steady-state free precession (bSSFP) acquisition and iterative reconstruction can provide high spatial resolution and coverage for cardiac magnetic resonance (CMR) perfusion. However, respiratory motion remains a challenge for iterative reconstruction techniques employing temporal regularisation. The aim of this study is to evaluate an iterative reconstruction with integrated motion compensation for SMS-bSSFP first-pass myocardial stress perfusion in the presence of respiratory motion.

METHODS

Thirty-one patients with suspected coronary artery disease were prospectively recruited and imaged at 1.5 T. A SMS-bSSFP prototype myocardial perfusion sequence was acquired at stress in all patients. All datasets were reconstructed using an iterative reconstruction with temporal regularisation, once with and once without motion compensation (MC and NMC, respectively). Three readers scored each dataset in terms of: image quality (1:poor; 4:excellent), motion/blurring (1:severe motion/blurring; 3:no motion/blurring), and diagnostic confidence (1:poor confidence; 3:high confidence). Quantitative assessment of sharpness was performed. The number of uncorrupted first-pass dynamics was measured on the NMC datasets to classify patients into 'suboptimal breath-hold (BH)' and 'good BH' groups.

RESULTS

Compared across all cases, MC performed better than NMC in terms of image quality (3.5 ± 0.5 vs. 3.0 ± 0.8, P = 0.002), motion/blurring (2.9 ± 0.1 vs. 2.2 ± 0.8, P < 0.001), diagnostic confidence (2.9 ± 0.1 vs. 2.3 ± 0.7, P < 0.001) and sharpness index (0.34 ± 0.05 vs. 0.31 ± 0.06, P < 0.001). Fourteen patients with a suboptimal BH were identified. For the suboptimal BH group, MC performed better than NMC in terms of image quality (3.8 ± 0.4 vs. 2.6 ± 0.8, P < 0.001), motion/blurring (3.0 ± 0.1 vs. 1.6 ± 0.7, P < 0.001), diagnostic confidence (3.0 ± 0.1 vs. 1.9 ± 0.7, P < 0.001) and sharpness index (0.34 ± 0.05 vs. 0.30 ± 0.06, P = 0.004). For the good BH group, sharpness index was higher for MC than NMC (0.34 ± 0.06 vs 0.31 ± 0.07, P = 0.03), while there were no significant differences observed for the other three metrics assessed (P > 0.11). There were no significant differences between suboptimal BH MC and good BH MC for any of the reported metrics (P > 0.06).

CONCLUSIONS

Integrated motion compensation significantly reduces motion/blurring and improves image quality, diagnostic confidence and sharpness index of SMS-bSSFP perfusion with iterative reconstruction in the presence of motion.

Simultaneous multislice steady-state free precession myocardial perfusion with full left ventricular coverage and high resolution at 1.5 T

Purpose

To implement and evaluate a simultaneous multi‐slice balanced SSFP (SMS‐bSSFP) perfusion sequence and compressed sensing reconstruction for cardiac MR perfusion imaging with full left ventricular (LV) coverage (nine slices/heartbeat) and high spatial resolution (1.4 × 1.4 mm²) at 1.5T.

Methods

A preliminary study was performed to evaluate the performance of blipped controlled aliasing in parallel imaging (CAIPI) and RF‐CAIPI with gradient‐controlled local Larmor adjustment (GC‐LOLA) in the presence of fat. A nine‐slice SMS‐bSSFP sequence using RF‐CAIPI with GC‐LOLA with high spatial resolution (1.4 × 1.4 mm²) and a conventional three‐slice sequence with conventional spatial resolution (1.9 × 1.9 mm²) were then acquired in 10 patients under rest conditions. Qualitative assessment was performed to assess image quality and perceived signal‐to‐noise ratio (SNR) on a 4‐point scale (0: poor image quality/low SNR; 3: excellent image quality/high SNR), and the number of myocardial segments with diagnostic image quality was recorded. Quantitative measurements of myocardial sharpness and upslope index were performed.

Results

Fat signal leakage was significantly higher for blipped CAIPI than for RF‐CAIPI with GC‐LOLA (7.9% vs. 1.2%, p = 0.010). All 10 SMS‐bSSFP perfusion datasets resulted in 16/16 diagnostic myocardial segments. There were no significant differences between the SMS and conventional acquisitions in terms of image quality (2.6 ± 0.6 vs. 2.7 ± 0.2, p = 0.8) or perceived SNR (2.8 ± 0.3 vs. 2.7 ± 0.3, p = 0.3). Inter‐reader variability was good for both image quality (ICC = 0.84) and perceived SNR (ICC = 0.70). Myocardial sharpness was improved using the SMS sequence compared to the conventional sequence (0.37 ± 0.08 vs 0.32 ± 0.05, p < 0.001). There was no significant difference between measurements of upslope index for the SMS and conventional sequences (0.11 ± 0.04 vs. 0.11 ± 0.03, p = 0.84).

Conclusion

SMS‐bSSFP with multiband factor 3 and compressed sensing reconstruction enables cardiac MR perfusion imaging with three‐fold increased spatial coverage and improved myocardial sharpness compared to a conventional sequence, without compromising perceived SNR, image quality, upslope index or number of diagnostic segments.

Advances in Myocardial Perfusion MR Imaging: Physiological Implications, the Importance of Quantitative Analysis, and Impact on Patient Care in Coronary Artery Disease

Stress myocardial perfusion imaging (MPI) is the preferred test in patients with intermediate-to-high clinical likelihood of coronary artery disease (CAD) and can be used as a gatekeeper to avoid unnecessary revascularization. Cardiac magnetic resonance (CMR) has a number of favorable characteristics, including: (1) high spatial resolution that can delineate subendocardial ischemia; (2) comprehensive assessment of morphology, global and regional cardiac functions, tissue characterization, and coronary artery stenosis; and (3) no radiation exposure to patients. According to meta-analysis studies, the diagnostic accuracy of perfusion CMR is comparable to positron emission tomography (PET) and perfusion CT, and is better than single-photon emission CT (SPECT) when fractional flow reserve (FFR) is used as a reference standard. In addition, stress CMR has an excellent prognostic value. One meta-analysis study demonstrated the annual event rate of cardiovascular death or non-fatal myocardial infarction was 4.9% and 0.8%, respectively, in patients with positive and negative stress CMR. Quantitative assessment of perfusion CMR not only allows the objective evaluation of regional ischemia but also provides insights into the pathophysiology of microvascular disease and diffuse subclinical atherosclerosis. For accurate quantification of myocardial perfusion, saturation correction of arterial input function is important. There are two major approaches for saturation correction, one is a dual-bolus method and the other is a dual-sequence method. Absolute quantitative mapping with myocardial perfusion CMR has good accuracy in detecting coronary microvascular dysfunction. Flow measurement in the coronary sinus (CS) with phase contrast cine CMR is an alternative approach to quantify global coronary flow reserve (CFR). The measurement of global CFR by quantitative analysis of perfusion CMR or flow measurement in the CS permits assessment of microvascular disease and diffuse subclinical atherosclerosis, which may provide improved prediction of future event risk in patients with suspected or known CAD. Multi-institutional studies to validate the diagnostic and prognostic values of quantitative perfusion CMR approaches are required.

Clinical Application of Dynamic Contrast Enhanced Perfusion Imaging by Cardiovascular Magnetic Resonance

Functionally significant coronary artery disease impairs myocardial blood flow and can be detected non-invasively by myocardial perfusion imaging. While multiple myocardial perfusion imaging modalities exist, the high spatial and temporal resolution of cardiovascular magnetic resonance (CMR), combined with its freedom from ionising radiation make it an attractive option. Dynamic contrast enhanced CMR perfusion imaging has become a well-validated non-invasive tool for the assessment and risk stratification of patients with coronary artery disease and is recommended by international guidelines. This article presents an overview of CMR perfusion imaging and its clinical application, with a focus on chronic coronary syndromes, highlighting its strengths and challenges, and discusses recent advances, including the emerging role of quantitative perfusion analysis.

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

Ischemic Heart Disease: Noninvasive Imaging Techniques and Findings

Ischemic heart disease is a leading cause of death worldwide and comprises a large proportion of annual health care expenditure. Management of ischemic heart disease is now best guided by the physiologic significance of coronary artery stenosis. Invasive coronary angiography is the standard for diagnosing coronary artery stenosis. However, it is expensive and has risks including vascular access site complications and contrast material–induced nephropathy. Invasive coronary angiography requires fractional flow reserve (FFR) measurement to determine the physiologic significance of a coronary artery stenosis. Multiple noninvasive cardiac imaging modalities can also anatomically delineate or functionally assess for significant coronary artery stenosis, as well as detect the presence of myocardial infarction (MI). While coronary CT angiography can help assess the degree of anatomic stenosis, its inability to assess the physiologic significance of lesions limits its specificity. Physiologic significance of coronary artery stenosis can be determined by cardiac MR vasodilator or dobutamine stress imaging, CT stress perfusion imaging, FFR CT, PET myocardial perfusion imaging (MPI), SPECT MPI, and stress echocardiography. Clinically unrecognized MI, another clear indicator of physiologically significant coronary artery disease, is relatively common and is best evaluated with cardiac MRI. The authors illustrate the spectrum of imaging findings of ischemic heart disease (coronary artery disease, myocardial ischemia, and MI); highlight the advantages and disadvantages of the various noninvasive imaging methods used to assess ischemic heart disease, as illustrated by recent clinical trials; and summarize current indications and contraindications for noninvasive imaging techniques for detection of ischemic heart disease.

Online supplemental material is available for this article.

Published under a CC BY 4.0 license.

Direct Comparison of Bayesian and Fermi Deconvolution Approaches for Myocardial Blood Flow Quantification: In silico and Clinical Validations

Cardiac magnetic resonance myocardial perfusion imaging can detect coronary artery disease and is an alternative to single-photon emission computed tomography or positron emission tomography. However, the complex, non-linear MR signal and the lack of robust quantification of myocardial blood flow have hindered its widespread clinical application thus far. Recently, a new Bayesian approach was developed for brain imaging and evaluation of perfusion indexes (Kudo et al., 2014). In addition to providing accurate perfusion measurements, this probabilistic approach appears more robust than previous approaches, particularly due to its insensitivity to bolus arrival delays. We assessed the performance of this approach against a well-known and commonly deployed model-independent method based on the Fermi function for cardiac magnetic resonance myocardial perfusion imaging. The methods were first evaluated for accuracy and precision using a digital phantom to test them against the ground truth; next, they were applied in a group of coronary artery disease patients. The Bayesian method can be considered an appropriate model-independent method with which to estimate myocardial blood flow and delays. The digital phantom comprised a set of synthetic time-concentration curve combinations generated with a 2-compartment exchange model and a realistic combination of perfusion indexes, arterial input dynamics, noise and delays collected from the clinical dataset. The myocardial blood flow values estimated with the two methods showed an excellent correlation coefficient (r² > 0.9) under all noise and delay conditions. The Bayesian approach showed excellent robustness to bolus arrival delays, with a similar performance to Fermi modeling when delays were considered. Delays were better estimated with the Bayesian approach than with Fermi modeling. An in vivo analysis of coronary artery disease patients revealed that the Bayesian approach had an excellent ability to distinguish between abnormal and normal myocardium. The Bayesian approach was able to discriminate not only flows but also delays with increased sensitivity by offering a clearly enlarged range of distribution for the physiologic parameters.

Influence of the arterial input sampling location on the diagnostic accuracy of cardiovascular magnetic resonance stress myocardial perfusion quantification

BACKGROUND

Quantification of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) by cardiovascular magnetic resonance (CMR) perfusion requires sampling of the arterial input function (AIF). While variation in the AIF sampling location is known to impact quantification by CMR and positron emission tomography (PET) perfusion, there is no evidence to support the use of a specific location based on their diagnostic accuracy in the detection of coronary artery disease (CAD). This study aimed to evaluate the accuracy of stress MBF and MPR for different AIF sampling locations for the detection of abnormal myocardial perfusion with expert visual assessment as the reference.

METHODS

Twenty-five patients with suspected or known CAD underwent vasodilator stress-rest perfusion with a dual-sequence technique at 3T. A low-resolution slice was acquired in 3-chamber view to allow AIF sampling at five different locations: left atrium (LA), basal left ventricle (bLV), mid left ventricle (mLV), apical left ventricle (aLV) and aortic root (AoR). MBF and MPR were estimated at the segmental level using Fermi function-constrained deconvolution. Segments were scored as having normal or abnormal perfusion by visual assessment and the diagnostic accuracy of stress MBF and MPR for each location was evaluated using receiver operating characteristic curve analysis.

RESULTS

In both normal (300 out of 400, 75 %) and abnormal segments, rest MBF, stress MBF and MPR were significantly different across AIF sampling locations (p < 0.001). Stress MBF for the AoR (normal: 2.42 (2.15-2.84) mL/g/min; abnormal: 1.71 (1.28-1.98) mL/g/min) had the highest diagnostic accuracy (sensitivity 80 %, specificity 85 %, area under the curve 0.90; p < 0.001 versus stress MBF for all other locations including bLV: normal: 2.78 (2.39-3.14) mL/g/min; abnormal: 2.22 (1.83-2.48) mL/g/min; sensitivity 91 %, specificity 63 %, area under the curve 0.81) and performed better than MPR for the LV locations (p < 0.01). MPR for the AoR (normal: 2.43 (1.95-3.14); abnormal: 1.58 (1.34-1.90)) was not superior to MPR for the bLV (normal: 2.59 (2.04-3.20); abnormal: 1.69 (1.36-2.14); p = 0.717).

CONCLUSIONS

The AIF sampling location has a significant impact on MBF and MPR estimates by CMR perfusion, with AoR-based stress MBF comparing favorably to that for the current clinical reference bLV.

Automated Segmental Analysis of Fully Quantitative Myocardial Blood Flow Maps by First-Pass Perfusion Cardiovascular Magnetic Resonance

First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows fully quantitative pixel-wise myocardial blood flow (MBF) assessment, with proven diagnostic value for coronary artery disease. Segmental analysis requires manual segmentation of the myocardium. This work presents a fully automatic method of segmenting the left ventricular myocardium from MBF pixel maps, validated on a retrospective dataset of 247 clinical CMR perfusion studies, each including rest and stress images of three slice locations, performed on a 1.5T scanner. Pixel-wise MBF maps were segmented using an automated pipeline including region growing, edge detection, principal component analysis, and active contours to segment the myocardium, detect key landmarks, and divide the myocardium into sectors appropriate for analysis. Automated segmentation results were compared against a manually defined reference standard using three quantitative metrics: Dice coefficient, Cohen Kappa and myocardial border distance. Sector-wise average MBF and myocardial perfusion reserve (MPR) were compared using Pearson's correlation coefficient and Bland-Altman Plots. The proposed method segmented stress and rest MBF maps of 243 studies automatically. Automated and manual myocardial segmentation had an average (± standard deviation) Dice coefficient of 0.86 ± 0.06, Cohen Kappa of 0.86 ± 0.06, and Euclidian distances of 1.47 ± 0.73 mm and 1.02 ± 0.51 mm for the epicardial and endocardial border, respectively. Automated and manual sector-wise MBF and MPR values correlated with Pearson's coefficient of 0.97 and 0.92, respectively, while Bland-Altman analysis showed bias of 0.01 and 0.07 ml/g/min. The validated method has been integrated with our fully automated MBF pixel mapping pipeline to aid quantitative assessment of myocardial perfusion CMR.

Design and evaluation of an abbreviated pixelwise dynamic contrast enhancement analysis protocol for early extracellular volume fraction estimation

INTRODUCTION

T1-based method is considered as the gold standard for extracellular volume fraction (ECV) mapping. This technique requires at least a 10 min delay after injection to acquire the post injection T1 map. Quantitative analysis of Dynamic Contrast Enhancement (DCE) images could lead to an earlier estimation of an ECV like parameter (2 min). The purpose of this study was to design a quantitative pixel-wise DCE analysis workflow to assess the feasibility of an early estimation of ECV.

METHODS

Fourteen patients with mitral valve prolapse were included in this study. The MR protocol, performed on a 3 T MR scanner, included MOLLI sequences for T1 maps acquisition and a standard SR-turboFlash sequence for dynamic acquisition. DCE data were acquired for at least 120 s. We implemented a full DCE analysis pipeline with a pre-processing step using an innovative motion correction algorithm (RC-REG algorithm) and a post-processing step using the extended Tofts Model (ECV_ETM). Estimated ECV_ETM maps were compared to standard T1-based ECV maps (ECV_T1) with both a Pearson correlation analysis and a group-wise analysis.

RESULTS

Image and map quality assessment showed systematic improvements using the proposed workflow. Strong correlation was found between ECV_ETM, and ECV_T1 values (r-square = 0.87).

CONCLUSION

A DCE analysis workflow based on RC-REG algorithm and ETM analysis can provide good quality parametric maps. Therefore, it is possible to extract ECV values from a 2 min-long DCE acquisition that are strongly correlated with ECV values from the T1 based method.

Pathophysiology, classification, and MRI parallels in microvascular disease of the heart and brain

Diagnostic imaging technology in vascular disease has long focused on large vessels and the pathologic processes that impact them. With improved diagnostic techniques, investigators are now able to uncover many underlying mechanisms and prognostic factors for microvascular disease. In the heart and brain, these pathologic entities include coronary microvascular disease and cerebral small vessel disease, both of which have significant impact on patients, causing angina, myocardial infarction, heart failure, stroke, and dementia. In the current paper, we will discuss parallels in pathophysiology, classification, and diagnostic modalities, with a focus on the role of magnetic resonance imaging in microvascular disease of the heart and brain. Novel approaches for streamlined imaging of the cardiac and central nervous systems including the use of intravascular contrast agents such as ferumoxytol are presented, and unmet research gaps in diagnostics are summarized.

Quantification of regional myocardial mean intracellular water lifetime: A nonhuman primate study in myocardial stress

Heart failure with preserved ejection fraction (HFpEF) is typically associated with early metabolic remodeling. Noninvasive imaging biomarkers that reflect these changes will be crucial in determining responses to early drug interventions in these patients. Mean intracellular water lifetime (τ_i ) has been shown to be partially inversely related to Na, K-ATPase transporter activity and may thus provide insight into the metabolic status in HFpEF patients. Here, we aim to perform regional quantification of τ_i using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the nonhuman primate (NHP) heart and evaluate its region-specific variations under conditions of myocardial stress in the context of perturbed myocardial function. Cardiac stress was induced in seven naïve cynomolgus macaques using a dobutamine stepwise infusion protocol. All animals underwent 3 T cardiac dual-bolus DCE and tagging MRI experiments. The shutter-speed model was employed to quantify regional τ_i from the DCE-MR images. Additionally, τ_i values were correlated with myocardial strains. During cardiac stress, there was a significant decrease in global τ_i (192.9 ± 76.3 ms vs 321.6 ± 70 ms at rest, P < 0.05) in the left ventricle, together with an increase in global peak circumferential strain (-15.4% ± 2.7% vs -10.1% ± 2.9% at rest, P < 0.05). Specifically, slice-level analysis further revealed that a greater significant decrease in mean τ_i was observed in the apical region (Δτ_I = 182.4 ms) compared with the basal (Δτ_i = 113.2 ms) and midventricular regions (Δτ_i = 108.4 ms). Regional analysis revealed that there was a greater significant decrease in mean τ_i in the anterior (Δτ_i = 243.9 ms) and antero-lateral (Δτ_i = 177.2 ms) regions. In the inferior and infero-septal regions, although a decrease in τ_i was observed, it was not significant. Whole heart regional quantification of τ_i is feasible using DCE-MRI. τ_i is sensitive to regional changes in metabolic state during cardiac stress, and its value correlates with strain.

Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation

PURPOSE

Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization.

METHODS

Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g).

RESULTS

Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50).

CONCLUSIONS

An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.

Impact of baseline calibration on semiquantitative assessment of myocardial perfusion reserve by adenosine stress MRI

In this study, we sought to investigate the impact of baseline calibration, which is used in quantitative cardiac MRI perfusion analysis to correct for surface coil inhomogeneity and noise, on myocardial perfusion reserve index (MPRI) and its contribution to previously reported paradoxical low MPRI < 1.0 in patients with unobstructed coronary arteries. Semiquantitative perfusion analysis was performed in 20 patients with unobstructed coronary arteries undergoing stress/rest perfusion CMR and in ten patients undergoing paired rest perfusion CMR. The following baseline calibration settings were compared: (1) baseline division, (2) baseline subtraction and (3) no baseline calibration. In uncalibrated analysis, we observed ~ 20% segmental dispersion of signal intensity (SI)-over-time curves. Both baseline subtraction and baseline division reduced relative dispersion of t0-SI (p < 0.001), but only baseline division corrected for dispersion of peak-SI and maximum upslope also (p < 0.001). In the assessment of perfusion indices, however, baseline division resulted in paradoxical low MPRI (1.01 ± 0.23 vs. 1.63 ± 0.38, p < 0.001) and rest perfusion index (RPI 0.54 ± 0.07 vs. 0.94 ± 0.12, p < 0.001), respectively. This was due to a reversed ratio of blood-pool and myocardial baseline-SI before the second perfusion study caused by circulating contrast agent from the first injection. In conclusion, baseline division reliably corrects for inhomogeneity of the surface coil sensitivity profile facilitating comparisons of regional myocardial perfusion during hyperemia or at rest. However, in the assessment of MPRI, baseline division can lead to paradoxical low results (even MPRI < 1.0 in patients with unobstructed coronary arteries) potentially mimicking severely impaired perfusion reserve. Thus, in the assessment of MPRI we propose to waive baseline calibration.

Danish study of Non-Invasive testing in Coronary Artery Disease 2 (Dan-NICAD 2): Study design for a controlled study of diagnostic accuracy

BACKGROUND

Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), ⁸²rubidium positron emission tomography (⁸²Rb-PET), and CT-derived fractional flow reserve (FFR_CT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using ⁸²Rb-PET as reference standard.

METHODS

Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI ⁸²Rb-PET, FFR_CT, ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion.

DISCUSSION

The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR.

Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification

This work presents a new mathematical model to describe cardiac perfusion in the myocardium as acquired by cardiac magnetic resonance (CMR) perfusion exams. The combination of first pass (or contrast-enhanced CMR) and late enhancement CMR is a widely used non-invasive exam that can identify abnormal perfused regions of the heart via the use of a contrast agent (CA). The exam provides important information to the diagnosis, management, and prognosis of ischemia and infarct: perfusion on different regions, the status of microvascular structures, the presence of fibrosis, and the relative volume of extracellular space. This information is obtained by inferring the spatiotemporal dynamics of the contrast in the myocardial tissue from the acquired images. The evaluation of these physiological parameters plays an important role in the assessment of myocardial viability. However, the nature of cardiac physiology poses great challenges in the estimation of these parameters. Briefly, these are currently estimated qualitatively via visual inspection of images and comparison of relative brightness between different regions of the heart. Therefore, there is a great urge for techniques that can help to quantify cardiac perfusion. In this work, we propose a new mathematical model based on multidomain flow in porous media. The model is based on a system of partial differential equations. Darcy's law is used to obtain the pressure and velocity distribution. CA dynamics is described by reaction-diffusion-advection equations in the intravascular space and in the interstitial space. The interaction of fibrosis and the CA is also considered. The new model treats the domains as anisotropic media and imposes a closed loop of intravascular flow, which is necessary to reproduce the recirculation of the CA. The model parameters were adjusted to reproduce clinical data. In addition, the model was used to simulate different scenarios: normal perfusion; endocardial ischemia due to stenosis in a coronary artery in the epicardium; and myocardial infarct. Therefore, the computational model was able to correlate anatomical features, stenosis and the presence of fibrosis, with functional ones, cardiac perfusion. Altogether, the results suggest that the model can support the process of non-invasive cardiac perfusion quantification.

Fully quantitative pixel-wise analysis of cardiovascular magnetic resonance perfusion improves discrimination of dark rim artifact from perfusion defects associated with epicardial coronary stenosis

BACKGROUND

Dark rim artifacts in first-pass cardiovascular magnetic resonance (CMR) perfusion images can mimic perfusion defects and affect diagnostic accuracy for coronary artery disease (CAD). We evaluated whether quantitative myocardial blood flow (MBF) can differentiate dark rim artifacts from true perfusion defects in CMR perfusion.

METHODS

Regadenoson perfusion CMR was performed at 1.5 T in 76 patients. Significant CAD was defined by quantitative invasive coronary angiography (QCA) ≥ 50% diameter stenosis. Non-significant CAD (NonCAD) was defined as stenosis by QCA < 50% diameter stenosis or computed tomographic coronary angiography (CTA) < 30% in all major epicardial arteries. Dark rim artifacts had study specific and guideline-based definitions for comparison purposes. MBF was quantified at the pixel-level and sector-level.

RESULTS

In a NonCAD subgroup with dark rim artifacts, stress MBF was lower in the subendocardial than midmyocardial and epicardial layers (2.17 ± 0.61 vs. 3.06 ± 0.75 vs. 3.24 ± 0.80 mL/min/g, both p < 0.001) and was also 30% lower than in remote regions (2.17 ± 0.61 vs. 2.83 ± 0.67 mL/min/g, p < 0.001). However, subendocardial stress MBF in dark rim artifacts was 37-56% higher than in true perfusion defects (2.17 ± 0.61 vs. 0.95 ± 0.43 mL/min/g, p < 0.001). Absolute stress MBF differentiated CAD from NonCAD with an accuracy ranging from 86 to 89% (all p < 0.001) using pixel-level analyses. Similar results were seen at a sector level.

CONCLUSION

Quantitative stress MBF is lower in dark rim artifacts than remote myocardium but significantly higher than in true perfusion defects. If confirmed in larger series, this approach may aid the interpretation of clinical stress perfusion exams.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00027170 ; first posted 11/28/2001; updated 11/27/2017.

Diagnostic Performance of Fully Automated Pixel-Wise Quantitative Myocardial Perfusion Imaging by Cardiovascular Magnetic Resonance

OBJECTIVES

The authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients.

BACKGROUND

Fully quantitative CMR perfusion pixel maps were previously validated with microsphere MBF measurements and showed potential in clinical applications, but the methods required laborious manual processes and were excessively time-consuming.

METHODS

CMR perfusion imaging was performed on 80 patients with known or suspected coronary artery disease (CAD) and 17 healthy volunteers. Significant CAD was defined by quantitative coronary angiography (QCA) as ≥70% stenosis. Nonsignificant CAD was defined by: 1) QCA as <70% stenosis; or 2) coronary computed tomography angiography as <30% stenosis and a calcium score of 0 in all vessels. Automatically generated MBF maps were compared with manual quantification on healthy volunteers. Diagnostic performance of the automated MBF pixel maps was analyzed on patients using absolute MBF, myocardial perfusion reserve (MPR), and relative measurements of MBF and MPR.

RESULTS

The correlation between automated and manual quantification was excellent (r = 0.96). Stress MBF and MPR in the ischemic zone were lower than those in the remote myocardium in patients with significant CAD (both p < 0.001). Stress MBF and MPR in the remote zone of the patients were lower than those in the normal volunteers (both p < 0.001). All quantitative metrics had good area under the curve (0.864 to 0.926), sensitivity (82.9% to 91.4%), and specificity (75.6% to 91.1%) on per-patient analysis. On a per-vessel analysis of the quantitative metrics, area under the curve (0.837 to 0.864), sensitivity (75.0% to 82.7%), and specificity (71.8% to 80.9%) were good.

CONCLUSIONS

Fully quantitative CMR MBF pixel maps can be generated automatically, and the results agree well with manual quantification. These methods can discriminate regional perfusion variations and have high diagnostic performance for detecting significant CAD. (Technical Development of Cardiovascular Magnetic Resonance Imaging; NCT00027170)

Vascular input function correction of inflow enhancement for improved pharmacokinetic modeling of liver DCE-MRI

PURPOSE

To propose a simple method to correct vascular input function (VIF) due to inflow effects and to test whether the proposed method can provide more accurate VIFs for improved pharmacokinetic modeling.

METHODS

A spoiled gradient echo sequence-based inflow quantification and contrast agent concentration correction method was proposed. Simulations were conducted to illustrate improvement in the accuracy of VIF estimation and pharmacokinetic fitting. Animal studies with dynamic contrast-enhanced MR scans were conducted before, 1 week after, and 2 weeks after portal vein embolization (PVE) was performed in the left portal circulation of pigs. The proposed method was applied to correct the VIFs for model fitting. Pharmacokinetic parameters fitted using corrected and uncorrected VIFs were compared between different lobes and visits.

RESULTS

Simulation results demonstrated that the proposed method can improve accuracy of VIF estimation and pharmacokinetic fitting. In animal study results, pharmacokinetic fitting using corrected VIFs demonstrated changes in perfusion consistent with changes expected after PVE, whereas the perfusion estimates derived by uncorrected VIFs showed no significant changes.

CONCLUSION

The proposed correction method improves accuracy of VIFs and therefore provides more precise pharmacokinetic fitting. This method may be promising in improving the reliability of perfusion quantification. Magn Reson Med 79:3093-3102, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Demonstration of velocity selective myocardial arterial spin labeling perfusion imaging in humans

PURPOSE

Transit delay is a potential source of error in cardiac arterial spin-labeled (ASL) in heart failure or with collateral circulation. This study demonstrates the feasibility of using transit delay insensitive velocity selective ASL and compares its performance with flow-sensitive alternating inversion recovery (FAIR) ASL.

METHODS

Velocity selective labeling was achieved using an adiabatic BIR8 preparation. FAIR and velocity-selective ASL (VSASL) with various velocity cutoffs (V_C  = 10-40 cm/s) and labeling directions (anterior-posterior X, lateral-septal Y, and apical-basal Z) were carried out in 10 healthy volunteers (1F/9M age 23-30 y). Myocardial blood flow (MBF) and temporal signal-to-noise (TSNR) were measured.

RESULTS

VSASL sensitivity to perfusion decreased with increasing V_C . At low V_C (<5 cm/s), spurious labeling of myocardium occurs and overestimates MBF. MBF measured with FAIR (1.12 ± 0.26 ml/g/min) and VASL (1.26 ± 0.27 ml/g/min) at V_C of 10 cm/s in Z were comparable (TOST with difference of 0.30 ml/g/min, P = 0.049). TSNR was 2.8 times larger using FAIR (13.62 ± 5.25) than in VSASL (4.87 ± 1.58). VSASL was insensitive to perfusion in the Y direction. X and Z performed similarly with TSNR of 4.17 ± 2.32 and 3.97 ± 0.56, respectively.

CONCLUSION

VSASL is a promising alternative to FAIR ASL in the heart and is well suited for scenarios when transit delays are long. Magn Reson Med 80:272-278, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification

BACKGROUND

Quantification of myocardial blood flow requires knowledge of the amount of contrast agent in the myocardial tissue and the arterial input function (AIF) driving the delivery of this contrast agent. Accurate quantification is challenged by the lack of linearity between the measured signal and contrast agent concentration. This work characterizes sources of non-linearity and presents a systematic approach to accurate measurements of contrast agent concentration in both blood and myocardium.

METHODS

A dual sequence approach with separate pulse sequences for AIF and myocardial tissue allowed separate optimization of parameters for blood and myocardium. A systems approach to the overall design was taken to achieve linearity between signal and contrast agent concentration. Conversion of signal intensity values to contrast agent concentration was achieved through a combination of surface coil sensitivity correction, Bloch simulation based look-up table correction, and in the case of the AIF measurement, correction of T2* losses. Validation of signal correction was performed in phantoms, and values for peak AIF concentration and myocardial flow are provided for 29 normal subjects for rest and adenosine stress.

RESULTS

For phantoms, the measured fits were within 5% for both AIF and myocardium. In healthy volunteers the peak [Gd] was 3.5 ± 1.2 for stress and 4.4 ± 1.2 mmol/L for rest. The T2* in the left ventricle blood pool at peak AIF was approximately 10 ms. The peak-to-valley ratio was 5.6 for the raw signal intensities without correction, and was 8.3 for the look-up-table (LUT) corrected AIF which represents approximately 48% correction. Without T2* correction the myocardial blood flow estimates are overestimated by approximately 10%. The signal-to-noise ratio of the myocardial signal at peak enhancement (1.5 T) was 17.7 ± 6.6 at stress and the peak [Gd] was 0.49 ± 0.15 mmol/L. The estimated perfusion flow was 3.9 ± 0.38 and 1.03 ± 0.19 ml/min/g using the BTEX model and 3.4 ± 0.39 and 0.95 ± 0.16 using a Fermi model, for stress and rest, respectively.

CONCLUSIONS

A dual sequence for myocardial perfusion cardiovascular magnetic resonance and AIF measurement has been optimized for quantification of myocardial blood flow. A validation in phantoms was performed to confirm that the signal conversion to gadolinium concentration was linear. The proposed sequence was integrated with a fully automatic in-line solution for pixel-wise mapping of myocardial blood flow and evaluated in adenosine stress and rest studies on N = 29 normal healthy subjects. Reliable perfusion mapping was demonstrated and produced estimates with low variability.

A look-locker acquisition scheme for quantitative myocardial perfusion imaging with FAIR arterial spin labeling in humans at 3 tesla

PURPOSE

A novel method for quantitative measurement of myocardial blood flow (MBF) using arterial spin labeling (ASL) in a single breath-hold is presented, evaluated by simulations, phantom studies and in vivo studies and tested for reproducibility and variability.

METHODS

A flow-sensitive alternating inversion recovery (FAIR) ASL method with Look-Locker readout (LL-FAIR-ASL) was implemented at 3 tesla. Scans were performed on 10 healthy volunteers and MBF measured in three slices. The method was investigated for reproducibility by Bland-Altman analysis and statistical measures, the coefficients of reproducibility (CR) and variation (CV) are reported.

RESULTS

The MBF values for the basal, mid, and apical slices were 1.04 ± 0.40, 1.06 ± 0.46, and 1.06 ± 0.38 ml/g/min, respectively (mean ± SD), which compare well with literature values. The CV across all scans, 43%, was greater than the between-session and within-session values, at 16 and 13%, respectively, for the mid-ventricular slice. The change in MBF required for detection, from the CR, was 61% between-session and 53% within-session for the mid-ventricle.

CONCLUSION

This study shows the feasibility of the LL-FAIR-ASL method for the quantification of MBF. The statistical measures reported will allow the planning of future clinical research studies involving rest and stress measurements. Magn Reson Med 78:541-549, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Quantitative MRI biomarkers to characterize regional left ventricular perfusion and function in nonhuman primates during dobutamine-induced stress: A reproducibility and reliability study

PURPOSE

To identify reproducible and reliable noninvasive regional imaging biomarkers of cardiac function and perfusion at rest and under stress in healthy nonhuman primates (NHPs) that may be used in the future for the early characterization of preclinical heart failure models, to evaluate therapy, and for clinical translation.

MATERIALS AND METHODS

Seven naive cynomolgus macaques underwent test-retest 3T cardiac MRI tagging and dual-bolus perfusion experiments. Regional cardiac function biomarkers, such as peak circumferential strain (CS), average diastolic strain-rate (DSR), contractile reserve (CR), diastolic reserve, peak torsion, and torsion reserve were quantified. Further, regional myocardial blood flow (MBF), myocardial perfusion reserve (MPR), and myocardial perfusion reserve-to-contractile reserve (MPR/CR) were also derived. Inter- and intraobserver reproducibility and test-retest reliability analyses were conducted using the reliability and generalizability coefficients including correlation coefficient (CC) and intraclass correlation coefficient (ICC).

RESULTS

Overall, peak CS, DSR, and MBF are robust biomarkers at both rest and stress with moderate-good inter- and intraobserver reproducibility and test-retest reliability. At rest: intra-/interobserver reproducibility (CC): peak CS (0.81/0.81), DSR (0.81/0.81), MBF (0.72/0.57), peak torsion (0.79/0.79); test-retest reliability: (CC/ICC): peak CS (0.62/0.75), DSR (0.24/0.55), MBF (0.66/0.62), and peak torsion (0.79/0.78). Under stress: intra-/interobserver reproducibility (CC): peak CS (0.61/0.60), DSR (0.50/0.50), MBF (0.63/0.61), MPR (0.43/0.43), and peak torsion (0.38/0.38); test-retest reliability: (CC/ICC): peak CS (0.58/0.58), DSR (0.24/0.43), MBF (0.58/0.58), MPR (0.43/0.38), and peak torsion (0.38/0.38).

CONCLUSION

We demonstrated the feasibility of using cardiac MRI to characterize left ventricular functional and perfusion responses to stress in an NHP species, and specific robust biomarkers such as peak CS, DSR, MBF, diastolic reserve, and MPR have been identified for clinical translation and drug research.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:556-569.

Myocardial arterial spin labeling

Arterial spin labeling (ASL) is a cardiovascular magnetic resonance (CMR) technique for mapping regional myocardial blood flow. It does not require any contrast agents, is compatible with stress testing, and can be performed repeatedly or even continuously. ASL-CMR has been performed with great success in small-animals, but sensitivity to date has been poor in large animals and humans and remains an active area of research. This review paper summarizes the development of ASL-CMR techniques, current state-of-the-art imaging methods, the latest findings from pre-clinical and clinical studies, and future directions. We also explain how successful developments in brain ASL and small-animal ASL-CMR have helped to inform developments in large animal and human ASL-CMR.

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.

Resting myocardial blood flow quantification using contrast-enhanced magnetic resonance imaging in the presence of stenosis: A computational fluid dynamics study

PURPOSE

The extent to which atherosclerotic plaques affect contrast agent (CA) transport in the coronary arteries and, hence, quantification of myocardial blood flow (MBF) using magnetic resonance imaging (MRI) is unclear. The purpose of this work was to evaluate the influence of plaque induced stenosis both on CA transport and on the accuracy of MBF quantification.

METHODS

Computational fluid dynamics simulations in a high-detailed realistic vascular model were employed to investigate CA bolus transport in the coronary arteries. The impact of atherosclerosis was analyzed by inserting various medium- to high-grade stenoses in the vascular model. The influence of stenosis morphology was examined by varying the stenosis shapes but keeping the area reduction constant. Errors due to CA bolus transport were analyzed using the tracer-kinetic model MMID4.

RESULTS

Dispersion of the CA bolus was found in all models and for all outlets, but with a varying magnitude. The impact of stenosis was complex: while high-grade stenoses amplified dispersion, mild stenoses reduced the effect. Morphology was found to have a marked influence on dispersion for a small number of outlets in the post-stenotic region. Despite this marked influence on the concentration-time curves, MBF errors were less affected by stenosis. In total, MBF was underestimated by -7.9% to -44.9%.

CONCLUSIONS

The presented results reveal that local hemodynamics in the coronary vasculature appears to have a direct impact on CA bolus dispersion. Inclusion of atherosclerotic plaques resulted in a complex alteration of this effect, with both degree of area reduction and stenosis morphology affecting the amount of dispersion. This strong influence of vascular transport effects impairs the accuracy of MRI-based MBF quantification techniques and, potentially, other bolus-based perfusion measurement techniques like computed tomography perfusion imaging.

Quantification of myocardial blood flow using non-electrocardiogram-triggered MRI with three-slice coverage

PURPOSE

Accurate quantification of myocardial perfusion is dependent on reliable electrocardiogram (ECG) triggering. Measuring myocardial blood flow (MBF) in patients with arrhythmias or poor ECGs is currently infeasible with MR. The purpose of this study was to demonstrate the feasibility of a non-ECG-triggered method with clinically useful three-slice ventricular coverage for measurement of MBF in healthy volunteers.

METHODS

A saturation recovery magnetization-prepared gradient recalled echo acquisition was continuously repeated during first-pass imaging. A slice-interleaved radial trajectory was employed to enable image-based retrospective triggering. The arterial input function was generated using a beat-by-beat T1 estimation method. The proposed technique was validated against a conventional ECG-triggered dual-bolus technique in 10 healthy volunteers. The technique was further demonstrated under adenosine stress in 12 healthy volunteers.

RESULTS

The proposed method produced MBF with no significant difference compared with the ECG-triggered technique. The proposed method yielded mean myocardial perfusion reserve comparable to published literature.

CONCLUSION

We have developed a non-ECG-triggered quantitative perfusion imaging method. In this preliminary study, our results demonstrate that our method yields comparable MBF compared with the conventional ECG-triggered method and that it is feasible for stress imaging.

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

PURPOSE

To compare methods designed to minimize or correct signal nonlinearity in quantitative myocardial dynamic contrast-enhanced (DCE) MRI.

METHODS

DCE-MRI studies were simulated and data acquired in eight volunteers. Signal nonlinearity was corrected using either a dual-bolus approach or model-based correction using proton-density weighted imaging (conventional or dual-sequence acquisition) or T1 data (native or bookend). Scanning of healthy and infarcted myocardium at 3 T was simulated, including noise, saturation imperfection and T1 measurement error. Data were analyzed using model-based deconvolution with a one-compartment (mono-exponential) model.

RESULTS

Substantial variation between methods was demonstrated in volunteers. In simulations the dual-bolus method proved stable for realistic levels of saturation efficiency but demonstrated bias due to residual nonlinearity. Model-based methods performed ideally in the absence of confounding error sources and were generally robust to noise or saturation imperfection, except for native T1 based correction which was highly sensitive to the latter. All methods demonstrated large variation in accuracy above an over-saturation level where baseline signal was nulled. For the dual-sequence approach this caused substantial bias at the saturation efficiencies observed in volunteers.

CONCLUSION

The choice of nonlinearity correction method in myocardial DCE-MRI impacts on accuracy and precision of estimated parameters, particularly in the presence of nonideal saturation.

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.

Cyclosporine A reduces microvascular obstruction and preserves left ventricular function deterioration following myocardial ischemia and reperfusion

Postconditioning and cyclosporine A prevent mitochondrial permeability transition pore opening providing cardioprotection during ischemia/reperfusion. Whether microvascular obstruction is affected by these interventions is largely unknown. Pigs subjected to coronary occlusion for 1 h followed by 3 h of reperfusion were assigned to control (n = 8), postconditioning (n = 9) or cyclosporine A intravenous infusion 10–15 min before the end of ischemia (n = 8). Postconditioning was induced by 8 cycles of repeated 30-s balloon inflation and deflation. After 3 h of reperfusion magnetic resonance imaging, triphenyltetrazolium chloride/Evans blue staining and histopathology were performed. Microvascular obstruction (MVO, percentage of gadolinium-hyperenhanced area) was measured early (3 min) and late (12 min) after contrast injection. Infarct size with double staining was smaller in cyclosporine (46.2 ± 3.1 %, P = 0.016) and postconditioning pigs (47.6 ± 3.9 %, P = 0.008) versus controls (53.8 ± 4.1 %). Late MVO was significantly reduced by cyclosporine (13.9 ± 9.6 %, P = 0.047) but not postconditioning (23.6 ± 11.7 %, P = 0.66) when compared with controls (32.0 ± 16.9 %). Myocardial blood flow in the late MVO was improved with cyclosporine versus controls (0.30 ± 0.06 vs 0.21 ± 0.03 ml/g/min, P = 0.002) and was inversely correlated with late-MVO extent (R² = 0.93, P < 0.0001). Deterioration of left ventricular ejection fraction (LVEF) between baseline and 3 h of reperfusion was smaller with cyclosporine (−7.9 ± 2.4 %, P = 0.008) but not postconditioning (−12.0 ± 5.5 %, P = 0.22) when compared with controls (−16.4 ± 5.5 %). In the three groups, infarct size (β = −0.69, P < 0.001) and late MVO (β = −0.33, P = 0.02) were independent predictors of LVEF deterioration following ischemia/reperfusion (R² = 0.73, P < 0.001). Despite both cyclosporine A and postconditioning reduce infarct size, only cyclosporine A infusion had a beneficial effect on microvascular damage and was associated with better preserved LV function when compared with controls.

Optimization of dual-saturation single bolus acquisition for quantitative cardiac perfusion and myocardial blood flow maps

BACKGROUND

In-vivo quantification of cardiac perfusion is of great research and clinical value. The dual-bolus strategy is universally used in clinical protocols but has known limitations. The dual-saturation acquisition strategy has been proposed as a more accurate alternative, but has not been validated across the wide range of perfusion rates encountered clinically. Dual-saturation acquisition also lacks a clinically-applicable procedure for optimizing parameter selection. Here we present a comprehensive validation study of dual-saturation strategy in vitro and in vivo.

METHODS

The impact of saturation time and profile ordering in acquisitions was systematically analyzed in a phantom consisting of 15 tubes containing different concentrations of contrast agent. In-vivo experiments in healthy pigs were conducted to evaluate the effect of R2* on the definition of the arterial input function (AIF) and to evaluate the relationship between R2* and R1 variations during first-pass of the contrast agent. Quantification by dual-saturation perfusion was compared with the reference-standard dual-bolus strategy in 11 pigs with different grades of myocardial perfusion.

RESULTS

Adequate flow estimation by the dual-saturation strategy is achieved with myocardial tissue saturation times around 100 ms (always <30 ms of AIF), with the lowest echo time, and following a signal model for contrast conversion that takes into account the residual R2* effect and profile ordering. There was a good correlation and agreement between myocardial perfusion quantitation by dual-saturation and dual-bolus techniques (R(2) = 0.92, mean difference of 0.1 ml/min/g; myocardial perfusion ranges between 0.18 and 3.93 ml/min/g).

CONCLUSIONS

The dual-saturation acquisition strategy produces accurate estimates of absolute myocardial perfusion in vivo. The procedure presented here can be applied with minimal interference in standard clinical procedures.

FLASH proton density imaging for improved surface coil intensity correction in quantitative and semi-quantitative SSFP perfusion cardiovascular magnetic resonance

BACKGROUND

A low excitation flip angle (α < 10°) steady-state free precession (SSFP) proton-density (PD) reference scan is often used to estimate the B1-field inhomogeneity for surface coil intensity correction (SCIC) of the saturation-recovery (SR) prepared high flip angle (α = 40-50°) SSFP myocardial perfusion images. The different SSFP off-resonance response for these two flip angles might lead to suboptimal SCIC when there is a spatial variation in the background B0-field. The low flip angle SSFP-PD frames are more prone to parallel imaging banding artifacts in the presence of off-resonance. The use of FLASH-PD frames would eliminate both the banding artifacts and the uneven frequency response in the presence of off-resonance in the surface coil inhomogeneity estimate and improve homogeneity of semi-quantitative and quantitative perfusion measurements.

METHODS

B0-field maps, SSFP and FLASH-PD frames were acquired in 10 healthy volunteers to analyze the SSFP off-resonance response. Furthermore, perfusion scans preceded by both FLASH and SSFP-PD frames from 10 patients with no myocardial infarction were analyzed semi-quantitatively and quantitatively (rest n = 10 and stress n = 1). Intra-subject myocardial blood flow (MBF) coefficient of variation (CoV) over the whole left ventricle (LV), as well as intra-subject peak contrast (CE) and upslope (SLP) standard deviation (SD) over 6 LV sectors were investigated.

RESULTS

In the 6 out of 10 cases where artifacts were apparent in the LV ROI of the SSFP-PD images, all three variability metrics were statistically significantly lower when using the FLASH-PD frames as input for the SCIC (CoVMBF-FLASH = 0.3 ± 0.1, CoVMBF-SSFP = 0.4 ± 0.1, p = 0.03; SDCE-FLASH = 10 ± 2, SDCE-SSFP = 32 ± 7, p = 0.01; SDSLP-FLASH = 0.02 ± 0.01, SDSLP-SSFP = 0.06 ± 0.02, p = 0.03). Example rest and stress data sets from the patient pool demonstrate that the low flip angle SSFP protocol can exhibit severe ghosting artifacts originating from off-resonance banding artifacts at the edges of the field of view that parallel imaging is not able to unfold. These artifacts lead to errors in the quantitative perfusion maps and the semi-quantitative perfusion indexes, such as false positives. It is shown that this can be avoided by using FLASH-PD frames as input for the SCIC.

CONCLUSIONS

FLASH-PD images are recommended as input for SCIC of SSFP perfusion images instead of low flip angle SSFP-PD images.

Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus

BACKGROUND

Mathematical modeling of cardiovascular magnetic resonance perfusion data allows absolute quantification of myocardial blood flow. Saturation of left ventricle signal during standard contrast administration can compromise the input function used when applying these models. This saturation effect is evident during application of standard Fermi models in single bolus perfusion data. Dual bolus injection protocols have been suggested to eliminate saturation but are much less practical in the clinical setting. The distributed parameter model can also be used for absolute quantification but has not been applied in patients with coronary artery disease. We assessed whether distributed parameter modeling might be less dependent on arterial input function saturation than Fermi modeling in healthy volunteers. We validated the accuracy of each model in detecting reduced myocardial blood flow in stenotic vessels versus gold-standard invasive methods.

METHODS

Eight healthy subjects were scanned using a dual bolus cardiac perfusion protocol at 3T. We performed both single and dual bolus analysis of these data using the distributed parameter and Fermi models. For the dual bolus analysis, a scaled pre-bolus arterial input function was used. In single bolus analysis, the arterial input function was extracted from the main bolus. We also performed analysis using both models of single bolus data obtained from five patients with coronary artery disease and findings were compared against independent invasive coronary angiography and fractional flow reserve. Statistical significance was defined as two-sided P value < 0.05.

RESULTS

Fermi models overestimated myocardial blood flow in healthy volunteers due to arterial input function saturation in single bolus analysis compared to dual bolus analysis (P < 0.05). No difference was observed in these volunteers when applying distributed parameter-myocardial blood flow between single and dual bolus analysis. In patients, distributed parameter modeling was able to detect reduced myocardial blood flow at stress (<2.5 mL/min/mL of tissue) in all 12 stenotic vessels compared to only 9 for Fermi modeling.

CONCLUSIONS

Comparison of single bolus versus dual bolus values suggests that distributed parameter modeling is less dependent on arterial input function saturation than Fermi modeling. Distributed parameter modeling showed excellent accuracy in detecting reduced myocardial blood flow in all stenotic vessels.

Quantification of myocardial perfusion with self-gated cardiovascular magnetic resonance

BACKGROUND

Current myocardial perfusion measurements make use of an ECG-gated pulse sequence to track the uptake and washout of a gadolinium-based contrast agent. The use of a gated acquisition is a problem in situations with a poor ECG signal. Recently, an ungated perfusion acquisition was proposed but it is not known how accurately quantitative perfusion estimates can be made from such datasets that are acquired without any triggering signal.

METHODS

An undersampled saturation recovery radial turboFLASH pulse sequence was used in 7 subjects to acquire dynamic contrast-enhanced images during free-breathing. A single saturation pulse was followed by acquisition of 4-5 slices after a delay of ~40 msec. This was repeated without pause and without any type of gating. The same pulse sequence, with ECG-gating, was used to acquire gated data as a ground truth. An iterative spatio-temporal constrained reconstruction was used to reconstruct the undersampled images. After reconstruction, the ungated images were retrospectively binned ("self-gated") into two cardiac phases using a region of interest based technique and deformably registered into near-systole and near-diastole. The gated and the self-gated datasets were then quantified with standard methods.

RESULTS

Regional myocardial blood flow estimates (MBFs) obtained using self-gated systole (0.64 ± 0.26 ml/min/g), self-gated diastole (0.64 ± 0.26 ml/min/g), and ECG-gated scans (0.65 ± 0.28 ml/min/g) were similar. Based on the criteria for interchangeable methods listed in the statistical analysis section, the MBF values estimated from self-gated and gated methods were not significantly different.

CONCLUSION

The self-gated technique for quantification of regional myocardial perfusion matched ECG-gated perfusion measurements well in normal subjects at rest. Self-gated systolic perfusion values matched ECG-gated perfusion values better than did diastolic values.

Quantitative pixel-wise measurement of myocardial blood flow: the impact of surface coil-related field inhomogeneity and a comparison of methods for its correction

BACKGROUND

Surface coil-related field inhomogeneity potentially confounds pixel-wise quantitative analysis of perfusion CMR images. This study assessed the effect of surface coil-related field inhomogeneity on the spatial variation of pixel-wise myocardial blood flow (MBF), and assessed its impact on the ability of MBF quantification to differentiate ischaemic from remote coronary territories. Two surface coil intensity correction (SCIC) techniques were evaluated: 1) a proton density-based technique (PD-SCIC) and; 2) a saturation recovery steady-state free precession-based technique (SSFP-SCIC).

METHODS

26 subjects (18 with significant CAD and 8 healthy volunteers) underwent stress perfusion CMR using a motion-corrected, saturation recovery SSFP dual-sequence protocol. A proton density (PD)-weighted image was acquired at the beginning of the sequence. Surface coil-related field inhomogeneity was approximated using a third-order surface fit to the PD image or a pre-contrast saturation prepared SSFP image. The estimated intensity bias field was subsequently applied to the image series. Pixel-wise MBF was measured from mid-ventricular stress images using the two SCIC approaches and compared to measurements made without SCIC.

RESULTS

MBF heterogeneity in healthy volunteers was higher using SSFP-SCIC (24.8 ± 4.1%) compared to PD-SCIC (20.8 ± 3.0%; p = 0.009), however heterogeneity was significantly lower using either SCIC technique compared to analysis performed without SCIC (36.2 ± 6.3%). In CAD patients, the difference in MBF between remote and ischaemic territories was minimal when analysis was performed without SCIC (0.06 ± 0.91 mL/min/kg), and was substantially lower than with either PD-SCIC (0.50 ± 0.63 mL/min/kg; p = 0.013) or with SSFP-SCIC (0.63 ± 0.89 mL/min/kg; p = 0.005). In 6 patients, MBF quantified without SCIC was artifactually higher in the stenosed coronary territory compared to the remote territory. PD-SCIC and SSFP-SCIC had similar differences in MBF between remote and ischaemic territories (p = 0.145).

CONCLUSIONS

This study demonstrates that surface coil-related field inhomogeneity can confound pixel-wise MBF quantification. Whilst a PD-based SCIC led to a more homogenous correction than a saturation recovery SSFP-based technique, this did not result in an appreciable difference in the differentiation of ischaemic from remote coronary territories and thus either method could be applied.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment

OBJECTIVES

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation.

BACKGROUND

Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited.

METHODS

Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal.

RESULTS

The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively).

CONCLUSIONS

Fully quantitative stress perfusion CMR has high diagnostic accuracy for detecting obstructive coronary artery disease. QP outperforms semiquantitative measures of perfusion and qualitative methods that incorporate a combination of cine, perfusion, and late gadolinium enhancement imaging. These findings suggest a potential clinical role for quantitative stress perfusion CMR.

DCE-MRI of the liver: reconstruction of the arterial input function using a low dose pre-bolus contrast injection

Purpose

To assess the quality of the arterial input function (AIF) reconstructed using a dedicated pre-bolus low-dose contrast material injection imaged with a high temporal resolution and the resulting estimated liver perfusion parameters.

Materials and Methods

In this IRB–approved prospective study, 24 DCE-MRI examinations were performed in 21 patients with liver disease (M/F 17/4, mean age 56 y). The examination consisted of 1.3 mL and 0.05 mmol/kg of gadobenate dimeglumine for pre-bolus and main bolus acquisitions, respectively. The concentration-curve of the abdominal aorta in the pre-bolus acquisition was used to reconstruct the AIF. AIF quality and shape parameters obtained with pre-bolus and main bolus acquisitions and the resulting estimated hepatic perfusion parameters obtained with a dual-input single compartment model were compared between the 2 methods. Test–retest reproducibility of perfusion parameters were assessed in three patients.

Results

The quality of the pre-bolus AIF curve was significantly better than that of main bolus AIF. Shape parameters peak concentration, area under the time activity curve of gadolinium contrast at 60 s and upslope of pre-bolus AIF were all significantly higher, while full width at half maximum was significantly lower than shape parameters of main bolus AIF. Improved liver perfusion parameter reproducibility was observed using pre-bolus acquisition [coefficient of variation (CV) of 4.2%–38.7% for pre-bolus vs. 12.1–71.4% for main bolus] with the exception of distribution volume (CV of 23.6% for pre-bolus vs. 15.8% for main bolus). The CVs between pre-bolus and main bolus for the perfusion parameters were lower than 14%.

Conclusion

The AIF reconstructed with pre-bolus low dose contrast injection displays better quality and shape parameters and enables improved liver perfusion parameter reproducibility, although the resulting liver perfusion parameters demonstrated no clinically significant differences between pre-bolus and main bolus acquisitions.

Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy

PURPOSE

To compare the diagnostic performance of four tracer kinetic analysis methods to quantify myocardial perfusion from magnetic resonance (MR) imaging cardiac perfusion data sets in terms of their ability to lead to the diagnosis of myocardial ischemia.

MATERIALS AND METHODS

The study was approved by the regional ethics committee, and all patients gave written consent. A representative sample of 50 patients with suspected ischemic heart disease was retrospectively selected from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease trial data set. Quantitative myocardial blood flow (MBF) was estimated from rest and adenosine stress MR imaging perfusion data sets by using four established methods. A matching diagnosis of both an inducible defect as assessed with single photon emission computed tomography and a luminal stenosis of 70% or more as assessed with quantitative x-ray angiography was used as the reference standard for the presence of myocardial ischemia. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for each method, with stress MBF and myocardial perfusion reserve (MPR) serving as continuous measures.

RESULTS

Area under the ROC curve with stress MBF and MPR as the outcome measures, respectively, was 0.86 and 0.92 for the Fermi model, 0.85 and 0.87 for the uptake model, 0.85 and 0.80 for the one-compartment model, and 0.87 and 0.87 for model-independent deconvolution. There was no significant difference between any of the models or between MBF and MPR, except that the Fermi model outperformed the one-compartment model if MPR was used as the outcome measure (P = .02).

CONCLUSION

Diagnostic performance of quantitative myocardial perfusion estimates is not affected by the tracer kinetic analysis method used.

Quantification of myocardial blood flow using non-ECG-triggered MR imaging

PURPOSE

MR myocardial perfusion imaging is dependent on reliable electrocardiogram (ECG) triggering for accurate measurement of myocardial blood flow (MBF). A non-ECG-triggered method for quantitative first-pass imaging may improve clinical feasibility in patients with poor ECG signal. The purpose of this study is to evaluate the feasibility of a non-ECG-triggered method for myocardial perfusion imaging in a single slice.

METHODS

The proposed non-ECG-triggered technique uses a saturation-recovery magnetization preparation and golden-angle radial acquisition for integrated arterial input function (AIF) measurement. Image based self-gating with a temporal resolution of 42.6 ms is used to generate a first-pass image series with consistent cardiac phase. The AIF is measured using beat-by-beat T1 estimation of the ventricular blood pool. The proposed technique was performed on 14 healthy volunteers and compared against a conventional ECG-triggered dual-bolus acquisition.

RESULTS

The proposed method produced MBF with no significant difference compared with ECG-triggered technique (mean of 0.63 ± 0.22 mL/min/g to 0.73 ± 0.21 mL/min/g).

CONCLUSION

We have developed a non-ECG-triggered perfusion imaging method with T1 based measurement of the AIF in a single slice. In this preliminary study, our results demonstrate that MBF measured using the proposed method is comparable to the conventional ECG-triggered method.