OBJECTIVES: To determine whether threshold criteria using semi-quantitative multiphase-dynamic contrast-enhanced magnetic resonance imaging (DCE- MRI) can improve prediction of malignancy in complex adnexal masses. METHODS: MRI features of 70 complex adnexal masses with enhancing components in 63 patients were reviewed and correlated with histopathology (n = 67) or radiological follow-up (n = 3). Masses were categorised as benign (n = 34) or borderline/invasive malignant (n = 36). Borderline lesions (n = 6) were also analysed separately. Using the semi-quantitative breast analysis software, regions of interest were drawn around the most avidly enhancing component of each lesion. Maximum absolute enhancement of signal intensities (SI(max)), maximum relative enhancement (SI(rel)) and wash-in rate (WIR) were recorded. Optimal threshold criteria were established to predict borderline/invasive malignancy. RESULTS: There was a significant difference in mean SI(max) (P < 0.05), SI(rel) (P < 0.01) and WIR (P < 0.001) between benign and borderline/invasive malignant groups. A cut-off WIR ≥ 9.5 l/s had a specificity of 88% and positive predictive value of 86% for predicting malignancy, significantly better than conventional MRI (62%, P < 0.01). WIR <8.2 l/s had a negative predictive value of 94%. CONCLUSION: Threshold criteria using semi-quantitative multiphase DCE-MRI improves specificity in the prediction of malignancy in complex adnexal masses with enhancing components and is complementary to standard qualitative assessment. KEY POINTS: Semi-quantitative DCE-MRI threshold criteria are effective for predicting ovarian malignancy. The surgical approach may be altered depending on DCE-MRI threshold criteria analysis. Borderline tumours demonstrate significant overlap with benign lesions using DCE-MRI threshold criteria.
OBJECTIVES: To determine whether threshold criteria using semi-quantitative multiphase-dynamic contrast-enhanced magnetic resonance imaging (DCE- MRI) can improve prediction of malignancy in complex adnexal masses. METHODS: MRI features of 70 complex adnexal masses with enhancing components in 63 patients were reviewed and correlated with histopathology (n = 67) or radiological follow-up (n = 3). Masses were categorised as benign (n = 34) or borderline/invasive malignant (n = 36). Borderline lesions (n = 6) were also analysed separately. Using the semi-quantitative breast analysis software, regions of interest were drawn around the most avidly enhancing component of each lesion. Maximum absolute enhancement of signal intensities (SI(max)), maximum relative enhancement (SI(rel)) and wash-in rate (WIR) were recorded. Optimal threshold criteria were established to predict borderline/invasive malignancy. RESULTS: There was a significant difference in mean SI(max) (P < 0.05), SI(rel) (P < 0.01) and WIR (P < 0.001) between benign and borderline/invasive malignant groups. A cut-off WIR ≥ 9.5 l/s had a specificity of 88% and positive predictive value of 86% for predicting malignancy, significantly better than conventional MRI (62%, P < 0.01). WIR <8.2 l/s had a negative predictive value of 94%. CONCLUSION: Threshold criteria using semi-quantitative multiphase DCE-MRI improves specificity in the prediction of malignancy in complex adnexal masses with enhancing components and is complementary to standard qualitative assessment. KEY POINTS: Semi-quantitative DCE-MRI threshold criteria are effective for predicting ovarian malignancy. The surgical approach may be altered depending on DCE-MRI threshold criteria analysis. Borderline tumours demonstrate significant overlap with benign lesions using DCE-MRI threshold criteria.
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