Value of Diffusion Weighted Imaging in Ovarian Lesion Diagnosis

Document Type : Original Article

Authors

1 Department of Radiology, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt

2 National Cancer Institute, Cairo University, Egypt

Abstract

Background: Surgical exploration and histologic evaluation are often required to determine the nature of the ovarian tumors being benign or malignant. Therefore, it may be impossible to determine beforehand whether minimally invasive or extensive surgery is required. Better preoperative planning might be accomplished with the use of a trustworthy approach that could distinguish malignant and benign masses. MRI is beneficial for identifying ovarian masses and their origins due to its sensitivity and improved characters by the application of diffusion-weighted imaging. This research aimed to assess the characterization of ovarian lesions using MRI with DWI.
Methods: Forty patients diagnosed to have ovarian masses were evaluated in this cross-sectional analytical study after being referred to the University Hospital at the radiology department. All patients were exposed to pelvic MRI with DWI, and 7 underwent DWIBS. Surgery was performed with pathologic correlation on 39 individuals. Only one patient was given a 3-month course of routine US monitoring.
Results: MRI's sensitivity was 99.9 percent, whereas DWI's was one hundred percent. When comparing DWI with traditional MRI, the former has a greater specificity (78.1%) while the latter has a better accuracy (86.0%). On average, malignant lesions had an ADC of (0.93x 10-3 ± 0.43 SD mm2/s), whereas benign ones had 1.3 x 10-3 ± 0.6 SD mm2/s with a p-value = 0.005. Because of the teratoma's mixed cellularity, mature teratomas exhibited restricted diffusion with ADC values of 0.5x10-3mm2/s (false positive).
Conclusion: The specificity of conventional MRI was enhanced when combined with DWI, boosting radiologist confidence in picture interpretation and, in turn, improving patients' outcomes and prognoses.

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Main Subjects


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