Ryan T Woodall1,2, Stephanie L Barnes2, David A Hormuth2, Anna G Sorace3, C Chad Quarles4, Thomas E Yankeelov1,3,2,5. 1. Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, USA. 2. Center for Computational Oncology, Institute for Computational and Engineering Sciences, The University of Texas at Austin, Austin, Texas, USA. 3. Department of Internal Medicine, The University of Texas at Austin, Austin, Texas, USA. 4. Barrow Neurological Institute, Phoenix, Arizona, USA. 5. Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas, USA.
Abstract
PURPOSE: Quantitative evaluation of dynamic contrast enhanced MRI (DCE-MRI) allows for estimating perfusion, vessel permeability, and tissue volume fractions by fitting signal intensity curves to pharmacokinetic models. These compart mental models assume rapid equilibration of contrast agent within each voxel. However, there is increasing evidence that this assumption is violated for small molecular weight gadolinium chelates. To evaluate the error introduced by this invalid assumption, we simulated DCE-MRI experiments with volume fractions computed from entire histological tumor cross-sections obtained from murine studies. METHODS: A 2D finite element model of a diffusion-compensated Tofts-Kety model was developed to simulate dynamic T1 signal intensity data. Digitized histology slices were segmented into vascular (vp ), cellular and extravascular extracellular (ve ) volume fractions. Within this domain, Ktrans (the volume transfer constant) was assigned values from 0 to 0.5 min-1 . A representative signal enhancement curve was then calculated for each imaging voxel and the resulting simulated DCE-MRI data analyzed by the extended Tofts-Kety model. RESULTS: Results indicated parameterization errors of -19.1% ± 10.6% in Ktrans , -4.92% ± 3.86% in ve , and 79.5% ± 16.8% in vp for use of Gd-DTPA over 4 tumor domains. CONCLUSION: These results indicate a need for revising the standard model of DCE-MRI to incorporate a correction for slow diffusion of contrast agent. Magn Reson Med 80:330-340, 2018.
PURPOSE: Quantitative evaluation of dynamic contrast enhanced MRI (DCE-MRI) allows for estimating perfusion, vessel permeability, and tissue volume fractions by fitting signal intensity curves to pharmacokinetic models. These compart mental models assume rapid equilibration of contrast agent within each voxel. However, there is increasing evidence that this assumption is violated for small molecular weight gadolinium chelates. To evaluate the error introduced by this invalid assumption, we simulated DCE-MRI experiments with volume fractions computed from entire histological tumor cross-sections obtained from murine studies. METHODS: A 2D finite element model of a diffusion-compensated Tofts-Kety model was developed to simulate dynamic T1 signal intensity data. Digitized histology slices were segmented into vascular (vp ), cellular and extravascular extracellular (ve ) volume fractions. Within this domain, Ktrans (the volume transfer constant) was assigned values from 0 to 0.5 min-1 . A representative signal enhancement curve was then calculated for each imaging voxel and the resulting simulated DCE-MRI data analyzed by the extended Tofts-Kety model. RESULTS: Results indicated parameterization errors of -19.1% ± 10.6% in Ktrans , -4.92% ± 3.86% in ve , and 79.5% ± 16.8% in vp for use of Gd-DTPA over 4 tumor domains. CONCLUSION: These results indicate a need for revising the standard model of DCE-MRI to incorporate a correction for slow diffusion of contrast agent. Magn Reson Med 80:330-340, 2018.
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