doi:10.3969/j.issn.1674-490X.2020.02.006

Abstract

Abstract: Objective To explore the diagnostic value of the parameters of neurite orientation dispersion and density imaging(NODDI)in glioma classification. Methods A total of 30 cases of brain glioma, 16 cases of male and 14 cases of female, with an average age of(46.23±7.58)years were investigated with a retrospective study, of which 18 cases suffered from high-grade glioma and 12 cases from low-level glioma. Patients were examined with routine MR scan, enhancement, diffusion weighted imaging(DWI)and NODDI before operation,the results were determined with software to get figures of the oritention dispersion index(ODI), the intracellular volume fraction(VIC), the entracellular volume fraction(xVEC,yVEC,zVEC), the concentration distribution of Watson parameters(kappa)and the isotropic volume fraction(VISO), through the picture analysis software measurement with a tumor parenchyma, peritumoral area and contralateral normal white matter value of the average(mean). Results The mean values of VISO, yVEC, kappa, VIC and ODI of low-grade glioma could distinguish the solid area from the normal area, with statistically significant difference(P<0.05). The mean values of VISO, xVEC and VIC could distinguish the edema area from the normal area, with statistically significant difference(P<0.05). The mean values of VISO, yVEC, kappa, VIC and ODI of high-grade glioma could distinguish the solid area from the normal area, with statistically significant difference(P<0.05). The mean values of VISO, xVEC, yVEC, kappa, VIC and ODI could distinguish the edema area from the normal area, with statistically significant difference(P<0.05). In the solid area, the mean values of VISO, yVEC, kappa, VIC and ODI could distinguish the high grade glioma from the low grade glioma, with statistically significant difference(P<0.05). In edema area, the mean values of VISO, xVEC, zVEC and kappa could distinguish high-grade glioma from low-grade glioma, with statistically significant difference(P<0.05). Conclusion In the statistical results of the data in this study, NODDI's VISO, VEC, kappa, VIC and ODI parameters could identify high and low grade gliomas.

Key words: neurite orientation dispersion and density imaging, MRI, glioma, preoperative diagnostic classification

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