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  4. Walsh-ordered hadamard time-encoded pseudocontinuous ASL (WH pCASL)
 
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2015
Journal Article
Title

Walsh-ordered hadamard time-encoded pseudocontinuous ASL (WH pCASL)

Abstract
PURPOSE: Walsh ordering of Hadamard encoding-matrices and an additional averaging strategy are proposed for Hadamard-encoded pseudocontinuous arterial spin labeling (H-pCASL). In contrast to conventional H-pCASL the proposed method generates more perfusion-weighted images which are accessible already during a running experiment and even from incomplete sets of encoded images. THEORY: Walsh-ordered Hadamard matrices consist of fully decodable Hadamard submatrices. At any time during a measurement these submatrices may yield perfusion-weighted images, even at runtime and with incomplete datasets. The usage of an additional so-called mirrored matrix for averaging leads to more decodable subboli. METHODS: Perfusion-weighted images (five healthy volunteers) are generated using both a Walsh-ordered and a corresponding mirrored Hadamard matrix. To test their correctness they are compared with equivalent images from conventional multi postlabeling-delay (PLD) pCASL-measurements. RESULTS: All predicted perfusion-weighted images could be generated and correlated very well with multi-PLD images. Already small subsets of encoded images, acquired early during the measurement, yielded perfusion-weighted images. The mirrored matrix generates more perfusion-weighted images without time penalty. CONCLUSION: Early access to perfusion-weighted images despite incomplete datasets allows dynamic adaptation of parameters and increases robustness against artifacts. Thus, the approach may be well suited for clinical applications, where pathologies demand rapid parameter adaptation and increase the chance of artifacts. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
Author(s)
Samson-Himmelstjerna, F. von
Madai, V.
Sobesky, J.
Guenther, M.
Journal
Magnetic resonance in medicine  
DOI
10.1002/mrm.26078
Additional link
Full text
Language
English
Fraunhofer-Institut für Digitale Medizin MEVIS  
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