Assessment of segmental myocardial blood flow and myocardial perfusion reserve by adenosine-stress myocardial arterial spin labeling perfusion imaging

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.

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.

Quantification of Myocardial Perfusion With Vasodilation Using Arterial Spin Labeling at 1.5T

BACKGROUND

Myocardial perfusion is evaluated in first-pass MRI using a gadolinium-based contrast agent, which limits its repeatability and restricts its use in patients with abnormal kidney function. Arterial spin labeling (ASL) is a promising technique for measuring myocardial perfusion without contrast injection. The ratio of stress to rest perfusion, termed myocardial perfusion reserve (MPR), is an indicator of the severity of stenosis in patients with coronary artery disease (CAD).

PURPOSE

To quantify perfusion increases with pharmacological vasodilation, explore MPR differences between segments with and without perfusion defects, and examine the correlations between quantitative ASL and semiquantitative first-pass measurements.

STUDY TYPE

Prospective.

SUBJECTS

Sixteen patients with suspected CAD: 10 classified as "healthy," having normal perfusion on first-pass and no enhancement on late gadolinium enhancement (LGE), and six as "nonhealthy," having hypoperfused segments including ischemic and infarcted.

FIELD STRENGTH/SEQUENCE

Flow-sensitive alternating inversion recovery (FAIR) rest-stress cardiac ASL with balanced steady-state free precession (bSSFP), rest-stress first-pass imaging using gradient-echo and LGE using a phase-sensitive inversion-recovery bSSFP at 1.5T.

ASSESSMENT

For healthy subjects, rest-stress perfusion data were compared in global, coronary artery territory, and segment regions of interest (ROIs). A segmental MPR comparison was performed between normal segments from healthy subjects and abnormal segments from nonhealthy subjects. Correlations between ASL and first-pass parameters were explored.

STATISTICAL TESTS

Wilcoxon-signed-rank test, nonparametric factorial analysis of variance (ANOVA), and Pearson's/Spearman's correlations.

RESULTS

Perfusion increases were significant globally (P = 0.005), per coronary artery territory (P = 0.015), and per segment (P = 0.03 for all segments in ASL and first-pass, except anteroseptal in ASL P = 0.04). MPR differences between normal and abnormal segments were significant (P = 0.0028: ASL, P = 0.033: first-pass). ASL and first-pass measurements were correlated (MPR: r = 0.64, P = 0.008 and perfusion: rho = 0.47, P = 0.007).

DATA CONCLUSION

This study demonstrates the feasibility of ASL to detect hyperemia, the potential to differentiate segments with and without perfusion defects, and significant correlations between ASL and semiquantitative first-pass.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 1.

Practical Guide to Evaluating Myocardial Disease by Cardiac MRI

OBJECTIVE. A spectrum of pathophysiologic mechanisms can lead to the development of myocardial disorders including ischemia, genetic abnormalities, and systemic disorders. Cardiac MRI identifies different myocardial disorders, provides prognostic information, and directs therapy. In comparison with other imaging modalities, cardiac MRI has the advantage of allowing both functional assessment and tissues characterization in a single examination without the use of ionizing radiation. Newer cardiac MRI techniques including mapping can provide additional information about myocardial disease that may not be detected using conventional techniques. Emerging techniques including MR spectroscopy and finger printing will likely change the way we understand the pathophysiology mechanisms of the wide array of myocardial disorders. CONCLUSION. Imaging of myocardial disorders encompasses a large variety of conditions including both ischemic and nonischemic diseases. Cardiac MRI sequences, such as balanced steady-state free precession and late gadolinium enhancement, play a critical role in establishing diagnosis, determining prognosis, and guiding therapeutic management. Additional sequences-including perfusion imaging, T2*, real-time cine, and T2-weighted sequences-should be performed in specific clinical scenarios. There is emerging evidence for the use of mapping in imaging of myocardial disease. Multiple other new techniques are currently being studied. These novel techniques will likely change the way myocardial disorders are understood and diagnosed in the near future.

Accuracy, uncertainty, and adaptability of automatic myocardial ASL segmentation using deep CNN

PURPOSE

To apply deep convolution neural network to the segmentation task in myocardial arterial spin labeled perfusion imaging and to develop methods that measure uncertainty and that adapt the convolution neural network model to a specific false-positive versus false-negative tradeoff.

METHODS

The Monte Carlo dropout U-Net was trained on data from 22 subjects and tested on data from 6 heart transplant recipients. Manual segmentation and regional myocardial blood flow were available for comparison. We consider 2 global uncertainty measures, named "Dice uncertainty" and "Monte Carlo dropout uncertainty," which were calculated with and without the use of manual segmentation, respectively. Tversky loss function with a hyperparameter β was used to adapt the model to a specific false-positive versus false-negative tradeoff.

RESULTS

The Monte Carlo dropout U-Net achieved a Dice coefficient of 0.91 ± 0.04 on the test set. Myocardial blood flow measured using automatic segmentations was highly correlated to that measured using the manual segmentation (R² = 0.96). Dice uncertainty and Monte Carlo dropout uncertainty were in good agreement (R² = 0.64). As β increased, the false-positive rate systematically decreased and false-negative rate systematically increased.

CONCLUSION

We demonstrate the feasibility of deep convolution neural network for automatic segmentation of myocardial arterial spin labeling, with good accuracy. We also introduce 2 simple methods for assessing model uncertainty. Finally, we demonstrate the ability to adapt the convolution neural network model to a specific false-positive versus false-negative tradeoff. These findings are directly relevant to automatic segmentation in quantitative cardiac MRI and are broadly applicable to automatic segmentation problems in diagnostic imaging.

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.

Non-contrast assessment of microvascular integrity using arterial spin labeled cardiovascular magnetic resonance in a porcine model of acute myocardial infarction

BACKGROUND

Following acute myocardial infarction (AMI), microvascular integrity and function may be compromised as a result of microvascular obstruction (MVO) and vasodilator dysfunction. It has been observed that both infarcted and remote myocardial territories may exhibit impaired myocardial blood flow (MBF) patterns associated with an abnormal vasodilator response. Arterial spin labeled (ASL) CMR is a novel non-contrast technique that can quantitatively measure MBF. This study investigates the feasibility of ASL-CMR to assess MVO and vasodilator response in swine.

METHODS

Thirty-one swine were included in this study. Resting ASL-CMR was performed on 24 healthy swine (baseline group). A subset of 13 swine from the baseline group underwent stress ASL-CMR to assess vasodilator response. Fifteen swine were subjected to a 90-min left anterior descending (LAD) coronary artery occlusion followed by reperfusion. Resting ASL-CMR was performed post-AMI at 1-2 days (N = 9, of which 6 were from the baseline group), 1-2 weeks (N = 8, of which 4 were from the day 1-2 group), and 4 weeks (N = 4, of which 2 were from the week 1-2 group). Resting first-pass CMR and late gadolinium enhancement (LGE) were performed post-AMI for reference.

RESULTS

At rest, regional MBF and physiological noise measured from ASL-CMR were 1.08 ± 0.62 and 0.15 ± 0.10 ml/g/min, respectively. Regional MBF increased to 1.47 ± 0.62 ml/g/min with dipyridamole vasodilation (P < 0.001). Significant reduction in MBF was found in the infarcted region 1-2 days, 1-2 weeks, and 4 weeks post-AMI compared to baseline (P < 0.03). This was consistent with perfusion deficit seen on first-pass CMR and with MVO seen on LGE. There were no significant differences between measured MBF in the remote regions pre and post-AMI (P > 0.60).

CONCLUSIONS

ASL-CMR can assess vasodilator response in healthy swine and detect significant reduction in regional MBF at rest following AMI. ASL-CMR is an alternative to gadolinium-based techniques for assessment of MVO and microvascular integrity within infarcted, as well as salvageable and remote myocardium. This has the potential to provide early indications of adverse remodeling processes post-ischemia.