Quantification of blood–brain barrier water exchange and permeability with multidelay diffusion-weighted pseudo-continuous arterial spin labeling
Corresponding Author
Xingfeng Shao
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Correspondence
Xingfeng Shao, Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Email: [email protected]
Search for more papers by this authorChenyang Zhao
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorQinyang Shou
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorKeith S. St Lawrence
Lawson Health Research Institute, London, Ontario, Canada
Department of Medical Biophysics, Western University, London, Ontario, Canada
Search for more papers by this authorDanny J. J. Wang
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorCorresponding Author
Xingfeng Shao
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Correspondence
Xingfeng Shao, Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Email: [email protected]
Search for more papers by this authorChenyang Zhao
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorQinyang Shou
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorKeith S. St Lawrence
Lawson Health Research Institute, London, Ontario, Canada
Department of Medical Biophysics, Western University, London, Ontario, Canada
Search for more papers by this authorDanny J. J. Wang
Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
Search for more papers by this authorClick here for author-reader discussions
Funding information: National Institute of Health (NIH), Grant/Award Numbers: R01-EB028297, R01-NS114382, UF1-NS100614
Abstract
Purpose
To present a pulse sequence and mathematical models for quantification of blood–brain barrier water exchange and permeability.
Methods
Motion-compensated diffusion-weighted (MCDW) gradient-and-spin echo (GRASE) pseudo-continuous arterial spin labeling (pCASL) sequence was proposed to acquire intravascular/extravascular perfusion signals from five postlabeling delays (PLDs, 1590–2790 ms). Experiments were performed on 11 healthy subjects at 3 T. A comprehensive set of perfusion and permeability parameters including cerebral blood flow (CBF), capillary transit time (τc), and water exchange rate (kw) were quantified, and permeability surface area product (PSw), total extraction fraction (Ew), and capillary volume (Vc) were derived simultaneously by a three-compartment single-pass approximation (SPA) model on group-averaged data. With information (i.e., Vc and τc) obtained from three-compartment SPA modeling, a simplified linear regression of logarithm (LRL) approach was proposed for individual kw quantification, and Ew and PSw can be estimated from long PLD (2490/2790 ms) signals. MCDW-pCASL was compared with a previously developed diffusion-prepared (DP) pCASL sequence, which calculates kw by a two-compartment SPA model from PLD = 1800 ms signals, to evaluate the improvements.
Results
Using three-compartment SPA modeling, group-averaged CBF = 51.5/36.8 ml/100 g/min, kw = 126.3/106.7 min−1, PSw = 151.6/93.8 ml/100 g/min, Ew = 94.7/92.2%, τc = 1409.2/1431.8 ms, and Vc = 1.2/0.9 ml/100 g in gray/white matter, respectively. Temporal SNR of MCDW-pCASL perfusion signals increased 3-fold, and individual kw maps calculated by the LRL method achieved higher spatial resolution (3.5 mm3 isotropic) as compared with DP pCASL (3.5 × 3.5 × 8 mm3).
Conclusion
MCDW-pCASL allows visualization of intravascular/extravascular ASL signals across multiple PLDs. The three-compartment SPA model provides a comprehensive measurement of blood–brain barrier water dynamics from group-averaged data, and a simplified LRL method was proposed for individual kw quantification.
Supporting Information
| Filename | Description |
|---|---|
| mrm29581-sup-0001-Supinfo.docxWord 2007 document , 6.3 MB | Figure S1. Reconstruction results from one representative subject (Female, 25 years old). 36 and 12 slices were acquired by the proposed MCDW-pCASL and DP-pCASL, respectively. A and B show CBF and kw maps obtained from the MCDW-pCASL LRL (top) and DP-pCASL (bottom) techniques. C and D show Ew and PSw maps obtained from the proposed technique. E shows the ATT map obtained from DP-pCASL. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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