Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies

Quantitative cerebral blood flow (CBF) values can be obtained from dynamic susceptibility contrast (DSC) MR perfusion studies using the standard singular value decomposition (sSVD) deconvolution algorithm. Reports in the literature from simulation and in vivo studies suggest that CBF estimates obtai...

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Bibliographic Details
Published in:Magnetic resonance in medicine 2004-03, Vol.51 (3), p.631-634
Main Authors: Smith, M.R., Lu, H., Trochet, S., Frayne, R.
Format: Article
Language:English
Subjects:
Algorithms
arterial and tissue perfusion curves delays
blood flow
Brain Ischemia - physiopathology
Cerebrovascular Circulation - physiology
Computer Simulation
Contrast Media
Fourier Analysis
Gadolinium DTPA
Humans
Image Enhancement - methods
Magnetic Resonance Imaging - methods
magnetic resonance perfusion studies
Middle Aged
Models, Theoretical
Phantoms, Imaging
reformulated SVD algorithm
Reproducibility of Results
Sensitivity and Specificity
Stroke - physiopathology
SVD deconvolution artifacts
Time Factors
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Summary:Quantitative cerebral blood flow (CBF) values can be obtained from dynamic susceptibility contrast (DSC) MR perfusion studies using the standard singular value decomposition (sSVD) deconvolution algorithm. Reports in the literature from simulation and in vivo studies suggest that CBF estimates obtained using sSVD deconvolution depend on the arterial‐tissue delay (ATD). By contrast, Fourier transform (FT) deconvolution produces CBF estimates that are independent of ATD. The diagnostic reliability of quantitative CBF measurements to define areas of normal tissue flow and tissue at risk is brought into doubt by such gross sensitivity to the specifics of the deconvolution approach. This variation of CBF values with ATD is shown to be an artifact associated with the current implementation of the sSVD deconvolution algorithm. A reformulated version of the SVD deconvolution algorithm (rSVD) is presented and compared to the standard SVD algorithm through simulation and patient case studies. Magn Reson Med 51:631–634, 2004. © 2004 Wiley‐Liss, Inc.
ISSN:0740-3194
1522-2594
DOI:10.1002/mrm.20006