Application of Diffusion Tensor Imaging Quantitative Parameters in Grading of Cerebral Glioma on a 3.0T Scanner
10.3969/j.issn.1005-5185.2015.04.003
- VernacularTitle:3.0T扩散张量成像定量参数在脑胶质瘤分级中的应用
- Author:
Liang JIANG
;
Jun SUN
;
Wen LIU
;
Chaoyong XIAO
;
Zonghong LI
;
Xindao YIN
- Publication Type:Journal Article
- Keywords:
Glial cell tumors;
Brain neoplasms;
Magnetic resonance imaging;
Diffusion tensor imaging
- From:
Chinese Journal of Medical Imaging
2015;(4):250-254,259
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To study the application of MR diffusion tensor imaging (DTI) quantitative parameters in grading of cerebral glioma on a 3.0T scanner. Materials and Methods DTI mapping of 51 cases of cerebral glioma confirmed by pathology were retrospective analyzed. All the cases were divided into two groups: low-grade gliomas (grade I-II, 18 cases) and high-grade gliomas (grade III-IV, 33 cases). Value of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD),λ1, λ2, and λ3 of the tumor, peritumoral edema and contralateral tissue area were recorded and compared. Results rMDt, rADt, rRDt, λ1t, λ2t and λ3t of tumor in the low-grade glioma group were higher than those in the high-grade glioma group, and the difference was statistically significant (t=-3.235- -2.458, P<0.05). rFAt was lower in the low-grade glioma group, and the difference was not statistically significant (t=1.554, P>0.05). rFAe of peritumoral edema in the low-grade glioma group was higher than those in the high-grade group, while rMDe, rADe, rRDe, λ1e, λ2e and λ3e were lower in the low-grade group. All differences were not statistically significant except λ1e (t=2.052, P<0.05). ROC analysis showed the area under the curve (Az) of rMDt, rADt, rRDt, λ1t, λ2t, λ3t and λ1e were 0.746, 0.710, 0.762, 0.735, 0.722, 0.705 and 0.374, respectively. Az value of rMDt, rADt, rRDt,λ1t, λ2t, λ3t were statistically different between the low- and high-grade gliomas (Z=3.287-4.605, P<0.001). Conclusion Among DTI quantitative parameters on glioma grading, rMD, rAD, rRD, λ1, λ2, and λ3 of tumor area are helpful in grading gliomas.
