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Pixel-by-Pixel Comparison of Volume Transfer Constant and Estimates of Cerebral Blood Volume from Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast-Enhanced MR Imaging in High-Grade Gliomas
Authors:P. Alcaide-Leon  D. Pareto  E. Martinez-Saez  C. Auger  A. Bharatha  A. Rovira
Affiliation:aFrom the Department of Radiology, MR Unit (P.A.-L., D.P., C.A., A.R.);bDepartment of Pathology (E.M.-S.), Hospital Vall d''Hebron, Barcelona, Spain;cDepartment of Medical Imaging (A.B.), St Michael''s Hospital, Toronto, Ontario, Canada.
Abstract:BACKGROUND AND PURPOSE:Estimates of blood volume and volume transfer constant are parameters commonly used to characterize hemodynamic properties of brain lesions. The purposes of this study were to compare values of volume transfer constant and estimates of blood volume in high-grade gliomas on a pixel-by-pixel basis to comprehend whether they provide different information and to compare estimates of blood volume obtained by dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging.MATERIALS AND METHODS:Thirty-two patients with biopsy-proved grade IV gliomas underwent dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging, and parametric maps of volume transfer constant, plasma volume, and CBV maps were calculated. The Spearman rank correlation coefficients among matching values of CBV, volume transfer constant, and plasma volume were calculated on a pixel-by-pixel basis. Comparison of median values of normalized CBV and plasma volume was performed.RESULTS:Weak-but-significant correlation (P < .001) was noted for all comparisons. Spearman rank correlation coefficients were as follows: volume transfer constant versus CBV, ρ = 0.113; volume transfer constant versus plasma volume, ρ = 0.256; CBV versus plasma volume, ρ = 0.382. We found a statistically significant difference (P < .001) for the estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging (mean normalized plasma volume, 13.89 ± 11.25) and dynamic susceptibility contrast-enhanced MR imaging (mean normalized CBV, 4.37 ± 4.04).CONCLUSIONS:The finding of a very weak correlation between estimates of microvascular density and volume transfer constant suggests that they provide different information. Estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging are significantly higher than those obtained by dynamic susceptibility contrast-enhanced MR imaging in human gliomas, most likely due to the effect of contrast leakage.

Characterization of the hemodynamics of glial tumors by MR perfusion is very relevant because tumor aggressiveness and growth are associated with both endothelial hyperplasia and neovascularization.1The 2 most common MR perfusion techniques used in clinical practice are dynamic susceptibility contrast-enhanced MR imaging (DSC–MR imaging) and dynamic contrast-enhanced MR imaging (DCE–MR imaging).2 CBV is usually calculated from DSC–MR imaging data, while the volume transfer constant (Ktrans) is usually obtained by using DCE–MR imaging. Both CBV and the volume transfer constant have demonstrated good discriminative power in distinguishing low- and high-grade tumors3 and utility in predicting prognosis.46Ktrans is defined as the volume transfer constant between plasma and interstitial space. It is often used as a synonym for permeability, but, as defined by Tofts et al,7 “the measured transfer constant is a potentially intractable combination of flow, permeability, and surface area.” The physiologic significance of Ktrans depends on the balance between capillary permeability and blood flow in the tissue of interest. When permeability is very high, the amount of contrast that leaks out of the vessels depends on the amount of contrast that gets to the capillaries per unit of time. In this situation, Ktrans is equal to the blood plasma flow per unit volume of tissue (Fig 1). In cases of low permeability, the transfer constant equals the permeability surface area product between blood plasma and the extravascular-extracellular space, per unit volume of tissue.Open in a separate windowFig 1.Schematic illustrating flow-limited contrast extravasation. Due to high permeability, the rate of leakage within the voxel depends on the amount of plasma reaching the voxel per unit of time (plasma flow). The venous blood would be “clean” of contrast.In the brain, most cases are surface area product–limited,7 so Ktrans depends on both the leakiness of the vessels and the total surface of leaky capillaries. The problem is that the contribution of each factor to the measured Ktrans is a priori unknown. The transfer constant measured in a voxel may be high due to very leaky vessels, a high number of leaky capillaries within the voxel, or a combination of both (Fig 2).Open in a separate windowFig 2.Schematic illustrating 2 voxels with similar Ktrans values: the first one showing high permeability and low surface area and the second one with low permeability and high surface area.We suggest that within-voxel comparison of blood volume estimates and Ktrans would provide valuable information about physiologic meaning of Ktrans in high-grade gliomas. The correlation between Ktrans and CBV has been previously assessed in gliomas by Law et al.8 Regions with maximal CBV and maximal Ktrans were compared in each tumor to obtain a weak-but-positive correlation. However, they did not compare parameters of the same tumor region because their main goal was to correlate maximal values of the parameters with tumor grade. A similar approach was followed by Provenzale et al.9 They reported a high correlation between CBV and the degree of contrast enhancement, which was defined by the authors as a relative measure of permeability. Again the CBV and Ktrans values used for comparison were obtained from different tumor regions. Results about the correlation between Ktrans and CBV are, therefore, based on indirect methods and are controversial.The purpose of this study was to compare values of Ktrans and CBV in high-grade gliomas on a pixel-by-pixel basis to determine whether they provide different physiologic information. The second aim was to compare estimates of blood volume obtained by DCE–MR imaging and DSC–MR imaging.
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