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Magnetic resonance brain perfusion imaging with voxel‐specific arterial input functions
Author(s) -
Grüner Renate,
Bjørnarå Bård T.,
Moen Gunnar,
Taxt Torfinn
Publication year - 2006
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.20505
Subject(s) - voxel , computer science , perfusion scanning , deconvolution , cerebral blood flow , magnetic resonance imaging , white matter , nuclear medicine , perfusion , artificial intelligence , pattern recognition (psychology) , medicine , radiology , algorithm
Purpose To propose an automatic method for estimating voxel‐specific arterial input functions (AIFs) in dynamic contrast brain perfusion imaging. Materials and Methods Voxel‐specific AIFs were estimated blindly using the theory of homomorphic transformations and complex cepstrum analysis. Wiener filtering was used in the subsequent deconvolution. The method was verified using simulated data and evaluated in 10 healthy adults. Results Computer simulations accurately estimated differently shaped, normalized AIFs. Simple Wiener filtering resulted in underestimation of flow values. Preliminary in vivo results showed comparable cerebral flow value ratios between gray matter (GM) and white matter (WM) when using blindly estimated voxel‐specific AIFs or a single manually selected AIF. Significant differences ( P ≤ 0.0125) in mean transit time (MTT) and time‐to‐peak (TTP) in GM compared to WM was seen with the new method. Conclusion Initial results suggest that the proposed method can replace the tedious and difficult task of manually selecting an AIF, while simultaneously providing better differentiation between time‐dependent hemodynamic parameters. J. Magn. Reson. Imaging 2006. © 2006 Wiley‐Liss, Inc.