Quantitative in vivo imaging of tissue factor expression in glioma using dynamic contrast-enhanced MRI derived...

Tissue Factor (TF) has been well established in angiogenesis, invasion, metastasis, and prognosis in glioma. A noninvasive assessment of TF expression status in glioma is therefore of obvious clinical relevance. Dynamic contrast-enhanced (DCE) MRI parameters have been used to evaluate microvascular characteristics and predict molecular expression status in tumors. Our aim is to investigate whether quantitative DCE-MRI parameters could assess TF expression in glioma.

Thirty-two patients with histopathologically diagnosed supratentorial glioma who underwent DCE-MRI were retrospectively recruited. Extended Tofts linear model was used for DCE-MRI post-processing. Hot-spot, whole tumor cross-sectional approaches, and histogram were used for analysis of model based parameters. Four serial paraffin sections of each case were stained with TF, CD105, CD34 and α-Sooth Muscle Actin, respectively for evaluating the association of TF and microvascular properties. Pearson correlation was performed between percentage of TF expression area and DCE-MRI parameters, multiple microvascular indexes.

Volume transfer constant (K^trans) hot-spot value best correlated with TF (r=0.886, p<0.001), followed by 90th percentile K^trans value (r=0.801, p<0.001). Moreover, histogram analysis of K^trans value demonstrated that weak TF expression was associated with less heterogeneous and positively skewed distribution. Finally, pathology analysis revealed TF was associated with glioma grade and significantly correlated with these two dynamic angiogenic indexes which could be used to explain the strong correlation between K^trans and TF expression.

Our results indicate that K^trans may serve as a potential clinical imaging biomarker to predict TF expression status preoperatively in gliomas.