Three-dimensional whole-brain perfusion quantification using pseudo-continuous arterial spin labeling MRI at multiple post-labeling delays: Accounting for both arterial transit time and impulse response function

Research output: Contribution to journalArticle

Abstract

Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T1,eff. The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T1,eff values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T1,eff and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46±14 mL/100 g/min) and ATT (1.4±0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T1,eff values (1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.

Original languageEnglish (US)
Pages (from-to)116-128
Number of pages13
JournalNMR in Biomedicine
Volume27
Issue number2
DOIs
StatePublished - Feb 2014

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Cerebrovascular Circulation
Impulse response
Magnetic resonance imaging
Labeling
Brain
Statistical Models
Perfusion
Blood
Healthy Volunteers
Tissue
Kinetics

Keywords

  • Arterial transit time
  • Brain
  • Cerebral blood flow
  • Clinical
  • GRASE
  • Human
  • Impulse response function
  • PCASL

ASJC Scopus subject areas

  • Spectroscopy
  • Molecular Medicine
  • Radiology Nuclear Medicine and imaging

Cite this

@article{067bb04cf6b140bfa9fbe19d16df2ef7,
title = "Three-dimensional whole-brain perfusion quantification using pseudo-continuous arterial spin labeling MRI at multiple post-labeling delays: Accounting for both arterial transit time and impulse response function",
abstract = "Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T1,eff. The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T1,eff values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T1,eff and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46±14 mL/100 g/min) and ATT (1.4±0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T1,eff values (1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.",
keywords = "Arterial transit time, Brain, Cerebral blood flow, Clinical, GRASE, Human, Impulse response function, PCASL",
author = "Qin Qin and Huang, {Alan J.} and Jun Hua and John Desmond and Stevens, {Robert David} and {Van Zijl}, {Peter C}",
year = "2014",
month = "2",
doi = "10.1002/nbm.3040",
language = "English (US)",
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pages = "116--128",
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T1 - Three-dimensional whole-brain perfusion quantification using pseudo-continuous arterial spin labeling MRI at multiple post-labeling delays

T2 - Accounting for both arterial transit time and impulse response function

AU - Qin, Qin

AU - Huang, Alan J.

AU - Hua, Jun

AU - Desmond, John

AU - Stevens, Robert David

AU - Van Zijl, Peter C

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N2 - Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T1,eff. The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T1,eff values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T1,eff and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46±14 mL/100 g/min) and ATT (1.4±0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T1,eff values (1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.

AB - Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective impulse response function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T1,eff. The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T1,eff values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T1,eff and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46±14 mL/100 g/min) and ATT (1.4±0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T1,eff values (1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.

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KW - Impulse response function

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