A diagnostic challenge of seromucinous borderline tumor: A case report

MR Relaxometry for Discriminating Malignant Ovarian Cystic Tumors: A Prospective Multicenter Cohort Study

BACKGROUND

Endometriosis-associated ovarian cancer (EAOC) is a well-known type of cancer that arises from ovarian endometrioma (OE). OE contains iron-rich fluid in its cysts due to repeated hemorrhages in the ovaries. However, distinguishing between benign and malignant tumors can be challenging. We conducted a retrospective study on magnetic resonance (MR) relaxometry of cyst fluid to distinguish EAOC from OE and reported that this method showed good accuracy. The purpose of this study is to evaluate the accuracy of a non-invasive method in re-evaluating pre-surgical diagnosis of malignancy by a prospective multicenter cohort study.

METHODS

After the standard diagnosis process, the R2 values were obtained using a 3T system. Data on the patients were then collected through the Case Report Form (CRF). Between December 2018 and March 2023, six hospitals enrolled 109 patients. Out of these, 81 patients met the criteria required for the study.

RESULTS

The R2 values calculated using MR relaxometry showed good discriminating ability with a cut-off of 15.74 (sensitivity 80.6%, specificity 75.0%, AUC = 0.750, p < 0.001) when considering atypical or borderline tumors as EAOC. When atypical and borderline cases were grouped as OE, EAOC could be distinguished with a cut-off of 16.87 (sensitivity 87.0%, specificity 61.1%).

CONCLUSIONS

MR relaxometry has proven to be an effective tool for discriminating EAOC from OE. Regular use of this method is expected to provide significant insights for clinical practice.

Clinicopathological characteristics, molecular features and novel diagnostic strategies for the detection of malignant transformation of endometriosis (Review)

Endometriosis is a benign gynecological disease that affects women of reproductive age. Although malignant transformation of endometriosis is rare, physicians must be aware of this due to the high incidence of clear cell carcinoma of the ovary (CCC) in Japan. The most prevalent histological subtype of ovarian cancer is CCC (~70%) followed by endometrioid carcinoma (30%). The present review discusses the clinicopathological and molecular features of endometriosis-associated ovarian cancer (EAOC) as well as prospects for novel diagnostic strategies. Papers published between 2000 and 2022 in the PubMed and Google Scholar databases were included. Contents of the endometriotic cyst fluid may be involved in carcinogenesis, although the underlying mechanisms are largely unknown. Some studies have proposed a possible mechanism wherein excessive hemoglobin, heme and iron could cause an imbalance in intracellular redox homeostasis in endometriotic cells. Combined with DNA damage and mutations, the imbalances may induce the development of EAOC. Endometriotic cells evolve to adapt to the prolonged unfavorable oxidative microenvironmental stress. On the other hand, macrophages enhance the antioxidative defense mechanism and protect endometriotic cells against oxidative damage through intercellular crosstalk and signaling pathways. Therefore, changes in redox signaling, energy metabolism and the tumor immune microenvironment could be the key elements in the malignant transformation of certain endometriotic cell clones. Additionally, non-invasive bioimaging (i.e., magnetic resonance relaxometry) and biomarkers (i.e., tissue factor pathway inhibitor 2) may be promising tools for early-stage detection of the disease. In conclusion, the present review summarizes the latest advancements in research on the biological characteristics and early diagnosis of malignant transformation of endometriosis.

Whole-tumor ADC histogram analysis for differentiating endometriosis-related tumors: seromucinous borderline tumor, clear cell carcinoma and endometrioid carcinoma

PURPOSE

To investigate the feasibility of whole-tumor apparent diffusion coefficient (ADC) histogram analysis for improving the differentiation of endometriosis-related tumors: seromucinous borderline tumor (SMBT), clear cell carcinoma (CCC) and endometrioid carcinoma (EC).

METHODS

Clinical features, solid component ADC (ADC_SC) and whole-tumor ADC histogram-derived parameters (volume, the ADC_mean, 10th, 50th and 90th percentile ADCs, inhomogeneity, skewness, kurtosis and entropy) were compared among 22 SMBTs, 42 CCCs and 21 ECs. Statistical analyses were performed using chi-square test, one-way ANOVA or Kruskal-Wallis test, and receiver operating characteristic curves.

RESULTS

A significantly higher ADC_SC and smaller volume were associated with SMBT than with CCC/EC. The ADC_mean was significantly higher in CCC than in EC. The 10th percentile ADC was significantly lower in EC than in SMBT/CCC. The 50th and 90th percentile ADCs were significantly higher in CCC than in SMBT/EC. For differentiating SMBT from CCC, AUCs of the ADC_SC, volume, and 50th and 90th percentile ADCs were 0.97, 0.86, 0.72 and 0.81, respectively. For differentiating SMBT from EC, AUCs of the ADC_SC, volume and 10th percentile ADC were 0.97, 0.71 and 0.72, respectively. For differentiating CCC from EC, AUCs of the ADC_mean and 10th, 50th and 90th percentile ADCs were 0.79, 0.72, 0.81 and 0.85, respectively.

CONCLUSION

Whole-tumor ADC histogram analysis was valuable for differentiating endometriosis-related tumors, and the 90th percentile ADC was optimal in differentiating CCC from EC.

The Endometriotic Neoplasm Algorithm for Risk Assessment (e-NARA) Index Sheds Light on the Discrimination of Endometriosis-Associated Ovarian Cancer from Ovarian Endometrioma

BACKGROUND

Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate endometriosis-associated ovarian cancer (EAOC) from ovarian endometrioma (OE) with high accuracy. However, this method has a limitation in discriminating malignancy in clinical use because the R2 value depends on the device manufacturer and repeated imaging is unrealistic. The current study aimed to reassess the diagnostic accuracy of MR relaxometry and investigate a more powerful tool to distinguish EAOC from OE.

METHODS

This retrospective study was conducted at our institution from December, 2012, to May, 2022. A total of 150 patients were included in this study. Patients with benign ovarian tumors (n = 108) mainly received laparoscopic surgery, and cases with suspected malignancy (n = 42) underwent laparotomy. Information from a chart review of the patients' medical records was collected.

RESULTS

A multiple regression analysis revealed that the age, the tumor diameter, and the R2 value were independent malignant predicting factors. The endometriotic neoplasm algorithm for risk assessment (e-NARA) index provided high accuracy (sensitivity, 85.7%; specificity, 87.0%) to discriminate EAOC from OE.

CONCLUSIONS

The e-NARA index is a reliable tool to assess the probability of malignant transformation of endometrioma.

Current update on malignant epithelial ovarian tumors

Epithelial ovarian cancer (EOC) represents the most frequently occurring gynecological malignancy, accounting for more than 70% of ovarian cancer deaths. Preoperative imaging plays an important role in assessing the extent of disease and guides the next step in surgical decision-making and operative planning. In this article, we will review the multimodality imaging features of various subtypes of EOC. We will also discuss the role of imaging in the staging, management, and surveillance of EOC.

MR findings for differentiating decidualized endometriomas from seromucinous borderline tumors of the ovary

PURPOSE

Decidualized endometriomas (DEs) and seromucinous borderline tumors (SMBTs) exhibit similar MR findings including markedly hyperintense mural nodules within endometriotic cysts on T2-weighted images. The present study aimed to assess the efficacy of MR imaging for differentiating between DEs and SMBTs of the ovary.

MATERIALS AND METHODS

MR images of 8 DEs and 14 SMBTs were retrospectively assessed and compared according to pathologies.

RESULTS

With regard to quantitative assessments of mural nodules, the number and signal intensity ratios (SIRs) on T1-weighted images were significantly greater in DEs than in SMBTs (11.0 ± 8.4 vs. 4.3 ± 4.1, p < 0.05 and 2.36 ± 0.56 vs. 1.49 ± 0.27, p < 0.01, respectively), whereas the height was significantly lower in DEs than in SMBTs (4.5 ± 1.4 mm vs. 21.9 ± 11.4 mm, p < 0.01). However, there were no significant differences between DEs and SMBTs in the SIRs on T2-weighted images, SIRs on diffusion-weighted images, and apparent diffusion coefficient values. With regard to qualitative assessments of mural nodules, the lobulated margin, pedunculated configuration, and T2 hypointense core were significantly more frequent in SMBTs than in DEs (71% vs. 0%, p < 0.01; 86% vs. 0%, p < 0.01; and 43% vs. 0%, p < 0.05, respectively).

CONCLUSION

The number, height, SIRs on T1-weighted images, lobulated margin, pedunculated configuration, and T2 hypointense core of mural nodules within endometriotic cysts were useful MR findings for differentiating DEs from SMBTs.