Multiparametric MRI Evaluation of Complex Ovarian Masses

To assess the role of diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in the categorization of complex ovarian masses into benign and malignant. This prospective study was done on 33 complex ovarian masses. T1 and T2-weighted sequences, diffusion-weighted imaging,...

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Veröffentlicht in:Current problems in diagnostic radiology 2021-01, Vol.50 (1), p.34-40
Hauptverfasser: Singla, Veenu, Dawadi, Kapil, Singh, Tulika, Prabhakar, Nidhi, Srinivasan, Radhika, Suri, Vanita, Khandelwal, Niranjan
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Sprache:eng
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Zusammenfassung:To assess the role of diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in the categorization of complex ovarian masses into benign and malignant. This prospective study was done on 33 complex ovarian masses. T1 and T2-weighted sequences, diffusion-weighted imaging, apparent diffusion coefficient, and dynamic contrast-enhanced magnetic resonance imaging were performed on 1.5 T MRI. Time-intensity curves, tissue signal intensity on unenhanced T1 images (SI0), maximum absolute contrast enhancement (SImax), time to reach SImax (Tmax), maximum relative SI (SIrel = [SImax − SI0]/SI0 ×100), maximum Slope (Slopemax = SIrel/Tmax ×100), and wash in rate (WIR = [SImax − SI0]/Tmax) were calculated. Histopathological diagnosis was taken as gold standard. A total of 20/33 masses were benign, 2/33 were borderline tumors, and 11/33 were malignant. Diffusion restriction was seen in all malignant masses and 13/20 benign masses. The mean apparent diffusion coefficient values showed a significant difference between malignant and benign, with 81.8% sensitivity and 63.6% specificity. Type III curve showed 100% specificity for malignant lesions. Tmax and Slopemax were useful in differentiating benign and malignant masses; with Tmax cut-off at 73.5 seconds having a high specificity (81.8%) and Slopemax cut-off at 0.83%/s having high sensitivity (91%) and negative predictive value (94.4%). Multiparametric MRI confers high diagnostic accuracy in stratifying complex ovarian masses.
ISSN:0363-0188
1535-6302
DOI:10.1067/j.cpradiol.2019.07.008