Role Of Diffusion-Weighted Magnetic Resonance Imaging in Evaluation of Gynecologic Tumors

Background: Ovarian tumors are the second most common gynecological tumor and fifth commonest tumor in women and has the highest mortality rate among gynecologic malignancies . It is estimated to comprise 6% of all cancer-related deaths . It is desirable to preoperatively differentiate benign from malignant tumor to decide whether surgery is required, and which type of surgery is appropriate avoiding unnecessary surgery. Magnetic resonance imaging (MRI) has been established as an excellent modality for evaluation of gynecologic disease. However, morphologic MRI imaging has some limitations for lesion detection and characterization. The innovation of newer functional imaging sequences such as diffusion-weighted imaging has addressed many of these issues and enhanced diagnostic capabilities of MRI. Aim: To investigate the role of DWI in distinguishing between benign and malignant lesions in light of the increasing recognition of DWI. Patients & Methods : The current study is a prospective study that was conducted at diagnostic radiology department of Benha and Mansoura University Hospitals in the period from October 2018 till January 2022. The study included 80 female patients with any age complaining of gynecologic problem like mass lesion, vaginal bleeding or pelvic pain including any type of lesion inflammatory or neoplastic and excluding congenital malformation lesions. Ethical consideration, an informed consent was obtained from patients before enrollment in the study and an approval from research Ethics committee in Benha faculty of Medicine was obtained in 2015 with no code or number -code starts from 2019-.Axial T1-WI, Axial T2-WI, Sagittal T2-WI, and Coronal T2-WI, Gradient-echo sequences (GRE), Diffusion weighted MR images (DWI), ADC and Dynamic Contrast-Enhanced MRI- were all used in the MRI examination. Results: We found that the specificity and the accuracy of the DWI results were both 88.5 and 91.3 percent, respectively. ADC revealed a 94.7 percent sensitivity, 91.8 percent specificity,