Magnetic resonance brain perfusion imaging with voxel-specific arterial input functions.

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 < or = 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.