Synopsis
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564-01-016
ISMRM Abstract
Flexible Simulation with GigaBlochs: Investigation of PCASL with Pulsatile Flow
Accepted
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1. Williams DS, Detre JA, Leigh JS, Koretsky AP. Magnetic resonance imaging of perfusion using spin inversion of arterial water. Proceedings of the National Academy of Sciences. 1992 Jan;89(1):212-6. Available from: https://doi.org/10.1073/pnas.89.1.212. [doi]
2. Dai W, Garcia D, de Bazelaire C, Alsop DC. Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magnetic Resonance in Medicine. 2008 Nov;60(6):1488-97. Available from: https://doi.org/10.1002/mrm.21790. [doi]
3. Alsop DC, Detre JA, Golay X, Gunther M, Hendrikse J, Hernandez-Garcia L, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magnetic Resonance in Medicine. 2014 Apr;73(1):102-16. Available from: https://doi.org/10.1002/mrm.25197. [doi]
4. Ferre JC, Bannier E, Raoult H, Mineur G, Carsin-Nicol B, Gauvrit JY. Arterial spin labeling (ASL) perfusion: Techniques and clinical use. Diagnostic and Interventional Imaging. 2013 Dec;94(12):1211-23. Available from: https://doi.org/10.1016/j.diii.2013.06.010. [doi]
5. Taso M, Aramendia-Vidaurreta V, Englund EK, Francis S, Franklin S, Madhuranthakam AJ, et al. Update on state-of-the-art for arterial spin labeling (ASL) human perfusion imaging outside of the brain. Magnetic Resonance in Medicine. 2023 Feb;89(5):1754–1776. Available from: http://dx.doi.org/10.1002/mrm.29609. [doi]
6. Zhao L, Vidorreta M, Soman S, Detre JA, Alsop DC. Improving the robustness of pseudo-continuous arterial spin labeling to off-resonance and pulsatile flow velocity. Magnetic Resonance in Medicine. 2016 Oct;78(4):1342–1351. Available from: http://dx.doi.org/10.1002/mrm.26513. [doi]
7. Castillo-Passi C, Coronado R, Varela-Mattatall G, Alberola-L'opez C, Botnar R, Irarrazaval P. KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration. Magnetic Resonance in Medicine. 2023. Available from: https://doi.org/10.1002/mrm.29635. [doi]
8. Lauzon M. A Beginner’s Guide to Bloch Equation Simulations of Magnetic Resonance Imaging Sequences. arXiv; 2020. Available from: https://doi.org/10.48550/ARXIV.2009.02789. [doi]
9. Garwood M, DelaBarre L. The Return of the Frequency Sweep: Designing Adiabatic Pulses for Contemporary NMR. Journal of Magnetic Resonance. 2001 Dec;153(2):155–177. Available from: http://dx.doi.org/10.1006/jmre.2001.2340. [doi]
10. Okuta R, Unno Y, Nishino D, Hido S, Loomis C. CuPy: A NumPy-Compatible Library for NVIDIA GPU Calculations. In: Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS); 2017. Available from: http://learningsys.org/nips17/assets/papers/paper_16.pdf.
11. Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, et al. Array programming with NumPy. Nature. 2020 Sep;585(7825):357-62. Available from: https://doi.org/10.1038/s41586-020-2649-2. [doi]
12. Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods. 2020 Feb;17(3):261–272. Available from: http://dx.doi.org/10.1038/s41592-019-0686-2. [doi]
13. Holdsworth DW, Norley CJD, Frayne R, Steinman DA, Rutt BK. Characterization of common carotid artery blood-flow waveforms in normal human subjects. Physiological Measurement. 1999 Jan;20(3):219–240. Available from: http://dx.doi.org/10.1088/0967-3334/20/3/301. [doi]
14. Womersley JR. Method for the calculation of velocity, rate of flow and viscous drag in arteries when the pressure gradient is known. The Journal of Physiology. 1955 Mar;127(3):553–563. Available from: http://dx.doi.org/10.1113/jphysiol.1955.sp005276. [doi]
15. Sarrami-Foroushani A, Nasr Esfahany M, Nasiraei Moghaddam A, Saligheh Rad H, Firouznia K, Shakiba M, et al. Velocity Measurement in Carotid Artery: Quantitative Comparison of Time-Resolved 3D Phase-Contrast MRI and Image-based Computational Fluid Dynamics. Iranian Journal of Radiology. 2015 Oct;12(4). Available from: http://dx.doi.org/10.5812/iranjradiol.18286. [doi]
16. Lee W. General principles of carotid Doppler ultrasonography. Ultrasonography. 2013 Dec;33(1):11–17. Available from: http://dx.doi.org/10.14366/usg.13018. [doi]
17. Chung H, Jung YH, Kim KH, Kim JY, Min PK, Yoon YW, et al. Carotid Artery End-Diastolic Velocity and Future Cerebro-Cardiovascular Events in Asymptomatic High Risk Patients. Korean Circulation Journal. 2016;46(1):72. Available from: http://dx.doi.org/10.4070/kcj.2016.46.1.72. [doi]
18. Milner JS, Moore JA, Rutt BK, Steinman DA. Hemodynamics of human carotid artery bifurcations: Computational studies with models reconstructed from magnetic resonance imaging of normal subjects. Journal of Vascular Surgery. 1998 Jul;28(1):143–156. Available from: http://dx.doi.org/10.1016/S0741-5214(98)70210-1. [doi]
19. Chen JJ, Pike GB. Human whole blood T2 relaxometry at 3 Tesla. Magnetic Resonance in Medicine. 2009 Jan;61(2):249–254. Available from: http://dx.doi.org/10.1002/mrm.21858. [doi]
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http://echo.ismrm.org/p/ISMRM2026/564-01-016