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. 2013 Feb 20:2013:905279.
doi: 10.1155/2013/905279. eCollection 2013.

Measurement of blood-brain barrier permeability with t1-weighted dynamic contrast-enhanced MRI in brain tumors: a comparative study with two different algorithms

Affiliations

Measurement of blood-brain barrier permeability with t1-weighted dynamic contrast-enhanced MRI in brain tumors: a comparative study with two different algorithms

Maurizio Bergamino et al. ISRN Neurosci. .

Abstract

The purpose of this study was to assess the feasibility of measuring different permeability parameters with T1-weighted dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in order to investigate the blood brain-barrier permeability associated with different brain tumors. The Patlak algorithm and the extended Tofts-Kety model were used to this aim. Twenty-five adult patients with tumors of different histological grades were enrolled in this study. MRI examinations were performed at 1.5 T. Multiflip angle, fast low-angle shot, and axial 3D T1-weighted images were acquired to calculate T1 maps, followed by a DCE acquisition. A region of interest was placed within the tumor of each patient to calculate the mean value of different permeability parameters. Differences in permeability measurements were found between different tumor grades, with higher histological grades characterized by higher permeability values. A significant difference in transfer constant (K (trans)) values was found between the two methods on high-grade tumors; however, both techniques revealed a significant correlation between the histological grade of tumors and their K (trans) values. Our results suggest that DCE acquisition is feasible in patients with brain tumors and that K (trans) maps can be easily obtained by these two algorithms, even if the theoretical model adopted could affect the final results.

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Figures

Figure 1
Figure 1
Image and intensity data from a 69-year old female patient with glioblastoma multiforme (WHO IV). (a) T1-weighted postcontrast image. (b) Relative K trans⁡ map. (c) Signal intensity plot for a region of the tumor and for a portion of healthy brain tissue.
Figure 2
Figure 2
A statistically significant correlation was observed between mean K trans⁡ and tumor grade for both Patlak algorithm ((a): r = 0.54  (P = 0.004)) and for the ETK model ((b): r = 0.58  (P = 0.002)).

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