Correlation between HPV infection and ovarian epithelial cancer diagnosed by Dynamic Contrast-enhanced magnetic resonance imaging information technology under exponential distribution mathematical model

Abstract

This research aims to analyze the correlation between human papillomavirus (HPV) infection and ovarian epithelial cancer based on exponential distribution mathematical model, so as to provide an experimental basis for the early diagnosis of ovarian epithelial cancer by magnetic resonance imaging (MRI) in the future. In this study, 124 patients with ovarian epithelial cancer tissues pathologically confirmed in our hospital from March 31, 2017 to February 20, 2019 were selected as the experimental group, and 64 patients with normal ovarian tissues were selected as the control group, and the positive rate of HPV infection was detected by the computer cell test (CCT) system. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was constructed and adopted to analyze the scanning images. The correlation between HPV infection and pathological type, clinical stage, tissue differentiation degree, and CA125 in serum was studied by exponential distribution mathematical model. The results showed that the positive rate of HPV infection in the ovarian tissues of the experimental group was significantly higher than that of the control group (P < 0.05). Highly differentiated patients accounted for 25.97%, moderately differentiated patients accounted for 43.81%, and lowly differentiated patients accounted for 30.22%. Patients with clinical stage I-II accounted for 24.72%, patients with stage III accounted for 49.11%, and patients with stage IV accounted for 26.17%. HPV infection was significantly correlated with clinical stage III and moderate tissue differentiation by MRI of patients (P < 0.05), and extremely significantly correlated with clinical stage IV and low tissue differentiation by MRI (P < 0.001). The above findings show that the information technology of dynamic contrast-enhanced magnetic resonance imaging can clearly display the lesion metastasis of ovarian epithelial cancer patients with high soft tissue resolution.