Magnetic resonance brain perfusion imaging with voxel-specific arterial input functions.
OBJECTIVE
To propose an automatic method for estimating voxel-specific arterial input functions (AIFs) in dynamic contrast brain perfusion imaging.


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 < or = 0.0125) in mean transit time (MTT) and time-to-peak (TTP) in GM compared to WM was seen with the new method.


CONCLUSIONS
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.
Grüner
Renate
R
Department of Biomedicine, University of Bergen, Haukeland University Hospital, N-5021 Bergen, Norway. renate@fmri.no
Bjørnarå
Bård T
BT
Moen
Gunnar
G
Taxt
Torfinn
T
D000328:Adult; D000465:Algorithms; D002560:Cerebrovascular Circulation; D003198:Computer Simulation; D003287:Contrast Media; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009010:Monte Carlo Method; D009413:Nerve Fibers, Myelinated; D036421:Nerve Fibers, Unmyelinated; D018709:Statistics, Nonparametric
D003287:Contrast Media