Vol. 88, March 20120

Can Quantitative and Qualitative DWI Differentiate between Benign and Malignant Ovarian Masses?

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Can Quantitative and Qualitative DWI Differentiate between Benign and Malignant Ovarian Masses?, MOHAMED M. HEFEDA, LAMIAA ALAHWAL and MOHAMED F. DAWOUD

 

 Abstract

Background: Pre-operative diagnosis of ovarian represents diagnostic challenge as it affects the lines of treatment and patient's prognosis. Previous studies studied the role of the Diffusion Weighted Imaging (DWI) in discrimination between benign and malignant ovarian masses with controversial results. Aim of Study: The aim of this study was to evaluate the role of qualitative and quantitative Diffusion Weighted Imaging (DWI) in the discrimination between benign and malignant ovarian tumors. Material and Methods: The study included 82 patients. All patients underwent MRI with a 1.5T unit. Conventional MRI both pre and post contrast. Before administration of the contrast, the DWI sequence, single shot echo planar sequence in the axial plane was done for all patients. Analysis of the MRI findings, the signal intensity on DWI and the ADC value for solid and cystic components was done for all lesions. Results: For conventional MRI, the overall sensitivity, specificity, PPV, NPV and accuracy of MRI was 85.71%, 85.71%, 87.80%, 83.33% and 85.71% respectively. Hyperin-tense signal on DWI of the solid component was observed in 17/18 (94.4%) of malignant tumors. The restricted diffusion in the solid components had a sensitivity of 94.44%, specificity 85.71%, PPV 94.44% and NPV of 85.71% with overall accu-racy of 92.% in prediction of malignancy. Using 1.2 X 10–3 mm2/sec) as a cut off value between benign an malignant lesion had sensitivity 88.89%, specificity 85.71% and accuracy 88% in differentiation between benign and malignant masses. Conclusion: Diffusion weighted imaging especially the qualitative component have high diagnostic accuracy in differentiation between benign and malignant ovarian masses and should be integrated into the pelvic MRI.

 

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