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Numerical approximation to the general kinetic model for ASL quantification.

Nam G Lee1, Ahsan Javed2, Terrence R Jao1

  • 1Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.

Magnetic Resonance in Medicine
|May 6, 2020
PubMed
Summary
This summary is machine-generated.

A new numerical approximation enhances arterial spin labeling (ASL) quantification, offering greater flexibility for ASL acquisition methods. This method accurately models pulsed and pseudo-continuous labeling signals, comparable to existing models.

Keywords:
arterial spin labelingblood flowfingerprinting ASLperfusionquantificationsteady-pulsed ASL

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Area of Science:

  • Magnetic Resonance Imaging
  • Biomedical Engineering
  • Quantitative Physiology

Background:

  • Arterial Spin Labeling (ASL) is a crucial technique for non-invasive quantification of tissue perfusion.
  • Existing kinetic models for ASL quantification can be limited in their flexibility for diverse acquisition methods.
  • Developing adaptable numerical approximations is essential for advancing ASL applications.

Purpose of the Study:

  • To develop a flexible numerical approximation for the general kinetic model in arterial spin labeling (ASL) quantification.
  • To enable greater adaptability in ASL acquisition techniques through improved numerical modeling.
  • To provide a robust computational tool for quantitative ASL analysis.

Main Methods:

  • Extended Bloch-McConnell equations to incorporate single-compartment inflow and outflow effects on magnetization.
  • Employed an extension of Jaynes' matrix formalism with piecewise constant approximation for arterial flow and a clearance operator for venous flow.
  • Validated the approximation against the general kinetic model using simulations of pulsed and pseudo-continuous labeling, varying transit times and bolus durations.

Main Results:

  • The numerical approximation demonstrated arbitrary accuracy for pulsed and pseudo-continuous labeling, with errors below 0.05% for a 35 ms timestep.
  • Achieved excellent agreement between the approximation and customized signal expressions for steady-pulsed ASL and MR fingerprinting ASL.
  • Simulations incorporating flow, T2 relaxation, and magnetization transfer revealed increased steady-state signals in balanced SSFP and spoiled gradient-echo sequences.

Conclusions:

  • A novel numerical approximation of the Bloch-McConnell flow equations provides arbitrarily accurate modeling of ASL signals.
  • This approximation offers enhanced flexibility for experimental design in quantitative ASL.
  • The developed method facilitates more adaptable and precise ASL quantification across various imaging sequences.