J Korean Soc Magn Reson Med.  2011 Dec;15(3):191-199. 10.13104/jksmrm.2011.15.3.191.

Simulations of Perfusion Signals of Pulsed Arterial Spin Labeling MRI

• Kim HG
• Jahng GH
• Oh CH

• KMID: 2000047
• DOI: http://doi.org/10.13104/jksmrm.2011.15.3.191

Abstract

PURPOSE
A pulsed arterial spin labeling (PASL) signal usually depends on several parameters. The objective of this study was to determine the optimal parameters using simulation for perfusion signals of PASL magnetic resonance imaging (MRI).
MATERIALS AND METHODS
Perfusion signals, DeltaM/M(0b), derived from the Bloch equation were evaluated in regard to the four most important parameters in PASL MRI: the tissue-to-blood coefficient (lambda), the longitudinal relaxation time of blood (T(1b)), the arterial transit delay from the application of tag (deltat), and the magnetic field strength (B0). The simulation was conducted with Mathematica software.
RESULTS
First, perfusion signals differed depending on the value of lambda in brain tissue. The maximum signal, DeltaM/M(0b) = 0.390, was obtained at an inversion time (TI) = 1.53 sec for gray matter on 3T MRI. Second, perfusion signals were reduced with increasing deltat. The maximum signal, DeltaM/M0b = 0.526, was obtained at TI = 2.1 sec for deltat = 0.5 sec. Finally, perfusion signals increased with increasing B0. The maximum signal, DeltaM = 1.15, was obtained at TI = 1.52 sec for 3T MRI.
CONCLUSION
We reported that the optimized TI values were obtained to provide the highest PASL signals. It is very important that optimized TI values be used to obtain high-quality perfusion signals using PASL MRI.

Keyword

Perfusion; Arterial spin labeling; Bloch equation; Cerebral blood flow

MeSH Terms

Brain
Magnetic Fields
Magnetic Resonance Imaging
Perfusion
Relaxation

Figure

• 

  Fig. 1 Schematic illustration of the labeling of the spins in the arteries (1a) and schematic of the PASL pulse sequence (1b). τ is the duration of the arrival of labeled water molecules at the tissue. δt is the delay of water molecules between arterial labeling and exchange into tissue. TIt is the total labeling delay time, which is the time interval from the center of the labeling radiofrequency pulse and the center of the excitation pulse.

• 

  Fig. 2 Simulation results of the q-factor (2a) and perfusion signals (2b) depended on three different values of tissue-to-blood partition coefficient (λ). Whole brain (Solid line), gray matter (Dotted line), and white matter (Dashed line) Other parameters were used for T1b = 1.6 sec, δt = 0.7 sec, and α = 1 at 3T.

• 

  Fig. 3 Simulation results of the q-factor (3a) and perfusion signals (3b) depended on the longitudinal relaxation time of blood (T1b) T1b at 1.5T (Dotted line), at 3T (Dashed line), and at 7T (Solid line) Other parameters were used for λgm = 1.05 ml/g, δt = 0.7 sec, and α = 1 at 3T. T1b values were 1.4 sec, 1.6 sec, and 2.2 sec, for 1.5T, 3.0T, and 7.0T respectively.

• 

  Fig. 4 Simulation results of the q-factor (4a) and perfusion signals (4b) depended on the arterial transit delay (δt). δt at 0.5 sec (Solid line, Black), at 0.7 sec (Dotted line, Red), and at 0.9 sec (Dashed line, Blue) Other parameters were used for λgm = 1.05 ml/g, T1b = 1.6 sec, and α = 1 at 3T.

• 

  Fig. 5 Simulation results of perfusion signals (5) depended on the strength of the magnetic field (M0b). 1.5T (Solid line), 3T (Dotted line), and 7T (Dashed line) Other parameters were used for λgm = 1.05 ml/g, δt = 0.7 sec, and α = 1. T1b values were 1.4 sec, 1.6 sec, and 2.2 sec, for 1.5T, 3.0T, and 7.0T, respectively.

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