With the publication in 2015 of the consensus statement by the perfusion study group of the International Society for Magnetic Resonance in Medicine (ISMRM) and the EU-COST action ‘ASL in dementia’ on the implementation of arterial spin labelling MRI (ASL) in a clinical setting, the development of ASL can be considered to have become mature and ready for clinical prime-time. In this review article new developments and remaining issues will be discussed, especially focusing on quantification of ASL as well as on new technological developments of ASL for perfusion imaging and flow territory mapping. Uncertainty of the achieved labelling efficiency in pseudo-continuous ASL (pCASL) as well as the presence of arterial transit time artefacts, can be considered the main remaining challenges for the use of quantitative cerebral blood flow (CBF) values. New developments in ASL centre around time-efficient acquisition of dynamic ASL-images by means of time-encoded pCASL and diversification of information content, for example by combined 4D-angiography with perfusion imaging. Current vessel-encoded and super-selective pCASL-methodology have developed into easily applied flow-territory mapping methods providing relevant clinical information with highly similar information content as digital subtraction angiography (DSA), the current clinical standard. Both approaches seem therefore to be ready for clinical use.
The optimized labeling efficiency sequence provides robust artery-specific labeling efficiency measurement within a short acquisition time (∼30 s), thereby enabling improved accuracy of pCASL CBF quantification. Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
BackgroundThis study demonstrates a three-dimensional (3D) free-breathing native myocardial T1 mapping sequence at 3 T.MethodsThe proposed sequence acquires three differently T1-weighted volumes. The first two volumes receive a saturation pre-pulse with different recovery time. The third volume is acquired without magnetization preparation and after a significant recovery time. Respiratory navigator gating and volume-interleaved acquisition are adopted to mitigate misregistration. The proposed sequence was validated through simulation, phantom experiments and in vivo experiments in 12 healthy adult subjects.ResultsIn phantoms, good agreement on T1 measurement was achieved between the proposed sequence and the reference inversion recovery spin echo sequence (R2 = 0.99). Homogeneous 3D T1 maps were obtained from healthy adult subjects, with a T1 value of 1476 ± 53 ms and a coefficient of variation (CV) of 6.1 ± 1.4% over the whole left-ventricular myocardium. The averaged septal T1 was 1512 ± 60 ms with a CV of 2.1 ± 0.5%.ConclusionFree-breathing 3D native T1 mapping at 3 T is feasible and may be applicable in myocardial assessment. The proposed 3D T1 mapping sequence is suitable for applications in which larger coverage is desired beyond that available with single-shot parametric mapping, or breath-holding is unfeasible.Electronic supplementary materialThe online version of this article (10.1186/s12968-018-0487-2) contains supplementary material, which is available to authorized users.
Purpose: To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF-ASL) perfusion maps using deep learning. Method: A fully connected neural network, denoted as DeepMARS, was trained using simulation data and added Gaussian noise. Two MRF-ASL models were used to generate the simulation data, specifically a single-compartment model with 4 unknowns parameters and a two-compartment model with 7 unknown parameters. The DeepMARS method was evaluated using MRF-ASL data from healthy subjects (N = 7) and patients with Moymoya disease (N = 3). Computation time, coefficient of determination (R 2 ), and intraclass correlation coefficient (ICC) were compared between DeepMARS and conventional dictionary matching (DM). The relationship between DeepMARS and Look-Locker PASL was evaluated by a linear mixed model. Results: Computation time per voxel was <0.5 ms for DeepMARS and >4 seconds for DM in the single-compartment model. Compared with DM, the DeepMARS showed higher R 2 and significantly improved ICC for single-compartment derived bolus arrival time (BAT) and two-compartment derived cerebral blood flow (CBF) and higher or similar R 2 /ICC for other parameters. In addition, the DeepMARS was significantly correlated with Look-Locker PASL for BAT (single-compartment) and CBF (two-compartment). Moreover, for Moyamoya patients, the location of diminished CBF and prolonged BAT shown in DeepMARS was consistent with the position of occluded arteries shown in time-of-flight MR angiography. Conclusion: Reconstruction of MRF-ASL with DeepMARS is faster and more reproducible than DM. K E Y W O R D S deep learning, DeepMARS, MRF-ASL, reconstruction, reproducibility | 1025 ZHANG et Al.
Purpose: The aim of this study was to develop, test and validate a 3D free‐breathing technique for simultaneous measurement of native myocardial T1 and T2. Methods: The proposed 3D technique acquires five fat‐suppressed electrocardiogram‐triggered respiratory navigator‐gated spoiled gradient echo volumes in an interleaved manner. Four volumes are prepared using a combination of nonselective saturation and T2 preparation. One volume is acquired with fully recovered longitudinal magnetization for accuracy during parametric fitting. Performance of the technique was validated through numerical simulations, phantom experiments and in vivo experiments in 15 healthy human subjects. Results: Simulations and phantom experiments show that the measured T1 and T2 are largely insensitive to heart rate. In vivo whole‐heart maps with a voxel size of 1.5 × 1.5 × 16 mm3 were acquired without parallel imaging within ~ 8 min including respiratory gating efficiency. The in vivo parametric maps were homogeneous (coefficients of variation of left ventricle myocardium were 6.0% ± 0.8% and 10.2% ± 3.4% for T1 and T2 maps, respectively), with an average T1 value of 1470 ± 59.2 ms and T2 value of 41.6 ± 1.8 ms Conclusions: The proposed 3D technique allows for measurement of whole‐heart T1 and T2 with preserved accuracy and precision in a single scan.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.