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Updated: May 15, 2026

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

Published on: May 30, 2011

Perfusion quantification by model-free arterial spin labeling using nonlinear stochastic regularization

André Ahlgren¹, Ronnie Wirestam, Esben Thade Petersen

¹Department of Medical Radiation Physics, Lund University, Lund, Sweden.

Magnetic Resonance in Medicine

|January 3, 2013

Summary

Nonlinear stochastic regularization (NSR) improves cerebral blood flow quantification in model-free arterial spin labeling by providing realistic residue functions, outperforming traditional singular value decomposition (SVD) methods.

Keywords:

arterial spin labeling cerebral blood flow deconvolution

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Area of Science:

Neuroimaging
Medical Physics
Biomedical Engineering

Background:

Model-free arterial spin labeling (ASL) is used for cerebral blood flow (CBF) quantification.
Traditional deconvolution methods like singular value decomposition (SVD) can yield nonphysiological results and are affected by arterial dispersion.

Purpose of the Study:

To implement nonlinear stochastic regularization (NSR) for deconvolution in quantitative STAR labeling of arterial regions (QUASAR) ASL.
To compare NSR with SVD-based methods for residue function characterization and CBF quantification.
To assess the accuracy of NSR in simulations and in vivo.

Main Methods:

NSR deconvolution was applied to QUASAR ASL data from 10 volunteers.
Singular value decomposition (SVD)-based deconvolution (cSVD, oSVD) was used for comparison.
Simulations were conducted to validate in vivo findings.

Main Results:

NSR successfully resolved realistic residue functions, unlike SVD methods.
Mean gray matter CBF estimates were higher with NSR (40.9 ± 3.6 mL/100 g/min) and NSR with dispersion correction (42.9 ± 3.9 mL/100 g/min) compared to cSVD (36.6 ± 2.6) and oSVD (28.6 ± 3.3).
Simulations demonstrated superior accuracy for NSR-based perfusion estimates.

Conclusions:

Cerebral blood flow quantification using model-free ASL is sensitive to the deconvolution method.
NSR offers a feasible and more accurate alternative to SVD-based deconvolution for ASL perfusion quantification.