How to integrate O-RADS MRI scores with clinical and imaging criteria to predict histopathological subtypes

To enhance diagnostic precision by integrating the O-RADS MRI score with clinical and imaging criteria for histopathological subtyping.

This retrospective study analyzed data from the EURAD (EURopean ADnexal study) database between 2013 and 2018. Univariate and multivariate logistic regression analyses were performed to identify features potentially associated with presumed final histology.

The study encompassed 869 adnexal lesions from 651 patients (mean age: 49.7, STD: 16.1). On multivariate analysis, the presence of fatty content (OR = 126.5, CI_95% [43.6-367.1]) and multiple different signal T1W/T2W signals of cystic component (OR = 4.0, CI_95% [1.8-8.8]) were strongly associated with mature cystic teratomas. Endometriomas were predicted by endometriotic fluid (OR = 20.7, CI_95% [10.5-40.7]) and ADC values (× 10^-3 mm²/s) of cystic component (ADC_CT) < 2 (OR = 3.8, CI_95% [1.7-8.7]). Similarly, voluminous multilocular cysts with > 10 loculi (OR = 4.3, CI_95% [1.7-10.7]) were indicative of benign mucinous cystadenomas. The analysis also highlighted the significance of ADC values in distinguishing between benign and infiltrative lesions. Unilocular cysts with ADC_CT > 2 (OR = 11.1, CI_5% [3.8-32.8]) were strongly associated with benign serous cystadenomas. ADC of solid tissue (ADC_ST) with mural nodule morphology < 1.08 (OR = 3.3, 95%, CI_95% [1.5-7.5]) was predictive of primary invasive tumors, whereas ADC_ST > 1.08 (OR = 3.6, CI_95% [1.2-10.7]) with papillary projection was predictive of borderline tumors.

Combining the O-RADS MRI score with morphology, size, type of solid tissue and cystic component, including ADC values, enhances the precision of diagnosing presumed histological subtypes.

Question Does integrating the O-RADS MRI score with clinical and imaging criteria improve diagnostic precision for histopathological subtyping? Findings Combining the O-RADS MRI score with specific clinical or imaging features improved the prediction of borderline, primary invasive, or metastatic tumors. Clinical relevance Combining the O-RADS MRI score with morphological and clinical features can help differentiate ovarian tumors thereby improving patient management, as this can help guide treatment decisions, avoid unnecessary surgeries, and streamline the referral process to specialized care.