Embedded Files
Sickle cell disease (SCD) has provided a naturally occurring condition in which to study the reproducibility and variability of ASL measurement and quantification. The fact that in pCASL the labelling efficiency depends on flow-driven adiabatic inversion makes the measurement inherently flow-dependent [Wong 2014]. As such, variability is then also dependent on the variability of arterial flow velocity, which can be dramatically increased in patients with SCD. Labelling efficiency can be simulated to find velocity-specific efficiencies [Maccotta NMR Biomed 1997; Wu 2007 MRM], and the CBF quantification subsequently corrected by phase-contrast MRI measurements of velocity, resulting in velocity-derived labelling efficiency [Vaclavu et al ISMRM 2018]. It should be noted that whether the labelling efficiency is increased or decreased in patients with SCD compared to controls depends on the sequence parameters of the pCASL implementation with respect to the RF pulse and gradients. A more direct method is to measure the labelling efficiency during the pCASL experiment [van Osch 2017]. Due to the higher arterial flow velocities in SCD one can also expect significant reductions in the bolus arrival time [Kawadler 2018; Juttukonda 2017] and correcting for this may further prevent overestimation of CBF in this population. Another source of quantification error arises from differences in B1 inhomogeneities [Bush et al MRI 2018], B0 inhomogeneities and differences in T1 of blood, the latter of which is known to vary with haematocrit [De Vis 2014; Varela 2011]. In patients with SCD, CBF quantification can benefit from using an additionally acquired T1 blood measurement [Vaclavu et al2016].
Lena Vaclavu (lena.vaclavu@gmail.com)
References
References
1. Bush et al "Pseudo continuous arterial spin labeling quantification in anemic subjects with hyperemic cerebral blood flow." Magnetic resonance imaging 47 (2018): 137-146.
2. De Vis et al. "Impact of neonate haematocrit variability on the longitudinal relaxation time of blood: Implications for arterial spin labelling MRI." NeuroImage: Clinical 4 (2014): 517-525.
3. Juttukonda et al. "Cerebral hemodynamics and pseudo‐continuous arterial spin labeling considerations in adults with sickle cell anemia." NMR in Biomedicine 30.2 (2017).
4. Kawadler et al. "Cerebral perfusion characteristics show differences in younger versus older children with sickle cell anaemia: Results from a multiple‐inflow‐time arterial spin labelling study." NMR in Biomedicine 31.6 (2018): e3915.
5. Václavů et al (2018) ISMRM 5530 “Accounting for pCASL labelling efficiency variation in patients with low and high arterial blood flow velocities”.
6. Václavů et al. "In vivo T1 of blood measurements in children with sickle cell disease improve cerebral blood flow quantification from arterial spin-labeling MRI." American Journal of Neuroradiology 37.9 (2016): 1727-1732.
7. van Osch et al. "Advances in arterial spin labelling MRI methods for measuring perfusion and collateral flow." Journal of Cerebral Blood Flow & Metabolism (2017): 0271678X17713434.
8. Varela et al. "A method for rapid in vivo measurement of blood T1." NMR in biomedicine 24.1 (2011): 80-88.
9. Maccotta et al. "The efficiency of adiabatic inversion for perfusion imaging by arterial spin labeling." NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In Vivo 10.4‐5 (1997): 216-221.
10. Wong. "An introduction to ASL labeling techniques." Journal of Magnetic Resonance Imaging 40.1 (2014): 1-10.
11. Wu et al. "A theoretical and experimental investigation of the tagging efficiency of pseudocontinuous arterial spin labeling." Magnetic Resonance in Medicine 58.5 (2007): 1020-1027.
Google Sites
Report abuse