Objective: To compare the capability of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) histogram analysis in epithelial ovarian tumor categorization.
Methods: We retrospectively recruited 52 patients with pathologically proven ovarian serous epithelial cancer from our institution. ADC histogram analysis was performed using FeAture Explorer software after outlining the whole lesion area on the ADC map. The ADC histogram parameter difference between subgroups was compared; the correlation between the quantitative parameters on MRI and Ki-67 expression was calculated for both groups.
Results: The repeatability of ADC measurements across the two methods was good; the area method (ADCarea) had better performance in repeatability than the ROI method (ADCroi). The ADCroi, ADCarea, Ktrans, and Kep values significantly differed between the groups ( < 0.05). The histogram parameters (percent10, entropy, minimum, range and variance) and DCE parameter (Ktrans) were strongly correlated with Ki-67 expression ( = 0.000), while the conventional ADC measurements were not significantly correlated with Ki-67 expression ( > 0.05). Overall, Ktrans had the best diagnostic performance for discriminating type I with type II ovarian cancers (AUC = 0.826).
Conclusion: In the present study, both diffusion-weighted imaging (DWI) and DCE MRI could help classify ovarian cancer patients with high accuracy. ADC histogram analysis could accurately reflect the proliferative capability of tumor cells to some extent.
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