Positron emission tomography elucidates transport system and tumor proliferation in meningiomas
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- Published online on: October 1, 2005 https://doi.org/10.3892/or.14.4.853
- Pages: 853-859
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Abstract
To test the in vivo transport system and tumor proliferation of meningiomas, in comparison with gliomas, 25 patients with meningiomas and 8 gliomas underwent quantitative kinetic analysis of [18F]fluoro-2-deoxy-D-glucose (FDG) - positron emission tomography (PET) imaging and immunohistochemical study. Kinetic analysis was obtained by calculation of the rate constants: K1 (ml/g/min), which represents the transport of FDG from plasma to tissue; k2 (min-1), which demonstrates the transport back from tissue to plasma; and k3 (min-1), an indicator of glucose metabolism, using Gjedde's plot methods in a three-compartment model. Surgical specimens were evaluated by means of three different methods: i) immunoreactivity to vascular endothelial growth factor (VEGF) and glucose transporter-1 (Glut-1), representing the permeability of tumor vessels; ii) immunostaining for von Willebrand Factor (vWF), reflecting vascular surface areas of arterioles; and iii) the MIB-1 labeling index (MIB-1 LI), representing the proliferative potential. K1 was higher in meningiomas than in gliomas and was higher in atypical than in benign meningiomas. k3 was correlated with MIB-1 LI in meningiomas, but not in gliomas. Immunohistochemically, meningiomas were less reactive to VEGF or Glut-1 than gliomas but atypical meningiomas stained more intensely than benign meningiomas. The vascular surface area was significantly larger in meningiomas than in gliomas and atypical meningiomas had high values for both permeability and surface area than benign meningiomas. High values for K1 and k3 indicate the aggressive proliferation of meningiomas and, in atypical meningiomas, the synergistic interaction of the high permeability and the large surface area yielded conditions conducive to glucose metabolism and tumor proliferation. Evaluation of K1 and k3 facilitates to predict the tumor aggressiveness and to optimize the surgical management.