Enhancing the preoperative diagnostic accuracy for ovarian sex cord-stromal tumors through evaluation of clinical and imaging characteristics

Introduction

Ovarian sex cord-stromal tumors (OSCSTs) constitute rare and diverse type of ovarian tumors, accounting for a mere 5% to 8% of all ovarian neoplasms (1). This group encompasses various subtypes, notably ovarian thecoma, fibroma (comprising cellular fibroma), ovarian granulosa cell tumor (OGCT) (comprising adult OGCT and juvenile OGCT), sclerosing stromal tumor, and Sertoli-Leydig cell tumor, among others. Notably, OSCSTs frequently exhibit a combination of theca cells and fibroblasts, commonly referred to as fibrothecoma (2). Thecoma is not formally recognized in the World Health Organization (WHO) classification, and being rare, it is often grouped under fibrothecoma. Within the spectrum of OSCSTs, a classification of tumors into benign, borderline, and malignant types is feasible, with the majority being benign and carrying a favorable prognosis. Surgical intervention remains the primary therapeutic modality for OSCSTs. Granulosa cell tumors of the ovary are typically low-grade malignancies, necessitating a tailored surgical approach based on a comprehensive assessment of factors such as patient age, tumor histology, and fertility considerations. Conversely, OGCTs are generally low-grade malignancies, particularly advanced cases, posing risks of recurrence and metastasis (3). Consequently, accurate preoperative categorization of OSCSTs is critical to the selection of appropriate management strategies.

In diagnostic imaging, magnetic resonance imaging (MRI) is an invaluable tool for the preoperative assessment of pelvic lesions, including ovarian neoplasms, offering superior multiplanar imaging, multiparametric capabilities, radiation-free imaging, and high soft-tissue resolution (4). Meanwhile, ultrasound is as a key modality for the clinical evaluation of ovarian tumors, with advantages of minimal radiation exposure, ease of use, noninvasiveness, repeatability, and cost-effectiveness (4). Together, MRI and ultrasound are essential to the accurate diagnosis of pelvic lesions. However, the rarity and relative obscurity of OSCSTs often lead to preoperative misdiagnoses, underdiagnoses, or challenges in precise subclassification.

Research on OSCST diagnosis (4,5) has predominantly focused on isolated ultrasound or MRI findings, and comprehensive systematic appraisal is lacking. Therefore, we conducted a study to examine the clinical manifestations and diagnostic efficacy of ultrasound and MRI in the classification of OSCSTs, with the overarching goal of enhancing the preoperative diagnostic accuracy and subclassification of these enigmatic tumors. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1599/rc).

Methods

Patient population

The study retrospectively examined all consecutive patients who were diagnosed with OSCST at The Third Affiliated Hospital of Zhengzhou University between January 2015 and May 2022. Patients who underwent pelvic MRI within 7 days before surgery, had OSCSTs confirmed by postoperative pathology with clear subclassification, and had complete clinical data were included. Meanwhile, the patients were excluded if any of the following criteria applied: a history of pelvic surgery or radiotherapy or chemotherapy before MRI examination, a lack of critical clinical data, no pathological subclassification, other unrelated malignant tumors of reproductive system, incomplete nonprimary surgery, other synchronous malignancies, and a maximum diameter of the tumor less than 5 mm. Patient information, such as age, menopausal status, symptoms, accompanying details, hormone levels, tumor markers, pathological classification, immunohistochemical staining results, and other relevant data, was gathered via the picture archiving and communication system (PACS) and hospital information system (HIS). A total of 79 OSCST cases were collected, with statistical analysis focusing on granulosa cell tumors, fibromas, and fibrothecomas, sclerosing stromal tumors, and Sertoli-Leydig cell tumors being omitted due to their rarity to prevent bias. The final analysis included 71 patients, comprising 18 OGCTs (23 neoplasms), 19 fibromas (22 neoplasms), and 34 fibrothecomas (36 neoplasms) as shown in Figure 1. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Ethics Committee of The Third Affiliated Hospital of Zhengzhou University (approval No. 2023-252-01). The requirement for informed consent was waived due to the retrospective nature of the analysis.

Figure 1 Flowchart of patient selection. MRI, magnetic resonance imaging; OGCT, ovarian granulosa cell tumor; OSCST, ovarian sex cord-stromal tumor.

Imaging procedure

Preoperative MRI scans were conducted with a MAGNETOM Skyra 3T MR scanner (Siemens Healthineers, Erlangen, Germany) equipped with an 18-channel body surface phased front coil and a SIGNA Pioneer 3.0 T MR scanner (GE HealthCare, Chicago, IL, USA) with an 18-channel body coil. The scan encompassed regions from the umbilicus to the pubic symphysis, with potential extension to the abdomen for larger tumors. Imaging protocols included axial and sagittal T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), coronal T2WI, diffusion-weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI), and contrast-enhanced MRI (CE-MRI). For the Skyra 3T scanner, a dynamic enhancement scan with three-dimensional volumetric interpolated breath-hold examination (3D-VIBE) was performed at 40, 60, 80, 100, and 120 s after intravenous injection of 0.1 mmol/kg of gadopentetate dimeglumine. This was followed by stack-of-stars volumetric interpolated breath-hold examination (STAR-VIBE) for CE-MRI in the coronal, sagittal, and axial planes. For the Pioneer 3T scanner, a three-dimensional differential subsampling with Cartesian ordering (3D-DISCO) sequence was used for DCE-MRI, with 19 phases lasting 13 seconds each postinjection. Subsequently, liver acquisition with volume acceleration (LAVA) was applied for enhanced scans in coronal, sagittal, and axial orientations. The detailed scan parameters can be found in Table 1.

Image analysis

Two experienced diagnostic radiologists, one with 7 years and the other with 17 years of experience, independently reviewed images on the PACS workstation. They documented tumor characteristics, including laterality, maximum diameter, signal features (solid component signal exhibiting hypo-, iso-, or hyperintensity relative to the extrauterine myometrium) of solid regions (T1WI, T2WI, and DWI), morphology, border, and ascites. Ascites distribution was categorized as minimal if within the uterine fossa and rectum, extensive if beyond the uterine fundus, and moderate if in between the sites. Using the postprocessing workstation, radiologists measured the apparent diffusion coefficient (ADC) of the most prominent tumor solid component on the DWI-derived ADC map. A circular or oval region of interest (ROI; 20–30 mm²) was outlined, and the average of three measurements was recorded as the ADC value. During delineation, T2WI, DWI, and enhanced T1WI images were consulted to avoid areas with cystic changes, necrosis, peritumoral vessels, and artifacts. For DCE-MRI scans, the maximum enhancement rate (ERmax) was computed based on signal intensity (SI) with the following formula: ERmax = (SI enhancement – SI plain scan)/SI plain scan × 100%, where SI plain scan represents the precontrast T1WI lesion SI, and SI enhancement is the highest SI postenhancement.

Ultrasound procedure

For ultrasound, the patient underwent bladder emptying and assumed the lithotomy position before the probe was inserted into the vaginal fornix (for married individuals) or the rectum (for unmarried individuals), and scans were conducted with the Voluson E8 color Doppler ultrasound diagnostic device (GE HealthCare). The probe operated at a frequency of 7–10 MHz to assess the mass’s size, shape, and location, along with the presence of ascites. Color Doppler flow imaging (CDFI) was employed to examine vascular morphology and the blood flow patterns surrounding and within the tumor. Two additional clinicians, each with over 5 years of experience in gynecological ultrasound diagnostics, independently analyzed the images. All reviewers were unaware of the histopathological findings, ensuring unbiased evaluation of the imaging data.

Statistical analysis

Statistical analyses were conducted with SPSS version 26.0 (IBM Corp., Armonk, NY, USA) for Windows, MedCalc version 19.1.1 (MedCalc Software, Ostend, Belgium), and Stata version 16 (StataCorp, College Station, TX, USA) at a significance level of α=5% (P<0.05). Graphs were generated via GraphPad Prism version 8.0.2 (Dotmatics, Boston, MA, USA; http://www.graphpad.com/). Initially, normality tests were applied to continuously distributed data, with normally distributed data presented as mean ± standard deviation and nonnormally distributed data as mean with upper and lower quartiles. One-way analysis of variance (ANOVA) was used for normally distributed data and followed by Student-Newman-Keuls q correction for pairwise comparisons. In cases of nonnormal distribution and variance heterogeneity, the Kruskal-Wallis test was employed. Categorical data are described as the number of cases and percentages and were compared between groups via the Chi-squared test or Fisher exact test. Specifically, the Chi-squared test was used for comparisons unless any expected cell count was less than 5, in which case the Fisher exact test was applied. Receiver operating characteristic (ROC) curve analyses were conducted to assess the diagnostic performance of each group. Throughout the statistical analyses, significance was defined as P<0.05. For variables with missing data, the pattern of missingness was first assessed. If the proportion of missing data was very low (<5%), a complete-case analysis (deletion) was applied. For continuous variables with a higher proportion of missing data, mean imputation was used. All analyses were performed based on the processed complete dataset. Some patients had multiple or bilateral neoplasms. To account for the potential clustering effect and nonindependence of lesions from the same patient, all comparative analyses were performed with the generalized linear mixed effects model (GLMM), with tumor site incorporated as a random effect in the model.

Results

Clinical characteristics

A total of 71 patients encompassing 81 neoplasms were included in the analysis. The distribution of these neoplasms across subgroups was as follows: 18 OGCTs (16 single and 2 multiple, totaling 23 masses), 19 fibromas (17 single and 2 multiple, totaling 22 masses), and 34 fibrothecomas (32 single and 2 multiple, totaling 36 masses). The age range of patients with OGCT, fibroma, and fibrothecoma was 13–68 (42.87±11.80), 24–73 (47.05±16.34), and 21–73 (49.94±16.27) years, respectively. In the majority of cases, the primary clinical presentations of OSCSTs were often asymptomatic, incidentally discovered during unrelated physical examinations (53.5%), and were followed in incidence by cases with menstrual irregularities, vaginal bleeding, abdominal pain, and masses (28.2%). Pelvic effusion was present in 43 (60.6%) cases, including 2 cases of Meigs syndrome. Ovarian torsion occurred in 3 cases (2 granulosa cell tumors and 1 fibroma), 2 cases of OGCTs with endometrial carcinoma, and 1 case of breast cancer. Endometrial hyperplasia and polyps were also observed (39.4%). Hormone assessments revealed elevated prolactin in 24.5% of cases, and there was also elevation of thyroid-stimulating hormone (16.9%), testosterone (7.5%), and estradiol (1.9%). In serum tumor marker tests, there was elevation of cancer antigen 125 (CA125), cancer antigen 199 (CA199), and alpha fetoprotein (AFP) in 19.0%, 7.9%, and 4.7% of patients, respectively with the remainder being negative. Immunohistochemical analysis indicated inhibin-α expression was found 61.1% of patients, vimentin in 55.6%, CD99 in 36.1%, calretinin in 30.6%, WT-1 in 30.6%, CD56 in 16.7%, h-caldesmon in 5.6%, and desmin in 5.6%.

Comparative analysis of clinical features among the OGCT, fibroma, and fibrothecoma groups revealed no significant differences in age, primary symptoms, or associated symptoms (P>0.05); however, menopausal status was significantly different (P=0.022), as detailed in Table 2.

In pairwise comparisons of the clinical characteristics of the three groups, a statistically significant difference was found only for menopausal status between the OGCT and fibrothecoma groups (P<0.05). OGCTs were more prevalent in the premenopausal period compared to the postmenopausal period, while fibrothecoma showed a slightly higher incidence in postmenopausal individuals. No significant differences were observed in menopausal status between OGCTs and fibroma, as well as between fibroma and fibrothecoma (P>0.05).

Consistency test

Consistency testing revealed excellent interobserver agreement for maximum diameter, ADC value, and ERmax [intraclass correlation coefficient (ICC) =0.999, 0.923, and 0.997, respectively], as well as excellent intraobserver consistency (ICC =0.999, 0.975, and 0.998, respectively).

Imaging characteristics

In the study, 80 out of 81 masses exhibited clear borders, with only one showing unclear borders. Among these masses, 61 were circular or subcircular, while 20 were lobulated. Cystic necrosis was prevalent in 19 out of 23 OGCTs, with large cystic areas displaying mixed signals such as honeycomb, soap bubble, cheese, and stained-glass effects, often attributed to bleeding at different stages. Regarding imaging characteristics, solid areas within OGCTs typically showed hyperintensity on T2WI, isointensity or slight hypointensity on T1WI, and hyperintensity on DWI, with a median ADC value of 0.862×10³ mm²/s. Ultrasound imaging primarily depicted mixed echoes with minimal blood flow (Figure 2A-2H). Fibromas, observed in 18 out of 22 cases, were mainly solid with well-defined boundaries. The solid regions exhibited hypointensity on T1WI and T2WI, as well as on DWI, with a median ADC value of 1.199×10³ mm²/s, sometimes accompanied by slightly cloudy T2 hyperintensity and slit-like T2 hyperintensity. Ultrasound frequently revealed hypoechoic masses with minimal or absent blood flow (Figure 3A-3H). Fibrothecoma tumors, often presenting as solid or cystic-solid masses, displayed mixed intensity on T2WI. The solid areas showed slight hyper- and hypointensity on T2WI, with cloud-like T2 hyperintensity (theca cells) and a slit-like T2 high signal. Some borders exhibited blood vessels with hypointensity, and the transition between cystic degeneration and solidity was distinct, resembling a yin-yang symbol. The solid regions showed slight hyperintensity or hypointensity on T1WI and slight hyperintensity or hyperintensity on DWI, with a median ADC value of 1.324×10³ mm²/s. Enhanced scans demonstrated continuous mild enhancement in the solid component, while ultrasound typically depicted hypoechoic or mixed echoes with minimal or no blood flow (Figure 4A-4H).

Figure 2 A 35-year-old woman with a left ovarian adult OGCT. Axial T1WI (A) showed multiple hemorrhagic changes (arrow) with a homogeneously isointense solid region, and axial T2WI (B) showed multiple cystic changes (arrow) with a hyperintense solid region. Axial DWI (C) showed a slightly hyperintense solid area (arrow) with more hyperintense hemorrhagic areas, and an ROI drawn on ADC map (D) with the average ADC value measured 0.365×10³ mm²/s (arrow). DCE-MRI of fat-suppressed T1WI (E,F) showed obvious enhancement (arrows). Ultrasound (G) showed a mixed cystic-solid echogenic mass (arrow) with visible blood flow. The histopathology (H&E, 400×) (H) confirmed the diagnosis of an adult OGCT. ADC, apparent diffusion coefficient; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; DWI, diffusion-weighted imaging; H&E, hematoxylin and eosin; OGCT, ovarian granulosa cell tumor; ROI, region of interest; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging.

Figure 3 A 57-year-old woman with a left ovarian fibroma. Axial T1WI and T2WI (A,B) showed a homogeneously hypointense (arrows) solid mass. Axial DWI (C) showed an obvious hypointense mass (arrow), and an ROI drawn on the ADC map (D) had an average ADC value of 0.757×10³ mm²/s (arrow). DCE-MRI of fat-suppressed T1WI (E,F) showed very slight enhancement (arrows). Ultrasound (G) showed a solid hypoechoic mass without blood flow (arrow). The histopathology (H&E, 400×) (H) confirmed the diagnosis of a fibroma. ADC, apparent diffusion coefficient; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; DWI, diffusion-weighted imaging; H&E, hematoxylin and eosin; ROI, region of interest; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging.

Figure 4 A 21-year-old woman with a right ovarian fibrothecoma with Meigs syndrome. Axial T1WI and T2WI (A,B) showed an inhomogeneously isointense (arrows) solid mass. Axial DWI (C) showed a slightly hyperintense mass (arrow), and the ROI on the ADC map (D) had an average ADC value of 1.178×10³ mm²/s (arrow). DCE-MRI of fat-suppressed T1WI (E,F) showed mild enhancement (arrows). Ultrasound (G) showed a solid hypoechoic mass without blood flow (arrow). The histopathology (H&E, 400×) (H) confirmed the diagnosis of fibrothecoma. ADC, apparent diffusion coefficient; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; DWI, diffusion-weighted imaging; H&E, hematoxylin and eosin; ROI, region of interest; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging.

The imaging features of the three groups were compared, encompassing laterality, maximum diameter, signal characteristics (T1WI, T2WI, and DWI) of the solid region, as well as the ADC value, ultrasound echo, and CDFI traits. Findings revealed significant differences in maximum diameter, signal characteristics of the solid region, ADC value, and ultrasound echo traits across the three groups (P<0.05). However, there were no significant distinctions in laterality or CDFI (P>0.05), as shown in Table 3.

In the pairwise comparison of imaging features between the OGCT, fibroma, and fibrothecoma groups, results indicated that the maximum diameter of the fibrothecoma group significantly exceeded that of the fibroma group (P=0.017). No notable difference was observed in the maximum diameter between the OGCT and fibroma groups or between the OGCT and fibrothecoma group (P=0.084 and P>0.99, respectively; Figure 5). A significant difference in MRI signal within the solid region was also observed (P<0.05). The ADC value of the OGCT group was significantly lower than that of the fibroma and fibrothecoma groups, while the fibroma and fibrothecoma groups did not differ in this regard (Figure 5). Differences in ultrasound echo were evident between the OGCT and fibroma groups and between the fibroma and fibrothecoma groups (P<0.001), while no significant difference was observed in blood flow (P=0.298), as illustrated in Table 4. Moreover, the ERmax of the OGCT group was significantly higher than that of the fibroma and fibrothecoma group (P<0.001), while the fibroma and fibrothecoma groups did not differ in this regard (P=0.54; Figure 5).

Figure 5 Bar graph comparing the (A) maximum diameter, (B) ADC value, and (C) ERmax between the OGCT, fibroma, and fibrothecoma groups. ns, not significant (P>0.05); **, P<0.05; ***, P<0.001. ADC, apparent diffusion coefficient; ERmax, maximum enhancement rate; OGCT, ovarian granulosa cell tumor.

The area under the curve (AUC) values for ERmax in differentiating between OGCT and fibroma, OGCT and fibrothecoma, and fibroma and fibrothecoma were 0.929, 0.898, and 0.524, respectively (Figure 6). Maximum diameter, T1WI, T2WI, DWI, and ADC served as MRI parameters, while echo functioned as the ultrasound parameter. The AUC values for MRI, ultrasound, and the combination of MRI and ultrasound in distinguishing granulosa cell tumors from fibroma were 0.998, 0.882, and 1.000, respectively; for distinguishing granulosa cell tumors from fibrothecoma, the AUC values were 0.960, 0.645, and 0.969, respectively; and for distinguishing fibroma from fibrothecoma, the AUC values were 0.918, 0.785, and 0.970, respectively (Figure 6). The diagnostic efficacy of the combination was slightly greater than that of MRI, and that of MRI was significantly superior to that of ultrasound (P<0.05). Due to the imbalanced and limited sample sizes, further investigation of subgroup comparisons requires larger sample sizes to validate the efficacy of the above indicators.

Figure 6 ROC curves for the comparison of ERmax and ultrasound, MRI, and their combination between the OGCT, fibroma, and fibrothecoma groups, respectively. (A-C) ROC curves for the comparison of ERmax between the OGCT and fibroma, OGCT and fibrothecoma, and the fibroma and fibrothecoma groups. (D-F) ROC curves for the comparison of ultrasound, MRI, and their combination between the OGCT and fibroma, OGCT and fibrothecoma, and the fibroma and fibrothecoma groups. ERmax, maximum enhancement rate; MRI, magnetic resonance imaging; OGCT, ovarian granulosa cell tumor; ROC, receiver operating characteristic; US, ultrasound.

A GLMM was applied via Stata 16 to examine the risk factors of OGCT, fibroma, and fibrothecoma, with the tumor site incorporated as a random effect in the model. A two-sided P value of 0.05 or lower was regarded as significant. The analysis revealed that maximum (P=0.386), echo (P=0.713), and DWI (P=0.510) were not significant risk factors for OGCT, fibroma, or fibrothecoma; meanwhile, ADC (P=0.01), T1WI (P=0.01), and T2WI (P=0.008) features were significant (Table 5), with the highest odds ratio (OR) value for ADC [2.01; 95% confidence interval (CI): 0.482–3.539], followed by T2WI (1.225; 95% CI: 0.318–2.131) and T1WI (−1.879; 95% CI: 2.45–7.60).

Discussion

OSCSTs are a rare and diverse group of ovarian tumors, encompassing various subtypes with distinct histological characteristics and biological behaviors. According to the WHO’s histological classification of ovarian tumors, OSCSTs are typically classified into three categories: pure stromal tumors, pure sex cord tumors, and mixed sex cord-stromal tumors (6) [with minor revisions in the fifth edition (2020) compared to the fourth Edition (6)]. Common OSCSTs include OGCTs, fibrothecoma, fibroma, and related types, sometimes collectively referred to as the thecoma-fibroma group (5). The intricate imaging features of OSCSTs often lead to them being misdiagnosed as uterine fibroids, cystadenomas, endometriomas, or even ovarian cancer, potentially impacting treatment strategies. In our study, misdiagnoses included cases mistaken for cystadenomas (10 cases), subserosal or broad ligament fibroids (8 cases), endometriomas (5 cases), cystadenocarcinoma (5 cases), dysgerminoma (2 cases), and hydrosalpinx (2 cases). The elevated misdiagnosis rate may stem from inadequate familiarity with OSCST imaging manifestations, particularly in cases of large tumors for which identifying the origin or distinguishing numerous cystic, necrotic, and hemorrhagic components proves challenging. Recognition of the clinical, immunohistochemical, and imaging features of OSCSTs is vital for the accurate diagnosis and classification of these tumors.

Clinical characteristics

Ovarian fibroma, fibrothecoma, and OGCT are more prevalent in perimenopausal women, while juvenile granulosa cell tumors are typically found in individuals under 30 years old. In our study, patients with OGCTs ranged from 13 to 68 (42.87±11.80) years, with one of juvenile OGCT in a 13-year-old. Patients with fibroma were between 24 and 73 (47.05±16.34) years, and those with fibrothecoma were from 21 to 73 (49.94±16.27) years, aligning with other work (7). OSCSTs can manifest as asymptomatic or incidentally detected nonfunctioning ovarian tumors during routine exams. Larger masses may present with symptoms such as adnexal mass, abdominal distension, abdominal pain (8) or exhibit hormone-related manifestations due to estrogen or androgen production (5). Estrogen-producing OSCSTs may lead to menstrual irregularities, postmenopausal bleeding, endometrial hyperplasia, or carcinoma, while testosterone-producing OSCSTs can give rise to androgen-related symptoms such as amenorrhea, hirsutism, and acne (9). OGCTs, due to estrogen production, may be associated with endometrial carcinoma. In our study, we observed endometrial carcinoma in 2 patients and breast cancer in 1 case, consistent with previous literature (10,11). Three cases in our cohort presented with abdominal pain, later confirmed during surgery as torsioned OSCSTs, likely attributed to the large lesion size.

Hormones and serum tumor markers play a significant role in the evaluation of ovarian tumors. Estradiol, a key hormone produced by OGCTs in the presence of theca cells, is elevated in approximately 70% of OGCT cases (9,12). In our study, among hormones, elevation of prolactin was the most prevalent (24.5%), followed by testosterone (7.5%) and estradiol (1.9%). This finding suggests that elevation of estradiol is not the most common type of hormone elevation, which is not corroborated by the literature. This relatively low proportion may be explained by OSCSTs lacking theca cells in the tumor stroma or by the limited number of participants in this study, and further confirmation through expanded case collection is necessary. Among serum tumor markers, CA125 elevation was most commonly found in patients (19.0%), followed by that of CA199 (7.9%) and AFP (4.7%). Research by Nasioudis et al. (13) indicated that elevated preoperative CA125 levels in patients with early-stage OSCST are linked to poorer survival outcomes.

The immunohistochemical characteristics of OSCSTs play a crucial role in diagnosis due to the wide age range and variability in tissue morphology associated with these tumors. Immunohistochemical markers such as inhibin, calretinin, WT-1, and SF-1 are valuable for diagnostic purposes. However, certain OSCST subtypes may exhibit overlapping immunohistochemical features. Inhibin, produced by ovarian granulosa cells, is critical to regulating pituitary follicle-stimulating hormone secretion. Inhibin serves as a tumor marker for primary OGCTs and recurrent tumors (14). Among markers, inhibin-α expression was the most prevalent (61.1%), followed by vimentin (55.6%), CD99 (36.1%), calretinin (30.6%), and WT-1 (30.6%), which is in line with the literature (12,14).

Clinical characteristics did not significantly differ between the OGCT, fibroma, and fibrothecoma groups, consistent with the findings reported by Nagawa et al. (15), indicating limited utility in differential diagnosis based on clinical features. Notably, OGCT, as compared to fibrothecoma, was more prevalent in postmenopausal women in our study, possibly due to the higher occurrence of adult OGCTs during the perimenopausal period.

Imaging features

Owing to the excellent soft tissue resolution and nonionizing radiation of MRI, it is extensively employed for assessing adnexal neoplasms that have ambiguous findings on ultrasound or computed tomography scans. OSCSTs, characterized by benign or low-grade malignant behavior with minimal invasiveness, typically manifest as well-defined and regular masses on MRI.

In this study, 1 case with an unclear boundary was attributed to concurrent endometrioma, while 21 cases with irregular masses were deemed lobulated due to their significant size. OGCTs exhibit a spectrum of presentations ranging from purely solid to entirely cystic masses with diverse morphologies. Notably, a multilocular cystic mass filled with blood is recognized as a characteristic MRI sign of OGCT (16). Among the cases examined in our study, 4 (4/23) were purely cystic, 3 (3/23) were purely solid, and 16 (16/23) exhibited cystic degeneration and hemorrhage. MRI of multilocular cystic masses often displayed sponge-like, soap-bubble-like, cheese-like, and stained-glass-like appearances due to hemorrhagic components at varying stages, aligning with literature indicating a greater heterogeneity of OGCTs compared to fibroma and fibrothecoma (16). Furthermore, 5 cases of OGCTs were initially misdiagnosed as endometriotic cysts due to the presence of cystic degeneration and hemorrhagic elements. The solid regions of OGCTs demonstrated hyperintensity on DWI. This is in line with a previous study in which ADCs were heavily affected by T2 relaxation time (17), which can be attributed to dense cellular membranes limiting water molecule diffusion and reducing the ADC value. Fibromas typically exhibit hypointensity on T2WI due to fibroblast proliferation and fiber hyperplasia (18). A portion of fibromas display patchy slightly hyperintense signals on T2WI, indicating mild cellular degeneration and edema. Within our cohort, 18 (18/22, 81.8%) cases displayed hypointensity on T2WI, while 6 cases exhibited patch-like slightly hyperintense signals on T2WI. In contrast to those of fibromas, the solid regions of fibrothecoma exhibited hypointensity or slight hyperintensity on T2WI, reflecting the presence of theca cells and a susceptibility to cystic degeneration. The signal intensity of fibrothecoma depended on the theca cell-to-fibroblast ratio, with the lipid-rich theca cells leading to hyperintensity on T2WI. Higher theca cell content corresponds to a higher T2WI signal, while increased fibroblast content is associated with a lower T2WI signal due to the impact of fibrous content on hypointensity extent. In our study, fibrothecoma cases exhibited hypointensity (13/36, 36.1%) or slight hypointensity (23/36, 63.9%) on T2WI. On DWI, the solid regions of fibroma and fibrothecoma predominantly displayed hypointensity, with fibrothecoma occasionally showing slight hyperintensity. On enhancement scans, solid regions of granulosa cell tumor exhibited marked enhancement, whereas fibroma and fibrothecoma had minimal or slight delayed enhancement, consistent with previous research (16,19,20).

Statistical analysis (Table 4, Figure 6) revealed no significant differences in laterality or CDFI between the three groups. Ultrasound predominantly depicted hypoechoic masses with minimal or absent blood flow, aligning with the work be Jiang et al. (21). Differences in echo patterns across the groups were presumed to be linked to tumor composition. There was no significant disparity in the maximum diameter of granulosa cell tumors compared to that of fibromas, while fibrothecomas exhibited a larger maximum diameter than did fibromas, deviating slightly from previous research (16,19). Significant differences were observed in T1WI, T2WI, and DWI signals in the solid regions between the three groups, which is consistent with the literature (20). Additionally, the ADC value of the granulosa cell group was notably lower than that of the fibroma and fibrothecoma groups. Although there were differences between the fibroma and fibrothecoma groups, this was relatively slightly, suggesting higher cell density in OGCTs compared to fibromas and fibrothecomas. The ADC value proved valuable in distinguishing OGCT from fibroma and fibrothecoma, corroborating the findings of Zhang et al. (22). ERmax, calculated based on the signal intensity of DCE-MR images, indicated the vascularity of tumors, with a higher ERmax reflecting a more hypervascular tumor. Notably, this study represents the first analysis of the diagnostic efficacy of the ERmax quantitative parameter for common OSCSTs. The ERmax of the OGCT group significantly exceeded that of the fibroma and fibrothecoma groups, with no statistically significant difference between the latter two groups. OGCTs tended to exhibit higher vascularity, while fibromas and fibrothecomas typically presented as hypovascular tumors, despite having overlapping symptoms. It should be noted that these findings were derived from small and imbalanced subgroups (especially the comparison of OGCTs, fibromas, and fibrothecoma), and this study should be considered preliminary and exploratory, with future validation in larger, prospective cohorts being necessary.

Our study involved several other limitations that should be acknowledged. To begin, the retrospective and single-center design introduced the potential for selection bias. Moreover, our cohort consisted exclusively of patients who underwent surgical resection with pathological confirmation. Consequently, our sample may underrepresent patients with smaller, asymptomatic, or incidentally discovered OSCST who might be managed conservatively or with surveillance. This selection criterion likely means our findings are most applicable to patients presenting with symptoms or larger tumors necessitating surgical intervention. Therefore, the generalizability of our results to the entire spectrum of patients with OSCST in the broader population may be limited. Despite this, by providing detailed clinical and pathological data on a substantial number of surgically managed cases, our study offers valuable insights into the characteristics and outcomes of this important patient subgroup. Furthermore, the sample size for our enhanced scans was small, immunohistochemical features were not incorporated into the statistical analysis, and only relatively common OSCSTs were included. Future efforts will focus on expanding the study to encompass a broader spectrum of cases, including the differentiation between benign and malignant OSCSTs and distinguishing OSCSTs from other ovarian malignancies. Further work will also leverage radiomics to mitigate potential deviations stemming from subjective human factors.

Conclusions

Menopausal status differed significantly among the OSCST subtypes. Imaging modalities such as MRI and ultrasound proved to be of considerable value in the preoperative diagnosis and classification of prevalent OSCSTs. ERmax emerged as a promising quantitative indicator for distinguishing OGCTs from fibroma and fibrothecoma, demonstrating superior diagnostic efficacy when used independently. The combined use of MRI and ultrasound yielded enhanced utility in the preoperative diagnosis and classification of common OSCSTs as compared to ultrasound or MRI used alone. Notably, MRI in isolation demonstrated comparable diagnostic accuracy to the combined approach.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1599/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1599/dss

Funding: This study was funded by the Tianjian Laboratory of Advanced Biomedical Sciences and Major Project of Medical Science and Technology Jointly Constructed by the Provincial and Ministerial Departments (No. SBGJ202101020).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1599/coif). K.W. is an employee of MR Research China, GE Healthcare. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Third Affiliated Hospital of Zhengzhou University (No. 2023-252-01) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Nakai G, Yamada T, Yamamoto K, Hirose Y, Ohmichi M, Narumi Y. MRI appearance of ovarian serous borderline tumors of the micropapillary type compared to that of typical ovarian serous borderline tumors: radiologic-pathologic correlation. J Ovarian Res 2018;11:7. [Crossref] [PubMed]
2. Hauptmann S, Friedrich K, Redline R, Avril S. Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria. Virchows Arch 2017;470:125-42. [Crossref] [PubMed]
3. Chen VW, Ruiz B, Killeen JL, Coté TR, Wu XC, Correa CN. Pathology and classification of ovarian tumors. Cancer 2003;97:2631-42. [Crossref] [PubMed]
4. He G, Zhao J, Yang Z, Zhao Z, Bai Y, Xiong W. Comparison of image features and diagnostic value of color Doppler ultrasound and two-dimensional ultrasound in the diagnosis of ovarian sex cord-stromal tumors. Oncol Lett 2020;20:1671-6. [Crossref] [PubMed]
5. Jung SE, Rha SE, Lee JM, Park SY, Oh SN, Cho KS, Lee EJ, Byun JY, Hahn ST. CT and MRI findings of sex cord-stromal tumor of the ovary. AJR Am J Roentgenol 2005;185:207-15. [Crossref] [PubMed]
6. Cree IA, White VA, Indave BI, Lokuhetty D. Revising the WHO classification: female genital tract tumours. Histopathology 2020;76:151-6. [Crossref] [PubMed]
7. Inada Y, Nakai G, Yamamoto K, Yamada T, Hirose Y, Terai Y, Ohmichi M, Narumi Y. Rapidly growing juvenile granulosa cell tumor of the ovary arising in adult: a case report and review of the literature. J Ovarian Res 2018;11:100. [Crossref] [PubMed]
8. Monget P, McNatty K, Monniaux D. The Crazy Ovary. Genes (Basel) 2021;12:928. [Crossref] [PubMed]
9. Levin G, Zigron R, Haj-Yahya R, Matan LS, Rottenstreich A. Granulosa cell tumor of ovary: A systematic review of recent evidence. Eur J Obstet Gynecol Reprod Biol 2018;225:57-61. [Crossref] [PubMed]
10. Nemeth AJ, Patel SK. Meigs syndrome revisited. J Thorac Imaging 2003;18:100-3. [Crossref] [PubMed]
11. Nasioudis D, Wilson E, Mastroyannis SA, Sisti G, Haggerty AF, Ko EM, Latif NA. Increased Risk of Breast and Uterine Cancer Among Women With Ovarian Granulosa Cell Tumors. Anticancer Res 2019;39:4971-5. [Crossref] [PubMed]
12. François CM, Wargnier R, Petit F, Goulvent T, Rimokh R, Treilleux I, Ray-Coquard I, Zazzu V, Cohen-Tannoudji J, Guigon CJ. 17β-estradiol inhibits spreading of metastatic cells from granulosa cell tumors through a non-genomic mechanism involving GPER1. Carcinogenesis 2015;36:564-73. [Crossref] [PubMed]
13. Nasioudis D, Wilson E, Mastroyannis SA, Latif NA. Prognostic significance of elevated pre-treatment serum CA-125 levels in patients with stage I ovarian sex cord-stromal tumors. Eur J Obstet Gynecol Reprod Biol 2019;238:86-9. [Crossref] [PubMed]
14. Lappöhn RE, Burger HG, Bouma J, Bangah M, Krans M, de Bruijn HW. Inhibin as a marker for granulosa-cell tumors. N Engl J Med 1989;321:790-3. [Crossref] [PubMed]
15. Nagawa K, Kishigami T, Yokoyama F, Murakami S, Yasugi T, Takaki Y, Inoue K, Tsuchihashi S, Seki S, Okada Y, Baba Y, Hasegawa K, Yasuda M, Kozawa E. Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors. J Ovarian Res 2022;15:65. [Crossref] [PubMed]
16. Horta M, Cunha TM. Sex cord-stromal tumors of the ovary: a comprehensive review and update for radiologists. Diagn Interv Radiol 2015;21:277-86. [Crossref] [PubMed]
17. Wáng YXJ, Ma FZ. A tri-phasic relationship between T2 relaxation time and magnetic resonance imaging (MRI)-derived apparent diffusion coefficient (ADC). Quant Imaging Med Surg 2023;13:8873-80. [Crossref] [PubMed]
18. Valentini AL, Gui B, Miccò M, Mingote MC, De Gaetano AM, Ninivaggi V, Bonomo L. Benign and Suspicious Ovarian Masses-MR Imaging Criteria for Characterization: Pictorial Review. J Oncol 2012;2012:481806. [Crossref] [PubMed]
19. Javadi S, Ganeshan DM, Jensen CT, Iyer RB, Bhosale PR. Comprehensive review of imaging features of sex cord-stromal tumors of the ovary. Abdom Radiol (NY) 2021;46:1519-29. [Crossref] [PubMed]
20. Fang M, Dong J, Zhong Q, Fang X, Chen Y, Wang C, Yan H. Value of diffusion-weighted imaging combined with conventional magnetic resonance imaging in the diagnosis of thecomas and their differential diagnosis with adult granulosa cell tumors. Acta Radiol 2019;60:1532-42. [Crossref] [PubMed]
21. Jiang MJ, Le Q, Yang BW, Yuan F, Chen H. Ovarian sex cord stromal tumours: analysis of the clinical and sonographic characteristics of different histopathologic subtypes. J Ovarian Res 2021;14:53. [Crossref] [PubMed]
22. Zhang H, Zhang H, Gu S, Zhang Y, Liu X, Zhang G. MR findings of primary ovarian granulosa cell tumor with focus on the differentiation with other ovarian sex cord-stromal tumors. J Ovarian Res 2018;11:46. [Crossref] [PubMed]