The relationship between fractional anisotropy value and tumor microarchitecture in late-stage rat glioma

To explore the magnetic resonance diffusion tensor imaging (MR-DTI) features of in the late stage of Wistar rat C6 brain glioma, and the relationship between fractional anisotropy value and tumor microarchitecture.

The concentration of more than 1.0 × 10⁶/10 μL glioma cells and complete medium were injected stereotactically into the right caudate nucleus of the experimental group (n = 35) and control group (n = 10), respectively. Conventional MRI, DTI, and enhanced T1WI scans were Performed using the GE Signa HD × 3.0T MRI scanner about 3-4 weeks after implantation for the rats. Postprocessing was done using the DTI specific software Function Tool to gain FA image. Many ROIs were drawn avoiding hemorrhage, necrosis areas in tumor parenchyma, the value of FA was recorded. Each surviving rat brain was examined histologically using HE and immunohistochemical staining for VEGF and CD34. Pearson correlation analysis was used to determine the relationships between FA values and VEGF, MVD, cell density, respectively.

A total of 35 tumor-bearing rats were confirmed the tumor formation by the subsequent MRI and pathological examination. The mean FA values of the tumor and the contralateral brain tissue were 0.17 ± 0.03 and 0.31 ± 0.05 respectively, and the difference was statistically significant (t = 12.80, P < 0.05). The mean FA value of grade III glioma (n = 12) was 0.16 ± 0.03, and the average FA value of grade IV glioma (n = 23) was about 0.18 ± 0.04. There was no significant difference between the two groups (t = 1.92, P > 0.05). FA value in the late stage of Wistar rat C6 brain glioma has significant positive correlation to VEGF, MVD, cell density. The correlation coefficients between FA and VEGF, MVD, and cell density were 0.67, 0.65 and 0.71 (P < 0.05), respectively.

The FA value of rat glioma tumor in the late stage can preoperatively provide an accurate, reliable and noninvasive imaging monitoring method to evaluate the microstructure of glioma (cell density, the extent of angiogenesis, fiber bundle integrity and tumor cell infiltration and so on), predict the biological behavior of the tumor and make out surgical plan.