ABSTRACT
Objective:To explore the application value of contrast-enhanced ultrasound with SonoLiver software including quantitative analysis and dynamic vascular pattern (DVP) in the intraoperative diagnosis of glioma.Methods:SonoLiver software was used to analyze the contrast-enhanced ultrasound (CEUS) process of 252 cases with different grades of gliomas in General Hospital of Southern Theatre Command of PLA from 2006 to 2016. Among them, 144 were in the low-grade gliomas (LGG) group and 108 were in the high-grade gliomas (HGG) group. The quantitative parameters included maximum intensity (IMAX), time to peak (TTP) and mean transit time (mTT). The images of each CEUS were obtained, and the microvessel density (MVD) of corresponding pathology was compared, so as to analyze their correlations and characteristics.Results:There were significant differences in IMAX, TTP and mTT between the CEUS parameters of gliomas with different grades. IMAX in HGG group was significantly higher than that in LGG group( P<0.001), while TTP was shorter ( P=0.017) and mTT was longer( P=0.030). By correlation analysis between MVD and the CEUS parameters, MVD was positively correlated with IMAX ( r s=0.736, P<0.001) and mTT( r s=0.184, P=0.003), but negatively correlated with TTP( r s=-0.186, P=0.003). Compared with DVP images, the tumor areas of LGG group were mainly warm and black colors with small spots of cool-colored areas, and most of the surrounding areas were more obvious black areas. In HGG group, the tumor areas were mainly warm colors. Most of which were scattered in patchy cold colors areas, and the surrounding black areas were less ( P<0.05). There were significant differences in differentiating gliomas boundary before and after using DVP technique ( P<0.05). After using DVP, the boundary of glioma was clearer and more discernible. The discernibility of HGG group was up to 99%, and that of LGG group reached 97%. Conclusions:SonoLiver software can effectively and quantitatively analyze the CEUS parameters of gliomas with different grades, and its DVP images can directly reflect the contrast perfusion characteristics of gliomas, providing a new way to distinguish the boundary of gliomas and a new imaging method for the differential diagnosis of high and low grades of gliomas.