The Research And Application Of Kinetic Analysis Of Two-compartment Model Of DCE-MRI In Brain Glioma

PART Ⅰ:Qualitative Assessment of Glioma Grading by DCE-MRI based on Kinetic Analysis of Two-Compartment ModelPurpose:To evaluate the significance of the parameters (including Ktrans, Ve and Kep) of the kinetic analysis of two-compartment model of DCE-MRI in grading of brain glioma.Materials and Methods:DCE-MRI was preoperatively performed at3. OT MR in71patients(42males,29females; age range,13-74; mean age,44.6years), including31low grade gliomas(LGG:grade Ⅱ) and40high grade gliomas(HGG:grade Ⅲ8and Ⅳ32). The maps of Ktrans, Ve and Kep were acquired by analyzing the imaging data with the two-compartment model. The values of Ktrans, Ve and Kep were measured on the regions of highest signals in the maps. Statistical analysis of the parameters was performed using ANOVA and t test across histologically defined glioma grades (when the data sets compiled with the conditions of normality and equal varianc); otherwise, statistical analysis of the parameters was performed using kruskal-wallis test and Mann-Whitney U test. Furthermore, the Spearman correlation coefficient was determined between the parameters and glioma grades. Finally, cutoff values of Ktrans, Ve and Kep for distinguishing across histologically defined glioma grades were determined by receiver operator characteristic (ROC) curve analysis. Sensitivity and specificity were reported for the optimal thresholds. A P value of less than0.05was considered statistically significant.Results:The differences in Ktrans, Ve and Kep were statistically significant between grade Ⅱ and Ⅲ, grade Ⅱ and Ⅳ, LGG and HGG(P<0.01). Ktrans and Ve were positively correlated with glioma grades (P<0.01). Kep was negatively correlated with glioma grades (P<0.01). Ktrans was positively correlated with Ve (P<0.01). Ve was negatively correlated with Kep (P<0.01). In the ROC curve analysis, the cutoff value of Ktrans=0.037min-1for differentiation between LGG and HGG provided the best combination of sensitivity (92.5%) and specificity (83.9%).The cutoff value of Ve=0.149also provided the best combination of sensitivity (92.5%) and specificity (87.9%). There was no significance for Kep in the ROC curve analysis for differentiation between LGG and HGG. Conclusion:Our results suggested that the parameters of the kinetic analysis of two-compartment model of DCE-MRI had a high performance in grading of brain glioma. PART II:Quantitative Assessment of Microvascular Density and Tumor Proliferation Index in Brain Glioma based on Kinetic Analysis of Two-Compartment Model of DCE-MRIPurpose:To quantitatively evaluate the importance of the parameters (including Ktrans, Ve and Kep) of the kinetic analysis of two-compartment model of DCE-MRI in assessing microvascular density and tumor proliferation index by analyzing the correlation between Ktrans, Ve, Kep and Factor VIII-MVD (FVIII-MVD), CD105-MVD, vascular immaturity fraction (VIF), MIB-1labeling index (MIB-1LI) in brain glioma.Materials and Methods:DCE-MRI was preoperatively performed at3. OT MR in57patients(35males,22females; age range,14-70; mean age,45.7years), including24low grade gliomas(LGG:grade Ⅱ) and33high grade gliomas(HGG:grade III7and IV26). The maps of Ktrans, Ve and Kep were acquired by analyzing the imaging data with the two-compartment model. The values of Ktrans, Ve and Kep were measured on the the regions of highest signals on the maps. Surgical intervention was undertaken in all cases. The FVIII-MVD, CD105-MVD, MIB-1LI were all measured in surgical specimen. Statistical analysis of FVIII-MVD, CD105-MVD, VIF, and MIB-1LI was performed using ANOVA and t test across histologically defined glioma grades (when the data sets compiled with the conditions of normality and equal varianc); otherwise, statistical analysis of the parameters was performed using kruskal-wallis test and Mann-Whitney U test. The Spearman correlation coefficient was determined between Ktrans, Ve, Kep and FVIII-MVD, CD105-MVD, VIF, MIB-1LI. A P value of less than0.05was considered statistically significant.Results:1.The differences in FVIII-MVD, CD105-MVD, MIB-1LI were statistically significant between grade II and IV, LGG and HGG(P<0.01).2. Ktrans was positively correlated with FVIII-MVD, CD105-MVD, MIB-1LI (P<0.05); Ve was positively correlated with CD105-MVD, MIB-1LI (P<0.01); Kep was negatively correlated with CD105-MVD (P<0.05).3. The difference of VIF was not significant between LGG and HGG, and no correlation was demonstrated between Ktrans, Ve, Kep and VIF (P>0.05)Conclusion:Ktrans, Ve and Kep could be used to quantitatively assess the microvascular density (especially for the immature vessels) and tumor cell proliferation index in brain glioma. The kinetic analysis of two-compartment model of DCE-MRI play an important part in quantitatively evaluating the biological characteristics of microvascularity and tumor cells in brain glioma. Part III:The comparative study between DCE-MRI and CT perfusion in assessing the microvascular permeability of brain glioma:Ktrans and PSPurpose:To investigate whether the kinetic analysis of two-compartment model of DCE-MRI can be an alternative of substituting CT perfusion in assessing the microvascular permeability of brain glioma by analyzing the differences between Ktrans and PS.Materials and Methods:19patients(10males,9females; age range,27-70; mean age,51. lyears) was examined by CT perfusion at256-slice CT and by DCE-MRI in3.0T MR before surgery. The maps of Ktrans and PS were acquired by analyzing the imaging data with the same processing software. The values of Ktrans and PS were measured on the the regions of highest signals on the maps. Surgical intervention was undertaken in all cases. The Factor VIII-MVD (FVIII-MVD) and CD105-MVD were all measured in surgical specimen. Statistical analysis of Ktrans and PS was performed using the Mann-Whitney U test between low grade glioma (LGG) and high grade glioma (HGG). The Spearman correlation coefficient was determined between Ktrans, PS and FVIII-MVD, CD105-MVD. A P value of less than0.05was considered statistically significant.Results:19patients included6LGGs and13HGGs. The differences in Ktrans and PS were statistically significant between LGG and HGG (P<0.01). Ktrans and PS were both correlated with FVIII-MVD, CD105-MVD (P<0.01). Ktrans was correlated with PS (P<0.01).Conclusion:There were no differences between the kinetic analysis of two-compartment model of DCE-MRI and CT perfusion in assessing the microvascular permeability in brain glioma. The kinetic analysis of two-compartment model of DCE-MRI could be an alternative of substituting CT perfusion in assessing the microvascular permeability of brain glioma when considering patients avoiding receiving large doses of ionizing radiation.