Analysis on the Diagnosis of Ovarian Follicular Membrane Cell Tumor by Magnetic Resonance Imaging Under Statistical Discrepancy Algorithm

Abstract

In order to improve the early diagnosis rate of follicular cell tumor (C-Tu), reduce the occurrence of malignant tumor, make the patients receive timely treatment, and reduce the mortality, in this research, a total of 48 patients diagnosed as follicular C-Tu admitted to Chongqing Traditional Chinese Medicine Hospital from January 2017 to December 2018 were selected. Computed tomography (CT) and functional magnetic resonance imaging (MRI) images were used to obtain the image of lesion site and analyze the image characteristics. Patients were grouped and compared according to the difference of image characteristics based on statistical discrepancy algorithm (SDA). The specificity (Sp) and sensitivity (Se) of CT scan and MRI images were compared and analyzed to provide the most effective detection method for the subsequent clinical diagnosis. The results showed that most patients had unilateral disease, and most of them were round or oval, with different sizes. The SDA can effectively organize and analyze the influence characteristics of patients. Patients can be grouped according to the proportion of cystic firmness shown in the image. MRI plain scan showed moderate or low signal on T1WI and high signal on T2WI. The T2WI signal could be enhanced with the continuous cystic change of lesion site. The diagnosis efficiency (DE) of CT and MRI was compared with that of surgical pathology as the gold standard. The Se and accuracy (Ac) of MRI diagnosis were higher than that of CT diagnosis, and the comparison of kappa consistency was 0.73 (P < 0.05), which showed that the imaging diagnosis of follicular membrane cell tumour by MRI could obtain higher diagnosis Ac.