Analysis of MRI imaging characteristics in 10 cases of adult granulosa cell tumor with normal estrogen levels.

OBJECTIVE

This study investigates the MRI characteristics of primary and metastatic adult granulosa cell tumor with normal estrogen levels (AGCT-NEL) to enhance clinical understanding and diagnostic accuracy of this disease.

METHODS

We collected clinical data from 10 patients with AGCT-NEL, confirmed by pathology, treated at our hospital from January 2016 to January 2024. We retrospectively analyzed the MRI features of primary and metastatic lesions from aspects such as shape, edge characteristics, MRI signal, and enhancement features.

RESULTS

A total of 10 AGCT-NEL patients were included in this study, aged 28 to 81 years, with an average age of 54 ± 16 years. The primary tumors primarily presented as unilocular cystic, solid, and cystic-solid types. The solid components showed isointense to slightly hypointense signals on T1-weighted imaging (TWI), slightly hyperintense signals on T2-weighted imaging (TWI), and high signals on diffusion-weighted imaging (DWI), with possible internal hemorrhage or cystic degeneration. The cystic components exhibited low signal on TWI, high signal on TWI, uniform wall thickness, and no wall nodules, typically showing hemorrhagic fluid levels. Honeycomb and Swiss cheese signs are sometimes observed in cystic-solid tumors. All metastatic lesions were cystic (either unilocular or multilocular), presenting low signal on TWI and high signal on TWI, with no wall nodules and possible internal hemorrhagic fluid levels. The multilocular metastatic tumors demonstrated unevenly thickened partitions, also displaying honeycomb and Swiss cheese signs.

CONCLUSION

The MRI characteristics of primary and metastatic lesions in AGCT-NEL possess specific features, such as signs of hemorrhage, absence of wall nodules in the cystic portions of the tumors, and distinctive honeycomb and Swiss cheese signs, with metastatic lesions being cystic. Understanding these features can aid in improving preoperative diagnostic capabilities and reducing misdiagnosis.