Diffusion-weighted MR imaging findings of ovarian adenocarcinofibromas and adenofibromas

MRI combined with clinical features to differentiate ovarian thecoma-fibroma with cystic degeneration from ovary adenofibroma

OBJECTIVE

To explore the value of magnetic resonance imaging (MRI) and clinical features in identifying ovarian thecoma-fibroma (OTF) with cystic degeneration and ovary adenofibroma (OAF).

METHODS

A total of 40 patients with OTF (OTF group) and 28 patients with OAF (OAF group) were included in this retrospective study. Univariable and multivariable analyses were performed on clinical features and MRI between the two groups, and the receiver operating characteristic (ROC) curve was plotted to estimate the optimal threshold and predictive performance.

RESULTS

The OTF group had smaller cyst degeneration degree (P < .001), fewer black sponge sign (20% vs. 53.6%, P = .004), lower minimum apparent diffusion coefficient value (ADCmin) (0.986 (0.152) vs. 1.255 (0.370), P < .001), higher age (57.4 ± 14.2 vs. 44.1 ± 15.9, P = .001) and more postmenopausal women (72.5% vs. 28.6%, P < .001) than OAF. The area under the curve of MRI, clinical features and MRI combined with clinical features was 0.870, 0.841, and 0.954, respectively, and MRI combined with clinical features was significantly higher than the other two (P < .05).

CONCLUSION

The cyst degeneration degree, black sponge sign, ADCmin, age and menopause were independent factors in identifying OTF with cystic degeneration and OAF. The combination of MRI and clinical features has a good effect on the identification of the two.

ADVANCES IN KNOWLEDGE

This is the first time to distinguish OTF with cystic degeneration from OAF by combining MRI and clinical features. It shows the diagnostic performance of MRI, clinical features, and combination of the two. This will facilitate the discriminability and awareness of these two diseases among radiologists and gynaecologists.

MRI of Borderline Epithelial Ovarian Tumors: Pathologic Correlation and Diagnostic Challenges

Borderline epithelial ovarian tumors are a distinct pathologic entity characterized by increased epithelial proliferation and nuclear atypia, but without frank stromal invasion. Borderline tumor (BT) is now considered to represent an intermediate phase in the stepwise progression from benign to malignant ovarian epithelial tumor. Since BTs commonly manifest at early stages in women of reproductive age and are associated with a good prognosis, making the correct diagnosis is important in determining whether a patient is a candidate for fertility-sparing surgery. There are six histologic BT subtypes (serous, mucinous, seromucinous, endometrioid, clear cell, and Brenner), and each has different MRI features, reflecting their unique histologic architectures. Radiologists should be aware of the MRI features that can suggest BTs. These features include a hyperintense papillary architecture with hypointense internal branching, which can be observed with serous and seromucinous BTs on T2-weighted images; aggregates of microcysts that have hypointensity on T2-weighted images and reticular enhancement on contrast-enhanced T2-weighted images, which can be seen with mucinous BTs; and moderately high signal intensity on diffusion-weighted images along with relatively high apparent diffusion coefficient values, which can be observed regardless of the histologic subtype. Nevertheless, because the imaging features of BTs overlap with those of many benign lesions (eg, cystadenoma and cystadenofibroma, decidualized endometriosis, and polypoid endometriosis) and malignant tumors (ovarian cancers and metastases), histologic confirmation is required for the final diagnosis. Special emphasis is placed on the MRI features of BTs, pathologic correlation, and the challenges related to diagnosis. ^©RSNA, 2022.

The Value of Diffusion-Weighted Imaging in the Differential Diagnosis of Ovarian Lesions: A Meta-Analysis

OBJECTIVES

The ability of contrast-enhanced MRI to distinguish between malignant and benign ovarian masses is limited. The aim of this meta-analysis is to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) in differentiating malignant from benign ovarian masses.

METHODS

A comprehensive literature search was performed in several authoritative databases to identify relevant articles. The weighted mean difference (WMD) and corresponding 95% confidence interval (95% CI) were calculated. We also used subgroup analysis to analyze study heterogeneity, and evaluated publication bias.

RESULTS

The meta-analysis is based on 21 studies, which reported the findings for 731 malignant and 918 benign ovarian masses. There was no significant difference in apparent diffusion coefficient (ADC) values for DWI between benign and malignant lesions (WMD = 0.22, 95% CI = -0.02-0.47, p = 0.08). Subgroup analysis by benign tumor type revealed higher ADC values (or a trend toward higher values) for cysts, cystadenomas and other benign tumors compared to malignant masses (cyst: WMD = 0.54, 95% CI = -0.05-1.12, p = 0.07; cystadenoma: WMD = 0.73, 95% CI = 0.38-1.07, p < 0.0001; other benign tumor: WMD = 0.16, 95% CI = -0.13-0.46, p = 0.28). On the other hand, lower ADC values (or a trend toward lower values) were observed for endometrioma and teratoma compared to malignant masses (endometrioma: WMD = -0.09, 95% CI = -0.47-0.29, p = 0.64; teratoma: WMD = -0.49, 95% CI = -0.85-0.12, p = 0.009). Subgroup analysis by mass property revealed higher ADC values in cystic tumor types than in solid types for both benign and malignant tumors. Significant study heterogeneity was observed. There was no notable publication bias.

CONCLUSIONS

Quantitative DWI is not a reliable diagnostic method for differentiation between benign and malignant ovarian masses. This knowledge is essential in avoiding misdiagnosis of ovarian masses.