GnRHa as a Treatment for Letrozole-Resistent Recurrent Adult Granulosa Cell Tumors: A Case Report and Literature Review

Background: The optimal management of Recurrent Ovarian granulosa cell tumors was still unknown, Hormone therapy maybe an alternative for chemotherapy-resistant cases. the reaction rate for aromatase inhibitors was highest, how to treat the progressed case after aromatase inhibitors was challenging. Case presentation: Here we report a case of Recurrent Ovarian granulosa cell tumors treated with Diphereline and achieved clinical cure. A 46-year-old woman presented with third recurrence after primary treatment. She developed tumor progression and drug-induced nephritis after 6 cycles of combined treatment of cisplatin and paclitaxel for the second recurrence and failed to benefit from chemotherapy ,after the third Optimal cytoreduction and tumor progression after 6 months Letrozole treatent. The implementation of experimental treatment with Diphereline achieved Good therapeutic effect.Conclusion: Hormone therapy maybe an alternative to recurrent granulosa cell tumors, Gonadotropin-releasing hormone agonistsas maybe a rescued treatment for Aroatase inhibitor-resistant cases

The Value of MRI Findings Combined With Texture Analysis in the Differential Diagnosis of Primary Ovarian Granulosa Cell Tumors and Ovarian Thecoma–Fibrothecoma

ObjectiveThis study aims to explore the value of magnetic resonance imaging (MRI) and texture analysis (TA) in the differential diagnosis of ovarian granulosa cell tumors (OGCTs) and thecoma-fibrothecoma (OTCA–FTCA).MethodsThe preoperative MRI data of 32 patients with OTCA–FTCA and 14 patients with OGCTs, confirmed by pathological examination between June 2013 and August 2020, were retrospectively analyzed. The texture data of three-dimensional MRI scans based on T2-weighted imaging and clinical and conventional MRI features were analyzed and compared between tumor types. The Mann–Whitney U-test, χ2 test/Fisher exact test, and multivariate logistic regression analysis were used to identify differences between the OTCA–FTCA and OGCTs groups. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic curve analysis was carried out to evaluate diagnostic efficiency.ResultsA multivariate analysis of the imaging-based features combined with TA revealed that intratumoral hemorrhage (OR = 0.037), log-sigma-20mm-3D_glszm_SmallAreaEmphasis (OR = 4.40), and log-sigma-2-0mm-3D_glszm_SmallAreaHighGrayLevelEmphasis (OR = 1.034) were independent features for discriminating between OGCTs and OTCA–FTCA (P < 0.05). An imaging-based diagnosis model, TA-based model, and combination model were established. The areas under the curve of the three models in predicting OGCTs and OTCA–FTCA were 0.935, 0.944, and 0.969, respectively; the sensitivities were 93.75, 93.75, and 96.87%, respectively; and the specificities were 85.71, 92.86, and 92.86%, respectively. The DeLong test indicated that the combination model had the highest predictive efficiency (P < 0.05), with no significant difference among the three models in differentiating between OGCTs and OTCA–FTCA (P > 0.05).ConclusionsCompared with OTCA–FTCA, intratumoral hemorrhage may be characteristic MR imaging features with OGCTs. Texture features can reflect the microheterogeneity of OGCTs and OTCA–FTCA. MRI signs and texture features can help differentiate between OGCTs and OTCA–FTCA and provide a more comprehensive and accurate basis for clinical treatment.