ASL: Beyond CBF
Peiying Liu1

1Johns Hopkins University School of Medicine, United States


This talk will cover advanced ASL-based techniques which provide quantitative measurements of hemodynamic and physiological parameters beyond brain perfusion measured in conventional ASL. Such advances include the implementation of different preparation and acquisitions modules, as well as comprehensive modeling of the signals. With these techniques, new hemodynamic and physiological parameters, including blood oxygenation, tissue transit time, arterial blood volume, vascular compliance, and water permeability of blood-brain barrier, can be obtained.

Target Audience

Research scientists and clinicians interested in learning more about advanced implementations of arterial spin labeling (ASL) that provide information beyond tissue perfusion.


ASL allows for non-invasive evaluation of tissue perfusion using magnetically labeled water spins in the arterial blood as the endogenous tracer (1). Based on this spin-labeling principle, a number of advanced techniques have been developed to obtain more information from the brain MR images than just cerebral blood flow (CBF). In this talk, we will review these new techniques, and describe which new hemodynamic and physiological parameters can be obtained and how they are estimated.

Measurement of blood oxygenation

Measurement of venous oxygenation and the associated quantification of oxygen consumption in the brain are important for the assessment of brain function and tissue viability. Since blood T2 is known to have a calibratable relationship with oxygenation (2), ASL has been combined with blood T2 measurement to provide estimation of blood oxygenation in the brain. In this method, ASL is applied to isolate blood signal and minimize tissue partial voluming. An example is the T2-Relaxation-Under-Spin-Tagging (TRUST) technique, which utilizes the spin-labeling principle on the venous side to separate out pure venous blood signal in a large training vein (3). The venous blood signal is modulated with different T2 weightings, and the monoexponential fitting of the blood signal to the T2-preparation duration then gives the T2 value of the venous blood, which can then be converted to venous oxygenation via a pre-established calibration plot (4). More advanced techniques using velocity-selective spin-labeling in combination with the TRUST-T2 measurement have also been proposed recently (5,6), which allow the mapping of venous oxygenation in the brain.

Measurement of tissue hemodynamics

In conventional multi-delay ASL techniques, arterial transit time (ATT) can be estimated simultaneously with CBF by acquiring multiple PLDs/TIs and fitting the signal to a single-compartment kinetic model (7-10). By combining multi-delay pseudo-continuous ASL (pCASL) with the TRUST-T2 measurement and fitting for the T2 evolution over time, it is possible to distinguish labeled spins within blood vessels from those within tissue compartments due to their different T2 characteristics, which allows the estimation of both arterial and tissue arrival times, as well as arterial cerebral blood volume (CBVa) (11). Schmid et al. further improved the time-efficiency of this method by combining TRUST with time-encoded pseudo-continuous ASL (te-pCASL), which significantly reduced the total scan duration while providing a higher temporal resolution and larger brain coverage (12).

CBVa can also be estimated using ASL with short PLDs (13,14). Other variants of ASL-based CBVa methods have been proposed, including the use of velocity‐selective pulse trains for labeling (15) and the use of multiphase balanced steady state free precession (bSSFP) for acquisition (16). Such ASL-based techniques have also been applied to improve non-contrast-enhanced MR angiography (MRA)(17-19). Furthermore, by combining ASL-based CBVa with systolic and diastolic blood pressure (BP) measurements, vascular compliance (VC), defined as the ratio of changes in CBVa and BP within the cardiac cycle, can also be obtained (20,21).

More recently, a pCASL-based MR fingerprinting technique (MRF-ASL) has also been proposed (22). By taking advantage of the rich information contained in MRF sequence, MRF-ASL provides estimation of up to seven parameters, including B1+, tissueT1, CBF, ATT, pass-through blood ATT, pass-through blood volume, and pass-through blood travel time (22).

Measurement of blood-brain barrier permeability to water

Capillary permeability is an important index of blood-brain barrier (BBB) function. It has been reported that capillary permeability surface area product (PS) can be estimated from conventional multi-delay ASL data using two-compartment models which incorporate both intravascular and extravascular compartments with the PS of the capillary wall characterizing the passage of water between the compartments (23,24). A recently study also showed that PS can be estimated from labeled spins in the venous blood using multi-delay ASL with very long PLDs (25). Other studies have used ASL with multi-echo readout to separate intravascular and extravascular compartments based on their T2 differences, and obtain the exchange time of labeled blood water between the two compartments which can then be converted to PS (26,27). ASL has also been combined with diffusion (28,29) or intra-vascular-incoherent-motion (IVIM)(30,31) to separate intravascular and extravascular signals, which can then give water exchange rate between the two compartments by fitting the signal to a tracer kinetic model.


ASL is currently widely used for mapping brain perfusion. However, new techniques derived from ASL have been shown to provide important information beyond brain perfusion. With these new techniques, we can gain insight into the oxygen consumption in the brain, evaluate tissue transit times, arterial blood volume and vascular compliance, and estimate water permeability of BBB. All these techniques are completely non-invasive and required no contrast agents, and therefore can be done in any patient population without safety concerns.


No acknowledgement found.


1. Alsop DC, Detre JA, Golay X, Gunther M, Hendrikse J, Hernandez-Garcia L, Lu H, MacIntosh BJ, Parkes LM, Smits M, van Osch MJ, Wang DJ, Wong EC, Zaharchuk G. 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. Magn Reson Med 2015;73(1):102-116.

2. van Zijl PC, Eleff SM, Ulatowski JA, Oja JM, Ulug AM, Traystman RJ, Kauppinen RA. Quantitative assessment of blood flow, blood volume and blood oxygenation effects in functional magnetic resonance imaging. Nat Med 1998;4(2):159-167.

3. Lu H, Ge Y. Quantitative evaluation of oxygenation in venous vessels using T2-Relaxation-Under-Spin-Tagging MRI. Magn Reson Med 2008;60(2):357-363.

4. Lu H, Xu F, Grgac K, Liu P, Qin Q, van Zijl P. Calibration and validation of TRUST MRI for the estimation of cerebral blood oxygenation. Magn Reson Med 2012;67(1):42-49.

5. Bolar DS, Rosen BR, Sorensen AG, Adalsteinsson E. QUantitative Imaging of eXtraction of oxygen and TIssue consumption (QUIXOTIC) using venular-targeted velocity-selective spin labeling. Magn Reson Med 2011;66(6):1550-1562.

6. Guo J, Wong EC. Venous oxygenation mapping using velocity-selective excitation and arterial nulling. Magn Reson Med 2012;68(5):1458-1471.

7. Buxton RB, Frank LR, Wong EC, Siewert B, Warach S, Edelman RR. A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magn Reson Med 1998;40(3):383-396.

8. Wang J, Alsop DC, Song HK, Maldjian JA, Tang K, Salvucci AE, Detre JA. Arterial transit time imaging with flow encoding arterial spin tagging (FEAST). Magn Reson Med 2003;50(3):599-607.

9. MacIntosh BJ, Filippini N, Chappell MA, Woolrich MW, Mackay CE, Jezzard P. Assessment of arterial arrival times derived from multiple inversion time pulsed arterial spin labeling MRI. Magn Reson Med 2010;63(3):641-647.

10. Dai W, Shankaranarayanan A, Alsop DC. Volumetric measurement of perfusion and arterial transit delay using hadamard encoded continuous arterial spin labeling. Magn Reson Med 2013;69(4):1014-1022.

11. Liu P, Uh J, Lu H. Determination of spin compartment in arterial spin labeling MRI. Magn Reson Med 2011;65(1):120-127.

12. Schmid S, Teeuwisse WM, Lu H, van Osch MJ. Time-efficient determination of spin compartments by time-encoded pCASL T2-relaxation-under-spin-tagging and its application in hemodynamic characterization of the cerebral border zones. Neuroimage 2015;123:72-79.

13. Chappell MA, MacIntosh BJ, Donahue MJ, Gunther M, Jezzard P, Woolrich MW. Separation of macrovascular signal in multi-inversion time arterial spin labelling MRI. Magn Reson Med 2010;63(5):1357-1365.

14. Whittaker JR, Bright MG, Driver ID, Babic A, Khot S, Murphy K. Changes in arterial cerebral blood volume during lower body negative pressure measured with MRI. Neuroimage 2017.

15. Liu D, Xu F, Lin DD, Zijl PCMv, Qin Q. Quantitative measurement of cerebral blood volume using velocity‐selective pulse trains. Magnetic Resonance in Medicine 2017;77(1):92-101.

16. Yan L, Li C, Kilroy E, Wehrli FW, Wang DJ. Quantification of arterial cerebral blood volume using multiphase-balanced SSFP-based ASL. Magn Reson Med 2012;68(1):130-139.

17. van Osch MJ, Hendrikse J, Golay X, Bakker CJ, van der Grond J. Non-invasive visualization of collateral blood flow patterns of the circle of Willis by dynamic MR angiography. Med Image Anal 2006;10(1):59-70.

18. Yan L, Wang S, Zhuo Y, Wolf RL, Stiefel MF, An J, Ye Y, Zhang Q, Melhem ER, Wang DJ. Unenhanced dynamic MR angiography: high spatial and temporal resolution by using true FISP-based spin tagging with alternating radiofrequency. Radiology 2010;256(1):270-279.

19. Qin Q, Shin T, Schar M, Guo H, Chen H, Qiao Y. Velocity-selective magnetization-prepared non-contrast-enhanced cerebral MR angiography at 3 Tesla: Improved immunity to B0/B1 inhomogeneity. Magn Reson Med 2016;75(3):1232-1241.

20. Warnert EA, Murphy K, Hall JE, Wise RG. Noninvasive assessment of arterial compliance of human cerebral arteries with short inversion time arterial spin labeling. J Cereb Blood Flow Metab 2015;35(3):461-468.

21. Yan L, Liu CY, Smith RX, Jog M, Langham M, Krasileva K, Chen Y, Ringman JM, Wang DJJ. Assessing intracranial vascular compliance using dynamic arterial spin labeling. NeuroImage 2016;124:433-441.

22. Su P, Mao D, Liu P, Li Y, Pinho MC, Welch BG, Lu H. Multiparametric estimation of brain hemodynamics with MR fingerprinting ASL. Magn Reson Med 2017;78(5):1812-1823.

23. Zhou J, Wilson DA, Ulatowski JA, Traystman RJ, van Zijl PC. Two-compartment exchange model for perfusion quantification using arterial spin tagging. J Cereb Blood Flow Metab 2001;21(4):440-455.

24. Parkes LM, Tofts PS. Improved accuracy of human cerebral blood perfusion measurements using arterial spin labeling: accounting for capillary water permeability. Magn Reson Med 2002;48(1):27-41.

25. Lin Z, Li Y, Su P, Mao D, Wei Z, Pillai JJ, Moghekar A, van Osch M, Ge Y, Lu H. Non-contrast MR imaging of blood-brain barrier permeability to water. Magn Reson Med 2018.

26. Gregori J, Schuff N, Kern R, Gunther M. T2-based arterial spin labeling measurements of blood to tissue water transfer in human brain. J Magn Reson Imaging 2013;37(2):332-342.

27. Wells JA, Siow B, Lythgoe MF, Thomas DL. Measuring biexponential transverse relaxation of the ASL signal at 9.4 T to estimate arterial oxygen saturation and the time of exchange of labeled blood water into cortical brain tissue. J Cereb Blood Flow Metab 2013;33(2):215-224.

28. Wang J, Fernandez-Seara MA, Wang S, St Lawrence KS. When perfusion meets diffusion: in vivo measurement of water permeability in human brain. J Cereb Blood Flow Metab 2007;27(4):839-849.

29. Hales PW, Clark CA. Combined arterial spin labeling and diffusion-weighted imaging for noninvasive estimation of capillary volume fraction and permeability-surface product in the human brain. J Cereb Blood Flow Metab 2013;33(1):67-75.

30. Kim T, Kim SG. Quantification of cerebral arterial blood volume using arterial spin labeling with intravoxel incoherent motion-sensitive gradients. Magn Reson Med 2006;55(5):1047-1057.

31. Zhang X, Ingo C, Teeuwisse WM, Chen Z, van Osch MJP. Comparison of perfusion signal acquired by arterial spin labeling-prepared intravoxel incoherent motion (IVIM) MRI and conventional IVIM MRI to unravel the origin of the IVIM signal. Magn Reson Med 2018;79(2):723-729.

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)