Borderline Epithelial Ovarian Tumors Research Articles

Immunohistochemical expression of Beclin-1 and LC3B in benign and borderline ovarian tumors

Background Epithelial ovarian tumors account for ⁓90% of ovarian cancers. Recently conducted studies have demonstrated autophagy role in tumor development and progression. Autophagic markers include Beclin-1, essential for autophagosome formation and LC3B, required for the elongation step during autophagy. Aim To investigate Beclin-1 and LC3B expression in benign and borderline epithelial ovarian tumors along with its relation to clinicopathologic parameters. Materials and methods Thirty-six cases of epithelial ovarian neoplasms were subjected to hematoxylin and eosin staining and immunohistochemical staining with Beclin-1 and LC3B. Results Beclin-1 was expressed in the nucleus and/or the cytoplasm of tumor cells. The cytoplasmic expression of Beclin-1 was significantly more frequent in borderline cases compared with benign tumors. High Beclin-1 cytoplasmic expression was significantly associated with tumor size, gross appearance, and tumor histological type. Benign Brenner tumors were the only benign tumors expressing cytoplasmic Beclin-1 localization. Regarding LC3B expression, nuclear and cytoplasmic subcellular localizations were also detected. Cytoplasmic LC3B localization was significantly more frequent in the borderline groups. A significant relation was observed between high cytoplasmic LC3B expression and tumor size, tumor gross appearance, and histological type. The majority of benign Brenner tumors showed a high cytoplasmic LC3B expression. Conclusions The expression of Beclin-1 and LC3B varies in benign versus borderline epithelial ovarian tumors. Cytoplasmic expression is predominant in borderline tumors. Beclin-1 and LC3B cytoplasmic expression is significantly high in small-sized and solid benign tumors. Benign Brenner tumors are the only benign tumors showing cytoplasmic Beclin-1 and LC3B localization.

Fertility preservation options in epithelial ovarian cancer and borderline epithelial ovarian tumor

Fertility preservation options in epithelial ovarian cancer and borderline epithelial ovarian tumor

Role of protein tyrosine phosphatase receptor type M in epithelial ovarian cancer progression

BackgroundEpithelial ovarian cancer (EOC) is often diagnosed at advanced stages with low survival rates. Protein tyrosine phosphatase receptor type M (PTPRM) is involved in cancer development and progression; however, its role in EOC remains unclear. In this study,we aimed to detect PTPRM expression in ovarian epithelial tumors, analyze its relationship with the clinicopathological features and survival prognosis of patients with EOC, and provide a theoretical basis for new targets for EOC treatment. Fifty-seven patients with EOC treated at our hospital between January 2012–January 2014 were included; along with 18 borderline and 30 benign epithelial ovarian tumors and 15 normal ovarian and uterine tube tissue samples from patients surgically treated at our hospital during the same period. PTPRM expression was immunohistochemically detected, and we analyzed its relationship with clinicopathological features and prognosis. Associations between PTPRM expression and survival prognosis of patients with EOC were analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier Plotter databases.ResultsPTPRM had the highest expression rates in normal ovarian and uterine tube tissues, followed by benign and borderline epithelial ovarian tumors; the lowest positive expression rate was observed in EOC tumors. PTPRM expression differed significantly among groups (P < 0.05). The positive PTPRM expression rate significantly decreased with age, progressing clinical stage, and tumor recurrence, and the larger the mass diameter, the higher the positive PTPRM expression rate. PTPRM expression was significantly lower in ovarian cancer compared with that in normal tissues in the GEPIA database (P < 0.05). The overall survival (OS) and disease-free survival(DFS) rates were higher in the PTPRM high-expression group, with statistically significant (P < 0.05) and insignificant (P > 0.05) differences, respectively. The OS rate of the high-expression group compared with the low-expression group in the Kaplan–Meier Plotter database was higher, although without statistical significance (P > 0.05), and progression-free survival(PFS) was higher with statistical significance (P < 0.05).ConclusionPTPRM expression was low in patients with EOC, and the PTPRM positive-expression rate significantly decreased with progressing stages of EOC and tumor recurrence, suggesting that PTPRM acts as a tumor suppressor in EOC progression. Negative PTPRM expression may predict poor clinical outcomes in patients with EOC.

Differentiation of Borderline Epithelial Ovarian Tumors from Benign and Malignant Epithelial Ovarian Tumors by MRI Scoring

The distinction between benign and borderline epithelial ovarian tumors is important because treatment and follow-up strategies differ We aimed to evaluate benign, borderline, and malignant epithelial ovarian tumors using MRI features and contributed to the preoperative evaluation. MRIs of 81 patients (20 bilateral), including 31 benign, 27 borderline, and 23 malignant, who had pelvic imaging between 2013-2020, were evaluated retrospectively. The evaluation was made blindly to the pathology result by two radiologists with MRI scoring and features that we determined. MRI evaluation was performed with T1 TSE, T2 TSE, fat-suppressed T2 TSE, and before and after contrast T1 fat-suppressed and non-fat-suppressed TSE images. The numbers and findings obtained in scoring were evaluated by Chi-Square, ordinal logistic regression, and 2 and 3 category ROC analysis. The total score varied between 7 and 24. Among the three groups, a significant difference was found in terms of T1, T2 signal intensity (p <0.01), size (p = 0.055), solid area (p <0.001), septa number (p <0.05), ovarian parenchyma (p = 0.001), ascites (p <0.001), peritoneal involvement (p <0.001), laterality (p <0.001), contrast enhancement pattern (p <0.001). On the other hand, no significant difference was found in terms of wall thickness, lymph node involvement and endometrial thickness (p> 0.05). Cut-off values were found as 11.5 and 18.5 in the 3-category ROC analysis performed for the score (VUS: 0.8109). Patients with a score below 11.5 were classified as benign, those between 11.5-18.5 as borderline, and those over 18.5 as malignant. The differentiation of borderline tumors from benign and malignant tumors by MRI scoring will contribute to the preoperative diagnosis.

Combined use of CA125, neutrophil/lymphocyte ratio and platelet/lymphocyte ratio for the diagnosis of borderline and malignant epithelial ovarian tumors

BackgroundThe mortality rate of ovarian cancer ranks first among three common gynecological malignant tumors due to insidious onset and lack of effective early diagnosis methods. Borderline epithelial ovarian tumor (BEOT) is a type of low malignant potential tumor that is typically associated with better outcomes than ovarian cancer. However, BEOTs are easily confused with benign and malignant epithelial ovarian tumors (EOTs) due to similar clinical symptoms and lack of specific tumor biomarkers and imaging examinations. Notably, a small subset of BEOTs will transform into low-grade serous ovarian carcinoma with a poor prognosis. Therefore, searching for potential biomarkers that can be easily obtained and accurately identify malignant epithelial ovarian tumors (MEOTs) as well as BEOTs is essential for the clinician. Cancer antigen 125 (CA125) is a commonly used biomarker for the diagnosis of EOTs in the preoperative scenario but has low sensitivity and specificity. Nowadays, inflammatory biomarkers including inflammatory cell counts and derived ratios such as neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have been proved to be associated with tumor progression and poor prognosis, and were considered to be the most economically potential surrogate biomarkers for various malignancies. The purpose of this study was to find appropriate combinations of inflammatory and tumor biomarkers to improve the diagnostic efficiency of EOTs, especially the BEOTs.ResultsCA125, NLR and PLR increased steadily among benign, borderline and malignant EOTs and tended to be higher in advanced (stage III-IV) and lymph node metastasis MEOT groups than in early stage (stage I-II) and non-lymph node metastasis MEOT groups. CA125, NLR and PLR could be used separately in the differentiation of EOTs but could not take into account both sensitivity and specificity. The combined use of CA125, NLR and PLR was evaluated to be more efficient, especially in the identification of BEOTs, with both high sensitivity and high specificity.ConclusionsThe levels of CA125, NLR and PLR were closely related to the nature of EOTs and malignant progression of MEOTs. The combination of CA125, NLR and PLR was more accurate in identifying the nature of EOTs than either alone or double combination, especially for BEOTs.

Diffusion-weighted imaging-based radiomics in epithelial ovarian tumors: Assessment of histologic subtype.

Epithelial ovarian tumors (EOTs) are a group of heterogeneous neoplasms. It is importance to preoperatively differentiate the histologic subtypes of EOTs. Our study aims to investigate the potential of radiomics signatures based on diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps for categorizing EOTs. This retrospectively enrolled 146 EOTs patients [34 with borderline EOT(BEOT), 30 with type I and 82 with type II epithelial ovarian cancer (EOC)]. A total of 390 radiomics features were extracted from DWI and ADC maps. Subsequently, the LASSO algorithm was used to reduce the feature dimensions. A radiomics signature was established using multivariable logistic regression method with 3-fold cross-validation and repeated 50 times. Patients with bilateral lesions were included in the validation cohort and a heuristic selection method was established to select the tumor with maximum probability for final consideration. A nomogram incorporating the radiomics signature and clinical characteristics was also developed. Receiver operator characteristic, decision curve analysis (DCA), and net reclassification index (NRI) were applied to compare the diagnostic performance and clinical net benefit of predictive model. For distinguishing BEOT from EOC, the radiomics signature and nomogram showed more favorable discrimination than the clinical model (0.915 vs. 0.852 and 0.954 vs. 0.852, respectively) in the training cohort. In classifying early-stage type I and type II EOC, the radiomics signature exhibited superior diagnostic performance over the clinical model (AUC 0.905 vs. 0.735). The diagnostic efficacy of the nomogram was the same as that of the radiomics model with NRI value of -0.1591 (P = 0.7268). DCA also showed that the radiomics model and combined model had higher net benefits than the clinical model. Radiomics analysis based on DWI, and ADC maps serve as an effective quantitative approach to categorize EOTs.

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.

T2-weighted MRI-based radiomics for discriminating between benign and borderline epithelial ovarian tumors: a multicenter study

BackgroundPreoperative differentiation between benign and borderline epithelial ovarian tumors (EOTs) is challenging and can significantly impact clinical decision making. The purpose was to investigate whether radiomics based on T2-weighted MRI can discriminate between benign and borderline EOTs preoperatively.MethodsA total of 417 patients (309, 78, and 30 samples in the training and internal and external validation sets) with pathologically proven benign and borderline EOTs were included in this multicenter study. In total, 1130 radiomics features were extracted from manually delineated tumor volumes of interest on images. The following three different models were constructed and evaluated: radiomics features only (radiomics model); clinical and radiological characteristics only (clinic-radiological model); and a combination of them all (combined model). The diagnostic performances of models were assessed using receiver operating characteristic (ROC) analysis, and area under the ROC curves (AUCs) were compared using the DeLong test.ResultsThe best machine learning algorithm to distinguish borderline from benign EOTs was the logistic regression. The combined model achieved the best performance in discriminating between benign and borderline EOTs, with an AUC of 0.86 ± 0.07. The radiomics model showed a moderate AUC of 0.82 ± 0.07, outperforming the clinic-radiological model (AUC of 0.79 ± 0.06). In the external validation set, the combined model performed significantly better than the clinic-radiological model (AUCs of 0.86 vs. 0.63, p = 0.021 [DeLong test]).ConclusionsRadiomics, based on T2-weighted MRI, can provide critical diagnostic information for discriminating between benign and borderline EOTs, thus having the potential to aid personalized treatment options.

Quantitative analysis of the MRI features in the differentiation of benign, borderline, and malignant epithelial ovarian tumors

ObjectiveThis study aims to investigate the value of the quantitative indicators of MRI in the differential diagnoses of benign, borderline, and malignant epithelial ovarian tumors (EOTs).Materials and methodsThe study population comprised 477 women with 513 masses who underwent MRI and operation, including benign EOTs (BeEOTs), borderline EOTs (BEOTs), and malignant EOTs (MEOTs). The clinical information and MRI findings of the three groups were compared. Then, multivariate logistic regression analysis was performed to find the independent diagnostic factors. The receiver operating characteristic (ROC) curves were also used to evaluate the diagnostic performance of the quantitative indicators of MRI and clinical information in differentiating BeEOTs from BEOTs or differentiating BEOTs from MEOTs.ResultsThe MEOTs likely involved postmenopausal women and showed higher CA-125, HE4 levels, ROMA indices, peritoneal carcinomatosis and bilateral involvement than BeEOTs and BEOTs. Compared with BEOTs, BeEOTs and MEOTs appeared to be more frequently oligocystic (P < 0.001). BeEOTs were more likely to show mild enhancement (P < 0.001) and less ascites (P = 0.003) than BEOTs and MEOTs. In the quantitative indicators of MRI, BeEOTs usually showed thin-walled cysts and no solid component. BEOTs displayed irregular thickened wall and less solid portion. MEOTs were more frequently characterized as solid or predominantly solid mass (P < 0.001) than BeEOTs and BEOTs. The multivariate logistic regression analysis showed that volume of the solid portion (P = 0.006), maximum diameter of the solid portion (P = 0.038), enhancement degrees (P < 0.001), and peritoneal carcinomatosis (P = 0.011) were significant indicators for the differential diagnosis of the three groups. The area under the curves (AUCs) of above indicators and combination of four image features except peritoneal carcinomatosis for the differential diagnosis of BeEOTs and BEOTs, BEOTs and MEOTs ranged from 0.74 to 0.85, 0.58 to 0.79, respectively.ConclusionIn this study, the characteristics of MRI can provide objective quantitative indicators for the accurate imaging diagnosis of three categories of EOTs and are helpful for clinical decision-making. Among these MRI characteristics, the volume, diameter, and enhancement degrees of the solid portion showed good diagnostic performance.

Histomorphological Features of Ovarian Neoplasms and Expression of p53 and WT1 in Surface Epithelial Tumours: A Cross-sectional Study

Introduction: Ovary is the most common site of neoplastic and non neoplastic lesion, can present in childhood to postmenopausal age group and remain the most lethal of all gynaecological malignancies. Tumour Protein (p53) gene mutations or deletions are most common in ovarian carcinoma. However, Wilms' Tumor gene1 (WT1) and p16 expression are also seen in serous ovarian carcinoma. These Immunohistochemistry (IHC) marker are useful in the differential diagnosis of serous ovarian carcinomas. Aim: To study histomorphology of ovarian neoplasm along with expression of p53 and WT1 in surface epithelial tumours and to assess the prevalence of various ovarian neoplasms in different age groups. Materials and Methods: This cross-sectional study was conducted in Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India, over a period of two years (from September 2018-September 2020). A total of 78 ovarian specimen received in histology laboratory was studied for gross and microscopic features. The p53 and WT1 IHC expression pattern was studied in surface epithelial tumours. Statistical significance was calculated in relation to p53 and WT1 expression with histological type and grade of tumour using Chi-square test. Results: A total of 78 cases were studied, out of which benign tumours were the most common 40 (51.3%) cases, followed by malignant tumours 32 (41.0%) cases and borderline malignancy 6 (7.7%) cases. The most common benign lesions were mucinous cystadenoma 20 (50%) cases. Serous carcinomas were most common malignant tumours 19 (59.3%) cases followed by Germ Cell Tumours (GCT) 5 (15.6%) cases. All benign and borderline epithelial ovarian tumours were found p53 and WT1 negative. Out of 22 cases of malignant surface epithelial tumour, 14 (63.6%) and 12 (54.4%) were positive for p53 and WT1 respectively and all were serous carcinomas. Conclusion: Ovarian lesions present with wide spectrum of histomorphological features. The p53 and WT1 show different rates of expression and staining pattern in various epithelial ovarian carcinomas. Hence routine gross, proper histological examination and correct IHC interpretation is required for specific diagnosis.

Survival and reproductive outcomes after fertility-sparing surgery performed for borderline epithelial ovarian tumor in Japanese adolescents and young adults: Results of a retrospective nationwide study.

Epithelial borderline ovarian tumor (BOT) frequently occurs in young women. Because progression-free survival, overall survival, and reproductive function are important outcomes, BOT is often treated by fertility-sparing surgery (FSS). We conducted a Japan-wide study to understand post-FSS prognosis in relation to clinical characteristics and types of FSS performed. We analyzed clinical and outcome data pertaining to 531 adolescent and young adult (AYA) patients (aged 15-39 years) who underwent FSS for BOT between 2009 and 2013. Median (range) age was 30 (15-39) years, and median observation time was 70 (2-120) months. The disease was of FIGO stage I in 492 (93%) patients. Histopathologically, tumors were of the mucinous (n=372, 70%), serous (n=120, 23%), seromucinous (n=23, 4%), and other (n=16, 3%) types. Five-year overall survival was 99.5% among patients with stage I and 100% among those with stage II-IV. Five-year progression-free survival was 96.7% and 69.3%, respectively. Multivariate analysis in cases of stage I showed a positive peritoneal cytology to be a significant risk factor for recurrence (HR, 5.199; p=0.0188). The post-FSS pregnancy rate was relatively low for patients aged ≥30 years (OR, 0.868; 95% CI, 1.16-3.00; p=0.0090). Post-FFS outcomes in terms of overall and progression-free survival are favorable, especially for AYA patients with stage I BOT. However, the relapse rate is high for patients with FIGO stage II-IV and for those with stage I but a positive peritoneal cytology. A long-term prospective observation is needed before reproductive outcomes can be fully established.

Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between borderline and malignant epithelial ovarian tumors

Malignant epithelial ovarian tumors (MEOTs) are the most lethal gynecologic malignancies, accounting for 90% of ovarian cancer cases. By contrast, borderline epithelial ovarian tumors (BEOTs) have low malignant potential and are generally associated with a good prognosis. Accurate preoperative differentiation between BEOTs and MEOTs is crucial for determining the appropriate surgical strategies and improving the postoperative quality of life. Multimodal magnetic resonance imaging (MRI) is an essential diagnostic tool. Although state-of-the-art artificial intelligence technologies such as convolutional neural networks can be used for automated diagnoses, their application have been limited owing to their high demand for graphics processing unit memory and hardware resources when dealing with large 3D volumetric data. In this study, we used multimodal MRI with a multiple instance learning (MIL) method to differentiate between BEOT and MEOT. We proposed the use of MAC-Net, a multiple instance convolutional neural network (MICNN) with modality-based attention (MA) and contextual MIL pooling layer (C-MPL). The MA module can learn from the decision-making patterns of clinicians to automatically perceive the importance of different MRI modalities and achieve multimodal MRI feature fusion based on their importance. The C-MPL module uses strong prior knowledge of tumor distribution as an important reference and assesses contextual information between adjacent images, thus achieving a more accurate prediction. The performance of MAC-Net is superior, with an area under the receiver operating characteristic curve of 0.878, surpassing that of several known MICNN approaches. Therefore, it can be used to assist clinical differentiation between BEOTs and MEOTs.

Application of contrast-enhanced dual-energy spectral CT for differentiating borderline from malignant epithelial ovarian tumours

To investigate the value of contrast-enhanced dual-energy spectral computed tomography (CT) in differentiating borderline epithelial ovarian tumours (BEOTs) from malignant epithelial ovarian tumours (MEOTs). Sixty patients who underwent pelvic contrast-enhanced spectral CT were divided into two groups for analysis based on the tumour types confirmed at histopathological examination (26 BEOTs and 34 MEOTs). The regions of interest (ROIs) were selected on solid tumour components to measure attenuation values on monochromatic image sets (40-140 keV) in all imaging phases and tumour iodine concentrations (IC) on material decomposition images. Differences in the attenuation value between the unenhanced and contrast-enhanced phases (enhancement degree) and between energy strengths (slope k, k=[attenuation at 40 keV- attenuation at 140 keV]/100) were calculated. All measurements between the two groups were compared with independent t-test. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity, specificity and area under the ROC curve (AUC). Logistic regression analysis was used to evaluate the diagnostic efficacy of using combined parameters in two-phase contrast-enhanced images. In the arterial phase (AP) and venous phase (VP), the BEOTs had significantly lower enhancement than MEOTs from 40 to 100 keV (p<0.05). The k values and IC values both showed significant differences in the AP and VP (p<0.05). Combining parameters in two contrast-enhanced phases provided 80.8% sensitivity and 82.4% specificity in differentiating MEOTs from BEOTs with an AUC of 0.844. Dual-energy spectral CT provides a multiparametric approach in differentiating BEOTs from MEOTs with the best diagnostic efficacy using combined parameters in the AP and VP images.

The 2020 Japan Society of Gynecologic Oncology guidelines for the treatment of ovarian cancer, fallopian tube cancer, and primary peritoneal cancer.

The fifth edition of the Japan Society of Gynecologic Oncology guidelines for the treatment of ovarian cancer, fallopian tube cancer, and primary peritoneal cancer was published in 2020. The guidelines contain 6 chapters—namely, (1) overview of the guidelines; (2) epithelial ovarian cancer, fallopian tube cancer, and primary peritoneal cancer; (3) recurrent epithelial ovarian cancer, fallopian tube cancer, and primary peritoneal cancer; (4) borderline epithelial tumors of the ovary; (5) malignant germ cell tumors of the ovary; and (6) malignant sex cord-stromal tumors. Furthermore, the guidelines comprise 5 algorithms—namely, (1) initial treatment for ovarian cancer, fallopian tube cancer, and primary peritoneal cancer; (2) treatment for recurrent ovarian cancer, fallopian tube cancer, and primary peritoneal cancer; (3) initial treatment for borderline epithelial ovarian tumor; (4) treatment for malignant germ cell tumor; and (5) treatment for sex cord-stromal tumor. Major changes in the new edition include the following: (1) revision of the title to “guidelines for the treatment of ovarian cancer, fallopian tube cancer, and primary peritoneal cancer”; (2) involvement of patients and general (male/female) participants in addition to physicians, pharmacists, and nurses; (3) clinical questions (CQs) in the PICO format; (4) change in the expression of grades of recommendation and level of evidence in accordance with the GRADE system; (5) introduction of the idea of a body of evidence; (6) categorization of references according to research design; (7) performance of systematic reviews and meta-analysis for three CQs; and (8) voting for each CQ/recommendation and description of the consensus.

Ovarian reserve in patients with borderline ovarian tumors after surgical treatment

Borderline ovarian tumors are often diagnosed in women under the age of 40 years (31.8 %), which determines the need to optimize the management of this cohort of patients, taking into account the possibility of maintaining their reproductive function. Purpose of the study. Assessment of the ovarian reserve based on a comprehensive sonographic diagnosis of the ovarian reserve in patients of reproductive age with borderline ovarian tumors. Materials and methods. Group I (n = 103) included patients with borderline serous epithelial ovarian tumors. Group II (n = 95) was formed from women with mucinous epithelial ovarian tumors. Comparison group III (n = 189) included patients with benign ovarian cystadenomas. Ultrasound scanning of the pelvic organs and color Doppler mapping (DLC) were performed using Aloka 3500, Semiens G‑60 ultrasound scanners operating in real time and equipped with a pulsed doppler using a 3.5 MHz convex sensor and a 7.5 MHz transvaginal sensor. Results. The number of antral follicles does not depend on the volume of the ovary. The healthy remaining ovarian tissue of the ovary is most pronounced in groups I and III, significantly less represented in group II (p ≤ 0.0001). Three months after adnexectomy, ovulatory function in the intact (healthy) ovary was preserved in 71% (n = 49) of women from group I; in 89% (n = 73) of patients of group II and in 93% (n = 25) of respondents of group III, with a predominance in group II (φ* = 2.7; p ≤ 0.0010 and φ* = 1.6; p ≤ 0.0500). After a conservative operation, the function of the operated (resected) ovary detected ovulation in 62% (n = 21) of group I participants; 68% (n = 9) of women of group II and 86% (n = 139) of patients of group III. After 6 months, an increase in the number of antral ovaries and the number of ovulations with a predominance of ovarian reserve in group III (p ≤ 0.0010 and p ≤ 0.0001) was generally observed. Conclusions. Integrated ultrasound is a reliable and objective method that evaluates the features of the ovulatory reserve in patients with borderline and benign ovarian tumors, which makes it possible to formulate a prognosis of a woman’s reproductive health after various types of surgical treatment.

Texture Analysis of Three-Dimensional MRI Images May Differentiate Borderline and Malignant Epithelial Ovarian Tumors.

ObjectiveTo explore the value of magnetic resonance imaging (MRI)-based whole tumor texture analysis in differentiating borderline epithelial ovarian tumors (BEOTs) from FIGO stage I/II malignant epithelial ovarian tumors (MEOTs).Materials and MethodsA total of 88 patients with histopathologically confirmed ovarian epithelial tumors after surgical resection, including 30 BEOT and 58 MEOT patients, were divided into a training group (n = 62) and a test group (n = 26). The clinical and conventional MRI features were retrospectively reviewed. The texture features of tumors, based on T2-weighted imaging, diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging, were extracted using MaZda software and the three top weighted texture features were selected by using the Random Forest algorithm. A non-texture logistic regression model in the training group was built to include those clinical and conventional MRI variables with p value < 0.10. Subsequently, a combined model integrating non-texture information and texture features was built for the training group. The model, evaluated using patients in the training group, was then applied to patients in the test group. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the models.ResultsThe combined model showed superior performance in categorizing BEOTs and MEOTs (sensitivity, 92.5%; specificity, 86.4%; accuracy, 90.3%; area under the ROC curve [AUC], 0.962) than the non-texture model (sensitivity, 78.3%; specificity, 84.6%; accuracy, 82.3%; AUC, 0.818). The AUCs were statistically different (p value = 0.038). In the test group, the AUCs, sensitivity, specificity, and accuracy were 0.840, 73.3%, 90.1%, and 80.8% when the non-texture model was used and 0.896, 75.0%, 94.0%, and 88.5% when the combined model was used.ConclusionMRI-based texture features combined with clinical and conventional MRI features may assist in differentitating between BEOT and FIGO stage I/II MEOT patients.

Borderline epithelial ovarian tumors: what the radiologist should know.

Ovarian borderline tumors are neoplasms of epithelial origin that are typically present in young patients and tend to have a less aggressive clinical course than malignant tumors. Accurate diagnosis and staging of borderline tumors has important prognostic and management implications (like fertility-sparing procedures) for women of child-bearing age. This article will review the sonographic, CT, and MRI features of borderline epithelial ovarian tumors with histopathologic correlation. Borderline tumors have less soft tissue and thinner walls/septations than malignant tumors. Serous borderline tumors more commonly have papillary projections, which can simulate the appearance of a sea anemone. Mucinous borderline tumors often are larger, multi-cystic, and more commonly unilateral. The borderline mucinous tumors may also present with pseudomyxoma peritonei, which can make it difficult to distinguish from malignant mucinous carcinoma. Ultrasound is usually the first-line modality for imaging these tumors with MRI reserved for further characterizing indeterminate cases. CT is best used to stage tumors for both locoregional and distant metastatic disease. Overall, however, the imaging features overlap with both benign and malignant ovarian tumors. Despite this, it is important for the radiologist to be familiar with the imaging appearances of borderline tumors because they can present in younger patients and may benefit from different clinical/surgical management.

Semaphorin-4C is upregulated in epithelial ovarian cancer.

The present retrospective study aimed to investigate the expression of semaphorin-4C (Sema4C) in epithelial ovarian cancer (EOC), and to determine the association between Sema4C expression and patient clinicopathological characteristics. Sema4C mRNA expression was detected by reverse transcription-quantitative polymerase chain reaction in the tissues of 74 cases of EOC, 20 cases of ovarian epithelial benign tumor, 20 cases of ovarian borderline epithelial tumor and 15 cases of normal ovarian tissue. Immunohistochemistry was used to detect the expression and localization of Sema4C. The association between Sema4C expression level and patients clinicopathological characteristics was determined by χ2 test. The results demonstrated that Sema4C expression level in ovarian epithelial carcinoma tissues was significantly higher compared with that in benign tumors, borderline epithelial tumors and normal ovarian tissues (P<0.05). In addition, Sema4C expression in ovarian cancer tissues was significantly associated with the clinical and pathological stages of tumors (P<0.05). In conclusion, the present study demonstrated that Sema4C expression was upregulated in EOC.

Expression of p53 in epithelial ovarian tumors.

Ovarian cancers remain the most lethal of all gynecological malignancies despite major developments in their treatment. To study the rate of expression and staining patterns of p53 in various histological types and grades of epithelial ovarian tumors (EOT). Sixty EOTs received in a tertiary care center were studied for gross, microscopy, and p53 immunohistochemistry (IHC) expression patterns. Parameters such as age, laterality of tumor, ascites, capsule rupture, tumor size, stage at presentation, metastasis, tumor grade, and number of mitosis were correlated. Of the sixty cases studied, 23 (38.3%) were malignant. Serous carcinomas were the largest group with 17 cases (74%) followed by mucinous with 4 cases (17%) and 2 clear cell carcinomas (9%). All benign and borderline EOT were p53 negative. 65.2% of the malignancies were p53 positive and all of them were serous malignancies. 15 out of 16 high-grade serous carcinomas were p53 positive (94%), while one case was negative (6%). 10 cases (63%) showed intense diffuse positivity of more than 60% of the nucleus, while 5 cases (31%) showed aberrant null staining <5% staining of the nucleus. All mucinous, clear cell carcinomas, and the only low-grade serous carcinoma in the study were p53 negative. P53 staining had positive correlations with variables like capsule rupture, ascites, laterality, and CA 125. The study highlights the different rates of expression and staining patterns of p53 and the need for correct interpretation of p53 IHC for the diagnosis of various EOT.

When to Worry about Cancer: Concurrent Carcinoma and Recurrence in Borderline Ovarian Tumors.

The objectives of this study were to identify and assess the factors associated with concurrent carcinoma and recurrence in women with epithelial borderline ovarian tumors. The cancer and pathology databases at a tertiary care academic cancer center were queried for all borderline ovarian tumors from 2005 to 2015. Cases with/without concurrent ovarian carcinoma and with/without recurrence were compared. A total of 123 women with borderline tumors were identified (mean age 51.3 years). Concurrent carcinoma was present in 31 (25.2%). Women with concurrent carcinoma were significantly more likely to be peri- or postmenopausal, have an elevated CA-125, and have a nonserous histology. Seven (5.7%) women's cancer recurred at a mean of 23.5 months (mean follow-up 30.0 months). Women with recurrence were more likely to be nonwhite, have concurrent invasive carcinoma, and have had residual disease at the time of surgery. Epithelial borderline ovarian tumors often co-exist with carcinoma and occur more frequently in postmenopausal women, in women with elevated CA-125, and in tumors with nonserous histology. The presence of any of these factors should alert clinicians to the potential need for comprehensive staging at the time of surgery. The recurrence of borderline tumors is associated with nonwhite race, concurrent carcinoma, and residual disease at initial surgery.