Evaluation of the role of diffusion-weighted MRI in differentiating benign and malignant ovarian lesions
Evaluation of the role of diffusion-weighted MRI in differentiating benign and malignant ovarian lesions
forouzan absalan,1,*Farhad Heidari,2Ali Reza Eftekhari Moghadam1,3Milad Jalilian,4
2. Medical faculty, Abadan University of Medical Sciences, Abadan, Iran. 4. Department of Neuroscience, Neuroimaging and Addiction Studies, Schools of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
Introduction: Ovarian malignancies are one of the most common cancers of the female reproductive system and account for approximately 5% of women's deaths due to cancer, which requires early diagnosis. Therefore, the purpose of this study is the role of MRA emission weight imaging in differentiating malignant from benign ovarian lesions.
Methods: This study was conducted on 58 patients, of these 31 (53.4%) had benign and 27 (46.6%) had malignant masses. Imaging findings were reviewed in patients. Then the data was analyzed based on the findings of diagnostic accuracy.
Results: The findings of our study showed that the average T2 in patients with malignant tumors were significantly lower than the patients with benign mass (432.87 vs. 687.56) and also the average ADC in patients with malignant tumors were significantly lower. It was less than the patients with benign mass (115.69 vs. 995.39), on the other hand, the mean DWI in patients with malignant tumors was significantly higher than the patients with benign mass (548.03 vs. 184.71) and the average T1+ GAD in patients with malignant tumor was significantly more than patients with benign mass (154/16 vs. 24/44) and finally it was found that DWI and T1+GAD had the highest diagnostic accuracy in diagnosing ovarian malignant masses.
Conclusion: Considering the very high diagnostic accuracy of DWI and T1+GAD factors, malignant tumors can be distinguished from benign tumors with almost 100% accuracy from these two factors and the treatment process can be based on it.