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. 2014 Jun;71(6):2206-14.
doi: 10.1002/mrm.24873. Epub 2013 Jul 22.

Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T

Madhava P Aryal  1 , Tavarekere N Nagaraja, Kelly A Keenan, Hassan Bagher-Ebadian, Swayamprava Panda, Stephen L Brown, Glauber Cabral, Joseph D Fenstermacher, James R Ewing
Affiliations

Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T

Madhava P Aryal et al. Magn Reson Med. 2014 Jun.

Abstract

Purpose: To test the hypothesis that a noninvasive dynamic contrast enhanced MRI (DCE-MRI) derived interstitial volume fraction (ve ) and/or distribution volume (VD ) were correlated with tumor cellularity in cerebral tumor.

Methods: T1 -weighted DCE-MRI studies were performed in 18 athymic rats implanted with U251 xenografts. After DCE-MRI, sectioned brain tissues were stained with Hematoxylin and Eosin for cell counting. Using a Standard Model analysis and Logan graphical plot, DCE-MRI image sets during and after the injection of a gadolinium contrast agent were used to estimate the parameters plasma volume (vp ), forward transfer constant (K(trans) ), ve , and VD .

Results: Parameter values in regions where the standard model was selected as the best model were: (mean ± S.D.): vp = (0.81 ± 0.40)%, K(trans) = (2.09 ± 0.65) × 10(-2) min(-1) , ve = (6.65 ± 1.86)%, and VD = (7.21 ± 1.98)%. The Logan-estimated VD was strongly correlated with the standard model's vp + ve (r = 0.91, P < 0.001). The parameters, ve and/or VD , were significantly correlated with tumor cellularity (r ≥ -0.75, P < 0.001 for both).

Conclusion: These data suggest that tumor cellularity can be estimated noninvasively by DCE-MRI, thus supporting its utility in assessing tumor pathophysiology.

Keywords: DCE-MRI; Logan plot; distribution volume; dual-echo gradient-echo sequence; interstitial volume; longitudinal relaxation rate; tumor cellularity.

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Figures

Figure 1
Figure 1
Left: High-resolution post-contrast T1-weighted image. Middle; Corresponding centrally located ADC maps. Right; H&E staining of a centrally located tissue slice approximating the position of the MRI image.
Figure 2
Figure 2
Parametric maps left to right: vp, Ktrans, ve and Model selection. For the Model selection map, white is Model 3 acceptance, dark blue is Model 2 acceptance, light blue is Model 1 acceptance.
Figure 3
Figure 3
Left: H&E-stained tissue slide corresponding to parametric map. Right: Parametric map of ve (only in the model 3 region can ve be calculated). The white box drawn on the detail images shows the ROIs selected for cell count and ve values.
Figure 4
Figure 4
Top: Patlak graphical analysis of the data in the Histo sub-region. The solid line shows the linear fit of the data points; the slope of the line yields the forward transfer constant, Ktrans. Bottom: Logan graphical analysis of the data in the same sub-region. The solid line shows the linear fit of the data in the range 90:150, the slope of the line yields an estimate of distribution volume of about 9%.
Figure 5
Figure 5
Left: Scatter plot of Patlak plot estimates of interstitial volume versus tumor cellularity in the Histo sub-region. The solid line shows the linear fitting of the plot (r = 0.75, p < 0.001). Right: Scatter plot of Logan plot estimates of distribution volume (VD) versus tumor cellularity measured in the Histo sub-region. Solid line shows the linear fitting of the plot (r = 0.76, p < 0.001).
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