A unified impulse response model for DCE-MRI
Article first published online: 31 JAN 2012
Copyright © 2012 Wiley Periodicals, Inc.
Magnetic Resonance in Medicine
Volume 68, Issue 5, pages 1632–1646, November 2012
How to Cite
Schabel, M. C. (2012), A unified impulse response model for DCE-MRI. Magn Reson Med, 68: 1632–1646. doi: 10.1002/mrm.24162
- Issue published online: 22 OCT 2012
- Article first published online: 31 JAN 2012
- Manuscript Accepted: 21 DEC 2011
- Manuscript Revised: 15 DEC 2011
- Manuscript Received: 11 JUL 2011
- pharmacokinetic modeling;
- perfusion imaging;
- brain tumor
We describe the gamma capillary transit time model, a generalized impulse response model for DCE-MRI that mathematically unifies the Tofts-Kety, extended Tofts-Kety, adiabatic tissue homogeneity, and two-compartment exchange models. By including a parameter (α−1) representing the width of the distribution of capillary transit times within a tissue voxel, the GCTT model discriminates tissues having relatively monodisperse transit time distributions from those having a large degree of heterogeneity. All five models were compared using in vivo data acquired in three brain tumors (one glioblastoma multiforme, one pleomorphic xanthoastrocytoma, and one anaplastic meningioma) and Monte Carlo simulations. Our principal findings are : (1) The four most commonly used models for dynamic contrast-enhanced magnetic resonance imaging can be unified within a single formalism. (2) Application of the GCTT model to in vivo data incurs only modest penalties in parameter uncertainty and computational cost. (3) Measured nonparametric impulse response functions in human brain tumors are well described by the GCTT model. (4) Estimation of α−1 is feasible but achieving statistical significance requires higher SNR than is typically obtained in single voxel dynamic contrast-enhanced magnetic resonance imaging data. These results suggest that the GCTT model may be useful for extraction of information about tumor physiology beyond what is obtained using current modeling methodologies. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.