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Published on: November 28, 2010
Multiparametric MRI Features of Seromucinous and Mucinous Benign and Borderline Ovarian Tumors
1Department of Radiology, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey.
Objective:
To evaluate morphologic and quantitative MRI features associated with seromucinous and mucinous ovarian tumors of benign and borderline histology, with emphasis on their complementary role within structured preoperative imaging assessment.
Methods:
This retrospective single-center study included 76 women with 79 histopathologically confirmed mucinous or seromucinous ovarian tumors of benign or borderline histology who underwent preoperative pelvic MRI between 2011 and 2025. Tumors were classified as mucinous benign, mucinous borderline, seromucinous benign, or seromucinous borderline. MRI evaluation included morphologic features (tumor size, loculation number, septal thickness, and mural nodule presence) and quantitative analyses using signal intensity ratios on T1- and T2-weighted images (SIR-T1, SIR-T2). Enhancement and diffusion metrics were assessed for mural nodules when present. Multinomial logistic regression identified independent imaging predictors, and receiver operating characteristic (ROC) analysis evaluated diagnostic performance.
Results:
Tumor subtypes demonstrated distinct morphologic and signal-based patterns. Borderline tumors showed a higher prevalence of mural nodules than benign tumors. SIR-T1 differed significantly among subgroups and remained associated with tumor subtype in exploratory multivariable analysis. Overall intergroup differences were observed for tumor size, loculation number, SIR-T1, and mural nodule presence; however, these findings should be interpreted cautiously given the limited subgroup sizes. ROC analysis showed that SIR-T1 differentiated seromucinous borderline from mucinous benign tumors (AUC=0.801), while tumor size differentiated seromucinous benign from mucinous borderline tumors (AUC=0.796). Inter- and intraobserver agreement was good to excellent.
Conclusions:
Multiparametric MRI assessment integrating morphologic features with selected signal-based metrics may provide complementary information for the preoperative characterization of mucinous and seromucinous ovarian tumors. These findings should be interpreted as exploratory and adjunctive to structured MRI assessment frameworks such as O-RADS MRI rather than as standalone diagnostic criteria.
