Histogram Analysis Comparison of Monoexponential, Advanced Diffusion-Weighted Imaging, and Dynamic Contrast-Enhanced MRI for Differentiating Borderline From Malignant Epithelial Ovarian Tumors.
BACKGROUND
The accurate preoperative differentiation between borderline and malignant epithelial ovarian tumors (BEOTs vs. MEOTs) is crucial for determining the proper surgical strategy and improving the patient's postoperative quality of life. Several diffusion and perfusion MRI technologies are valuable for the differentiation; however, which is the best remains unclear.


PURPOSE
To compare the whole solid-tumor volume histogram analysis of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced MRI (DCE-MRI) in the differentiation of BEOTs vs. MEOTs and to identify the correlations between the perfusion parameters from IVIM and DCE-MRI.


STUDY TYPE
Retrospective.


POPULATION
Twenty patients with BEOTs and 42 patients with MEOTs.


FIELD STRENGTH/SEQUENCE
1.5T/DWI, DKI, and IVIM models fitting from 13 different b factors and 40 phases DCE-MRI.


ASSESSMENT
Histogram metrics were derived from the apparent diffusion coefficient (ADC), diffusion kurtosis (K), diffusion coefficient (Dk), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), volume transfer constant (Ktrans ), rate constant (kep ), and extravascular extracellular volume fraction (ve ).


STATISTICAL TESTS
The Mann-Whitney U-test and receiver operating characteristic curve were used to determine the best histogram metrics and parameters. Multivariate logistic regression analysis was used to determine the best combined model for each two from the four technologies. Spearman's rank correlation was used to analyze the correlations between the IVIM and DCE-MRI parameters.


RESULTS
ADC, D, Dk, and D* were significantly higher in BEOTs than in MEOTs (P < 0.05). K, Ktrans , kep , and ve were significantly lower in BEOTs than in MEOTs (P < 0.05). The 10th percentile of Dk was the most reliable single metric, with an area under the curve (AUC) of 0.921. Dk combined with Ktrans yielded the highest AUC of 0.950. A weak inverse correlation was found between D and Ktrans (r = -0.320, P = 0.025) and between D and kep (r = -0.267, P = 0.037).


DATA CONCLUSION
The 10th percentile of Dk was the most valuable metric and Dk combined with Ktrans had the best performance for differentiating BEOTs from MEOTs. There was no evident link between perfusion-related parameters derived from IVIM and DCE-MRI.


LEVEL OF EVIDENCE
4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:257-268.
['He|Mengge|M|', 'Song|Yang|Y|0000-0001-7426-4496', 'Li|Haiming|H|', 'Lu|Jing|J|', 'Li|Yongai|Y|', 'Duan|Shaofeng|S|', 'Qiang|Jinwei|J|0000-0002-6327-1401']
D003287:Contrast Media D038524:Diffusion Magnetic Resonance Imaging D005260:Female D006801:Humans D008279:Magnetic Resonance Imaging D010051:Ovarian Neoplasms D011788:Quality of Life D015203:Reproducibility of Results D012189:Retrospective Studies
histogram analysis diffusion-weighted imaging contrast-enhanced imaging magnetic resonance imaging ovarian neoplasm