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

Comparison of Myocardial Blood Flow Quantification Models for Double ECG Gating Arterial Spin Labeling MRI: Reproducibility Assessment

BACKGROUND

Arterial spin labeling (ASL) allows non-invasive quantification of myocardial blood flow (MBF). Double-ECG gating (DG) ASL is more robust to heart rate variability than single-ECG gating (SG), but its reproducibility requires further investigation. Moreover, the existence of multiple quantification models hinders its application. Frequency-offset-corrected-inversion (FOCI) pulses provide sharper edge profiles than hyperbolic-secant (HS), which could benefit myocardial ASL.

PURPOSE

To assess the performance of MBF quantification models for DG compared to SG ASL, to evaluate their reproducibility and to compare the effects of HS and FOCI pulses.

STUDY TYPE

Prospective.

SUBJECTS

Sixteen subjects (27 ± 8 years).

FIELD STRENGTH/SEQUENCE

1.5 T/DG and SG flow-sensitive alternating inversion recovery ASL.

ASSESSMENT

Three models for DG MBF quantification were compared using Monte Carlo simulations and in vivo experiments. Two models used a fitting approach (one using only a single label and control image pair per fit, the other using all available image pairs), while the third model used a T1 correction approach. Slice profile simulations were conducted for HS and FOCI pulses with varying B0 and B1. Temporal signal-to-noise ratio (tSNR) was computed for different acquisition/quantification strategies and inversion pulses. The number of images that minimized MBF error was investigated in the model with highest tSNR. Intra and intersession reproducibility were assessed in 10 subjects.

STATISTICAL TESTS

Within-subject coefficient of variation, analysis of variance. P-value <0.05 was considered significant.

RESULTS

MBF was not different across acquisition/quantification strategies (P = 0.27) nor pulses (P = 0.9). DG MBF quantification models exhibited significantly higher tSNR and superior reproducibility, particularly for the fitting model using multiple images (tSNR was 3.46 ± 2.18 in vivo and 3.32 ± 1.16 in simulations, respectively; wsCV = 16%). Reducing the number of ASL pairs to 13/15 did not increase MBF error (minimum = 0.22 mL/g/min).

DATA CONCLUSION

Reproducibility of MBF was better for DG than SG acquisitions, especially when employing a fitting model.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Update on state-of-the-art for arterial spin labeling (ASL) human perfusion imaging outside of the brain

This review article provides an overview of developments for arterial spin labeling (ASL) perfusion imaging in the body (i.e., outside of the brain). It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. In this review, we focus on specific challenges and developments tailored for ASL in a variety of body locations. After presenting common challenges, organ-specific reviews of challenges and developments are presented, including kidneys, lungs, heart (myocardium), placenta, eye (retina), liver, pancreas, and muscle, which are regions that have seen the most developments outside of the brain. Summaries and recommendations of acquisition parameters (when appropriate) are provided for each organ. We then explore the possibilities for wider adoption of body ASL based on large standardization efforts, as well as the potential opportunities based on recent advances in high/low-field systems and machine-learning. This review seeks to provide an overview of the current state-of-the-art of ASL for applications in the body, highlighting ongoing challenges and solutions that aim to enable more widespread use of the technique in clinical practice.

3D model-based super-resolution motion-corrected cardiac T1 mapping

Objective. To provide 3D high-resolution cardiac T1 maps using model-based super-resolution reconstruction (SRR).Approach. Due to signal-to-noise ratio limitations and the motion of the heart during imaging, often 2D T1 maps with only low through-plane resolution (i.e. slice thickness of 6-8 mm) can be obtained. Here, a model-based SRR approach is presented, which combines multiple stacks of 2D acquisitions with 6-8 mm slice thickness and generates 3D high-resolution T1 maps with a slice thickness of 1.5-2 mm. Every stack was acquired in a different breath hold (BH) and any misalignment between BH was corrected retrospectively. The novelty of the proposed approach is the BH correction and the application of model-based SRR on cardiac T1 Mapping. The proposed approach was evaluated in numerical simulations and phantom experiments and demonstrated in four healthy subjects.Main results. Alignment of BH states was essential for SRR even in healthy volunteers. In simulations, respiratory motion could be estimated with an RMS error of 0.18 ± 0.28 mm. SRR improved the visualization of small structures. High accuracy and precision (average standard deviation of 69.62 ms) of the T1 values was ensured by SRR while the detectability of small structures increased by 40%.Significance. The proposed SRR approach provided T1 maps with high in-plane and high through-plane resolution (1.3 × 1.3 × 1.5-2 mm³). The approach led to improvements in the visualization of small structures and precise T1 values.

Reduction of motion effects in myocardial arterial spin labeling

PURPOSE

To evaluate the accuracy and reproducibility of myocardial blood flow measurements obtained under different breathing strategies and motion correction techniques with arterial spin labeling.

METHODS

A prospective cardiac arterial spin labeling study was performed in 12 volunteers at 3 Tesla. Perfusion images were acquired twice under breath-hold, synchronized-breathing, and free-breathing. Motion detection based on the temporal intensity variation of a myocardial voxel, as well as image registration based on pairwise and groupwise approaches, were applied and evaluated in synthetic and in vivo data. A region of interest was drawn over the mean perfusion-weighted image for quantification. Original breath-hold datasets, analyzed with individual regions of interest for each perfusion-weighted image, were considered as reference values.

RESULTS

Perfusion measurements in the reference breath-hold datasets were in line with those reported in literature. In original datasets, prior to motion correction, myocardial blood flow quantification was significantly overestimated due to contamination of the myocardial perfusion with the high intensity signal of blood pool. These effects were minimized with motion detection or registration. Synthetic data showed that accuracy of the perfusion measurements was higher with the use of registration, in particular after the pairwise approach, which probed to be more robust to motion.

CONCLUSION

Satisfactory results were obtained for the free-breathing strategy after pairwise registration, with higher accuracy and robustness (in synthetic datasets) and higher intrasession reproducibility together with lower myocardial blood flow variability across subjects (in in vivo datasets). Breath-hold and synchronized-breathing after motion correction provided similar results, but these breathing strategies can be difficult to perform by patients.

Myocardial arterial spin labeling in systole and diastole using flow-sensitive alternating inversion recovery with parallel imaging and compressed sensing

Quantitative myocardial perfusion can be achieved without contrast agents using flow-sensitive alternating inversion recovery (FAIR) arterial spin labeling. However, FAIR has an intrinsically low sensitivity, which may be improved by mitigating the effects of physiological noise or by increasing the area of artifact-free myocardium. The aim of this study was to investigate if systolic FAIR may increase the amount of analyzable myocardium compared with diastolic FAIR and its effect on physiological noise. Furthermore, we compare parallel imaging acceleration with a factor of 2 with compressed sensing acceleration with a factor of 3 for systolic FAIR. Twelve healthy subjects were scanned during rest on a 3 T scanner using diastolic FAIR with parallel imaging factor 2 (FAIR-PI2_D ), systolic FAIR with the same acceleration (FAIR-PI2_S ) and systolic FAIR with compressed sensing factor 3 (FAIR-CS3_S ). The number of analyzable pixels in the myocardium, temporal signal-to-noise ratio (TSNR) and mean myocardial blood flow (MBF) were calculated for all methods. The number of analyzable pixels using FAIR-CS3_S (663 ± 55) and FAIR-PI2_S (671 ± 58) was significantly higher than for FAIR-PI2_D (507 ± 82; P = .001 for both), while there was no significant difference between FAIR-PI2_S and FAIR-CS3_S . The mean TSNR of the midventricular slice for FAIR-PI2_D was 11.4 ± 3.9, similar to that of FAIR-CS3_S, which was 11.0 ± 3.3, both considerably higher than for FAIR-PI2_S, which was 8.4 ± 3.1 (P < .05 for both). Mean MBF was similar for all three methods. The use of compressed sensing accelerated systolic FAIR benefits from an increased number of analyzable myocardial pixels compared with diastolic FAIR without suffering from a TSNR penalty, unlike systolic FAIR with parallel imaging acceleration.

FASt single-breathhold 2D multislice myocardial T1 mapping (FAST1) at 1.5T for full left ventricular coverage in three breathholds

Background

Conventional myocardial T₁ mapping techniques such as modified Look–Locker inversion recovery (MOLLI) generate one T₁ map per breathhold. T₁ mapping with full left ventricular coverage may be desirable when spatial T₁ variations are expected. This would require multiple breathholds, increasing patient discomfort and prolonging scan time.

Purpose

To develop and characterize a novel FASt single‐breathhold 2D multislice myocardial T₁ mapping (FAST1) technique for full left ventricular coverage.

Study Type

Prospective.

Population/Phantom

Numerical simulation, agarose/NiCl₂ phantom, 9 healthy volunteers, and 17 patients.

Field Strength/Sequence

1.5T/FAST1.

Assessment

Two FAST1 approaches, FAST1‐BS and FAST1‐IR, were characterized and compared with standard 5‐(3)‐3 MOLLI in terms of accuracy, precision/spatial variability, and repeatability.

Statistical Tests

Kruskal‐Wallis, Wilcoxon signed rank tests, intraclass correlation coefficient analysis, analysis of variance, Student's t‐tests, Pearson correlation analysis, and Bland–Altman analysis.

Results

In simulation/phantom, FAST1‐BS, FAST1‐IR, and MOLLI had an accuracy (expressed as T₁ error) of 0.2%/4%, 6%/9%, and 4%/7%, respectively, while FAST1‐BS and FAST1‐IR had a precision penalty of 1.7/1.5 and 1.5/1.4 in comparison with MOLLI, respectively. In healthy volunteers, FAST1‐BS/FAST1‐IR/MOLLI led to different native myocardial T₁ times (1016 ± 27 msec/952 ±22 msec/987 ± 23 msec, P < 0.0001) and spatial variability (66 ± 10 msec/57 ± 8 msec/46 ± 7 msec, P < 0.001). There were no statistically significant differences between all techniques for T₁ repeatability (P = 0.18). In vivo native and postcontrast myocardial T₁ times in both healthy volunteers and patients using FAST1‐BS/FAST1‐IR were highly correlated with MOLLI (Pearson correlation coefficient ≥0.93).

Data Conclusion

FAST1 enables myocardial T₁ mapping with full left ventricular coverage in three separated breathholds. In comparison with MOLLI, FAST1 yield a 5‐fold increase of spatial coverage, limited penalty of T₁ precision/spatial variability, no significant difference of T₁ repeatability, and highly correlated T₁ times. FAST1‐IR provides improved T₁ precision/spatial variability but reduced accuracy when compared with FAST1‐BS.

Level of Evidence: 1

Technical Efficacy: Stage 3

J. Magn. Reson. Imaging 2020;51:492–504.

Optimal repetition time for free breathing myocardial arterial spin labeling

The aim of this study was to improve the scan efficiency of ASL in the myocardium. Free breathing FAIR-ASL scans with different TRs were compared, while keeping the acquisition time constant. Scans were named by the trigger pulse that started each acquisition: every two (TP1), four (TP2) and six (TP3) cardiac cycles. TP2 offered the best alternative with a coefficient of variation of 17.15% intrasession and 36.85% intersession. Mean MBF increased by 0.22 ± 0.41 ml/g/min with mild stress.

Fully automated, inline quantification of myocardial blood flow with cardiovascular magnetic resonance: repeatability of measurements in healthy subjects

BACKGROUND

Non-invasive assessment of myocardial ischaemia is a cornerstone of the diagnosis of coronary artery disease. Measurement of myocardial blood flow (MBF) using positron emission tomography (PET) is the current reference standard for non-invasive quantification of myocardial ischaemia. Dynamic myocardial perfusion cardiovascular magnetic resonance (CMR) offers an alternative to PET and a recently developed method with automated inline perfusion mapping has shown good correlation of MBF values between CMR and PET. This study assessed the repeatability of myocardial perfusion mapping by CMR in healthy subjects.

METHODS

Forty-two healthy subjects were recruited and underwent adenosine stress and rest perfusion CMR on two visits. Scans were repeated with a minimum interval of 7 days. Intrastudy rest and stress MBF repeatability were assessed with a 15-min interval between acquisitions. Interstudy rest and stress MBF and myocardial perfusion reserve (MPR) were measured for global myocardium and regionally for coronary territories and slices.

RESULTS

There was no significant difference in intrastudy repeated global rest MBF (0.65 ± 0.13 ml/g/min vs 0.62 ± 0.12 ml/g/min, p = 0.24, repeatability coefficient (RC) =24%) or stress (2.89 ± 0.56 ml/g/min vs 2.83 ± 0.64 ml/g/min, p = 0.41, RC = 29%) MBF. No significant difference was seen in interstudy repeatability for global rest MBF (0.64 ± 0.13 ml/g/min vs 0.64 ± 0.15 ml/g/min, p = 0.80, RC = 32%), stress MBF (2.71 ± 0.61 ml/g/min vs 2.55 ± 0.57 ml/g/min, p = 0.12, RC = 33%) or MPR (4.24 ± 0.69 vs 3.73 ± 0.76, p = 0.25, RC = 36%). Regional repeatability was good for stress (RC = 30-37%) and rest MBF (RC = 32-36%) but poorer for MPR (RC = 35-43%). Within subject coefficient of variation was 8% for rest and 11% for stress within the same study, and 11% for rest and 12% for stress between studies.

CONCLUSIONS

Fully automated, inline, myocardial perfusion mapping by CMR shows good repeatability that is similar to the published PET literature. Both rest and stress MBF show better repeatability than MPR, particularly in regional analysis.

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.