Objective To determine feasibility of texture analysis of non-enhanced CT scan for differential diagnosis of liver cancer and hepatic hemangioma. Methods Fifty-six patients with liver cancer or hepatic hemangioma confirmed by pathology were enrolled in this retrospective study. After exclusion of images of 4 patients with artifacts and lesion diameter less than 1.0 cm, images of 52 patients (57 lesions) were available to further analyze. Texture features derived from the gray-level histogram, co-occurrence and run-length matrix, absolute gradient, autoregressive model, and wavelet transform were calculated. Fisher, probability of classification error and average correlation (POE+ACC), and mutual information coefficients (MI) were used to extract 10 optimized texture features. The texture characteristics were analyzed by using linear discriminant analysis (LDA) and nonlinear discriminant analysis (NDA) provided by B11 module in the Mazda software, the minimum error probability of differential diagnosis of liver cancer and hepatic hemangioma was calculated. Most discriminating features (MDF) of LDA was applied to K nearest neighbor classification (KNN); NDA to extract the data used in artificial neural network (ANN) for differential diagnosis. Results The NDA/ANN-POE+ACC was the best for identifying liver cancer and hepatic hemangioma, and the minimum error probability was the lowest as compared with the LDA/KNN-Fisher, LDA/KNN-POE+ACC, LDA/KNN-MI, NDA/ANN-Fisher, and NDA/ANN-MI respectively, the differences were statistically significant (χ2=4.56, 4.26, 3.14, 3.14, 3.33;P=0.020, 0.018, 0.026, 0.026, 0.022). Conclusions The minimum error probability is low for different texture feature selection methods and different analysis methods of Mazda texture analysis software in identifying liver cancer and hepatic hemangioma, and NDA/ANN-POE+ACC method is best. So it is feasible to use texture analysis of non-enhanced CT images to identify liver cancer and hepatic hemangioma.
Carney triad is a rare tumor syndrome with few reports. This case showed the enhanced CT and MRI images of a rare young woman patient with Carney triad (containing gastric stromal tumor, renal cell carcinoma, adrenal pheochromocytoma, and pulmonary chondrosarcoma), which is intended to provide a reference for clinical diagnosis and differential diagnosis. This case reminds the radiologists and clinicians that the patients with a history of primary gastrointestinal stromal tumor and neoplastic lesions occurring at specific sites (pulmonary chondrosarcoma, adrenal pheochromocytoma, renal cell carcinoma, etc.) need to be alerted to the possibility of combining with Carney triad.