Texture analysis of SPIO-enhanced MR imaging in rat models of hepatocellular carcinoma and hepatocirrhosis based on gray level co-occurrence matrix
Objective To analyze the texture features of SPIO-enhanced MR imaging in rat models of hepatocellular carcinoma (HCC) and hepatocirrhosis with gray level co-occurrence matrix (GLCM). Methods HCC and hepatocirrhosis models were established in rats. SPIO-enhanced MR images were obtained. A total of 161 regions of interests (ROIs, 81 of HCC and 80 of hepatocirrhosis) were selected manually. Feature values as angular second moment, contrast, correlation, inverse difference moment, entropy, variance were extracted based on GLCM. The differences of feature values between two groups were statistically analyzed. Results In SPIO-enhanced MR images, hypointense signal changes were found in hepatocirrhosis, as well as hyperintensity in HCC nodules and intermixed intensity in larger HCC nodules. Correlation and entropy values of HCC group were higher than that of hepatocirrhosis group, while the angular second moment, contrast, inverse difference moment, and variance values were lower than hepatocirrhosis group. Conclusion The feature values based on GLCM could be used for the further computer aided diagnosis of SPIO-enhanced MR images in rat models of HCC and hepatocirrhosis.
NETL
NSTL
万方数据
维普
