Imaging in gynecological disease (12): clinical and ultrasound features of invasive and non-invasive malignant serous ovarian tumors

MRI characteristics of FIGO stage IA epithelial ovarian cancer (EOC)

PURPOSE

To investigate the MRI characteristics of FIGO stage IA EOC with different pathologic subtypes in order to improve the radiologists' understanding of these diseases.

METHODS

In this retrospective study, we recruited patients who underwent surgery due to EOC at our hospital and were staged as FIGO IA from January 2013 to May 2024. The MR imaging and clinical features were evaluated by radiologists specialized in gynecology. Kruskal-Wallis test and Chi-squared test were performed to assess the difference between groups.

RESULTS

A total of 34 patients with a mean age of 56 years included serous carcinoma 9 cases (26 %), endometrioid carcinoma 9 cases (26 %), clear cell carcinoma 10 cases (29 %), mucinous carcinoma 6 cases (18 %). 2 patients synchronously developed ovarian cancer and uterus endometrial cancer. The median CA125 level was 65.6 U/ml (95 % CI, 21.6 to 92.8) and laterality ratio was 17:18 (left: right). Median diameter of tumor was 10.9 cm (95 % CI, 8.0 to 11.8). There were 6 cases of pure solid tumor, 5 cases of unilocular cystic-solid tumor and 23 multilocular cystic-solid tumor. 17 cases appeared hemorrhage signal and 6 of which had mixed signals in the loculi. As for enhancement pattern, total 10 cases of type I, 11 cases of type II and 13 cases of type III. Solid tissue in 33 (97 %) cases demonstrated restricted diffusion in DWI sequence. 9 cases presented ascites. There were 5 factors showed significant differences among different pathologic subtypes (p < 0.05), including maximum diameter, general morphology, growth pattern of solid tissue, grouped septa and presence of mixed signals in the loculi.

CONCLUSION

The imaging performance of FIGO stage IA EOC were variable, and there were differences in imaging characteristics among different pathological subtypes, which can improve current understanding of FIGO stage IA EOC and reduce clinical diagnostic omissions.

Ultrasonographic Features of the Fallopian Tubes: An Overview on Main Tubal Pathologies

Fallopian tubes are not usually visible on a transvaginal pelvic scan unless pelvic fluid or pathological processes are present. Depending on the underlying pathological process, they may exhibit different wall thicknesses, grades of vascularization, and variable echogenicity. Recognizing the affected tube and assessing the possible underlying process is of primary importance in clinical practice, as pathological tubes may represent benign pathologies, oncological state, or life-threatening conditions requiring different treatment to preserve fertility. The aim of this pictorial review is to describe the main characteristics of the most common tubal pathologies to help clinicians recognize them.

Ovarian cancer in pregnancy

OBJECTIVE

The objective of this manuscript is to review the epidemiology, diagnosis, treatment and outcomes of ovarian cancers diagnosed during pregnancy.

FINDING

Ovarian cancer in pregnancy, although rare, is more likely to be diagnosed early during pregnancy due to the increased use of high resolution ultrasound. Treatment will depend on a multidisciplinary team. These cancers are usually treated with surgery alone during pregnancy, optimally between 13-20 weeks to reduce the risk of miscarriage or preterm labor. Chemotherapy is usually given after delivery if appropriate to the tumor type, unless the patient has widely metastatic disease.

CONCLUSION

The majority of ovarian cancers diagnosed during pregnancy are Stage I due to both young age and increased use of early ultrasound during pregnancy and have a better overall prognosis than the cancers detected in older women.

Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid morphology on ultrasound

OBJECTIVE

The primary aim was to identify radiomics ultrasound features that can distinguish between benign and malignant adnexal masses with solid ultrasound morphology, and between primary malignant (including borderline and primary invasive) and metastatic solid ovarian masses, and to develop ultrasound-based machine learning models that include radiomics features to discriminate between benign and malignant solid adnexal masses. The secondary aim was to compare the discrimination performance of our newly developed radiomics models with that of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and that of subjective assessment by an experienced ultrasound examiner.

METHODS

This was a retrospective, observational single-center study conducted at Fondazione Policlinico Universitario A. Gemelli IRCC, in Rome, Italy. Included were patients with a histological diagnosis of an adnexal tumor with solid morphology according to International Ovarian Tumor Analysis (IOTA) terminology at preoperative ultrasound examination performed in 2014-2020, who were managed with surgery. The patient cohort was split randomly into training and validation sets at a ratio of 70:30 and with the same proportion of benign and malignant tumors in the two subsets, with malignant tumors including borderline, primary invasive and metastatic tumors. We extracted 68 radiomics features, belonging to two different families: intensity-based statistical features and textural features. Models to predict malignancy were built based on a random forest classifier, fine-tuned using 5-fold cross-validation over the training set, and tested on the held-out validation set. The variables used in model-building were patient age and radiomics features that were statistically significantly different between benign and malignant adnexal masses and assessed as not redundant based on the Pearson correlation coefficient. We evaluated the discriminative ability of the models and compared it to that of the ADNEX model and that of subjective assessment by an experienced ultrasound examiner using the area under the receiver-operating-characteristics curve (AUC) and classification performance by calculating sensitivity and specificity.

RESULTS

In total, 326 patients were included and 775 preoperative ultrasound images were analyzed. Of the 68 radiomics features extracted, 52 differed statistically significantly between benign and malignant tumors in the training set, and 18 uncorrelated features were selected for inclusion in model-building. The same 52 radiomics features differed significantly between benign, primary malignant and metastatic tumors. However, the values of the features manifested overlapped between primary malignant and metastatic tumors and did not differ significantly between them. In the validation set, 25/98 (25.5%) tumors were benign and 73/98 (74.5%) were malignant (6 borderline, 57 primary invasive, 10 metastatic). In the validation set, a model including only radiomics features had an AUC of 0.80, sensitivity of 0.78 and specificity of 0.76 at an optimal cut-off for risk of malignancy of 68%, based on Youden's index. The corresponding results for a model including age and radiomics features were AUC of 0.79, sensitivity of 0.86 and specificity of 0.56 (cut-off 60%, based on Youden's index), while those of the ADNEX model were AUC of 0.88, sensitivity of 0.99 and specificity of 0.64 (at a 20% risk-of-malignancy cut-off). Subjective assessment had a sensitivity of 0.99 and specificity of 0.72.

CONCLUSIONS

Our radiomics model had moderate discriminative ability on internal validation and the addition of age to this model did not improve its performance. Even though our radiomics models had discriminative ability inferior to that of the ADNEX model, our results are sufficiently promising to justify continued development of radiomics analysis of ultrasound images of adnexal masses. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Ultrasound-based ADNEX model for differentiating between benign, borderline, and malignant epithelial ovarian tumours

BACKGROUND

The purpose of this study was to evaluate the ability of the International Ovarian Tumor Analysis-Assessment of Different NEoplasias in the adneXa (IOTA-ADNEX) model to distinguish among benign, borderline, and malignant epithelial ovarian tumours (BeEOTs, BEOTs, and MEOTs, respectively).

METHODS

The study included 813 patients with BeEOTs, BEOTs, and MEOTs who underwent ultrasound examinations and pelvic operations. Comparisons were made between the clinical information and ultrasonographic features of the three patient groups, and the histopathological diagnosis was the gold standard. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of the ADNEX model were calculated.

RESULTS

This was a single-centre retrospective study. Of the 813 patients, 257 (31.6%) had BeEOTs, 114 (14.0%) had BEOTs, and 442 (54.4%) had MEOTs. For a cut-off value of 10% to identify the overall risk for ovarian cancer (OC), the sensitivity and specificity were 99.1% and 73.2%, respectively. According to the receiver operating characteristicscurves, the AUC was 0.987 (95% CI: 0.981-0.993) for BeEOTs compared with MEOTs, 0.820 (95% CI: 0.768-0.872) for BeEOTs compared with BEOTs, 0.912 (95% CI: 0.876-0.948) for BeEOTs compared with stage I OC, and 0.995 (95% CI: 0.992-0.998) for BeEOTs compared with stages II-IV OC. The AUC was 0.614 (95% CI: 0.519-0.709) for BEOTs compared with stage I OC, 0.903 (95% CI: 0.869-0.937) for BEOTs compared with stages II-IV OC, and 0.851 (95% CI: 0.800-0.902) for stage I OC compared with stages II-IV OC.

CONCLUSIONS

The IOTA-ADNEX model demonstrated good diagnostic performance for the three categories of EOTs and may have the potential to be popularised in assisting radiologists in the assessment of adnexal masses in the future.

Pseudotumoral pelviperitoneal tuberculosis mimicking ovarian cancer: A case report

Tuberculosis is a rare but treatable infectious disease that continues to pose a significant health issue in regions with high prevalence. Its abdominopelvic localization can mimic advanced ovarian cancer, leading to diagnostic challenges. This report describes the case of a 33-year-old woman who was admitted to the gastroenterology unit with ascites, peritoneal thickening, and an ovarian mass on imaging. The diagnosis of abdominopelvic and peritoneal tuberculosis was confirmed after laparoscopy. The patient underwent antitubercular chemotherapy and showed clinical improvement.

Clinical value of ACR O-RADS combined with CA125 in the risk stratification of adnexal masses

Purpose

To develop a combined diagnostic model integrating the subclassification of the 2022 version of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) with carbohydrate antigen 125 (CA125) and to validate whether the combined model can offer superior diagnostic efficacy than O-RADS alone in assessing adnexal malignancy risk.

Methods

A retrospective analysis was performed on 593 patients with adnexal masses (AMs), and the pathological and clinical data were included. According to the large differences in malignancy risk indices for different image features in O-RADS category 4, the lesions were categorized into groups A and B. A new diagnostic criterion was developed. Lesions identified as category 1, 2, 3, or 4A with a CA125 level below 35 U/ml were classified as benign. Lesions identified as category 4A with a CA125 level more than or equal to 35 U/ml and lesions with a category of 4B and 5 were classified as malignant. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) of O-RADS (v2022), CA125, and the combined model in the diagnosis of AMs were calculated and compared.

Results

The sensitivity, specificity, PPV, NPV, accuracy, and AUCs of the combined model were 92.4%, 96.5%, 80.2%, 98.8%, 94.1%, and 0.945, respectively. The specificity, PPV, accuracy, and AUC of the combined model were significantly higher than those of O-RADS alone (all P < 0.01). In addition, both models had acceptable sensitivity and NPV, but there were no significant differences among them (P > 0.05).

Conclusion

The combined model integrating O-RADS subclassification with CA125 could improve the specificity and PPV in diagnosing malignant AMs. It could be a valuable tool in the clinical application of risk stratification of AMs.

Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis

AIM

The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis.

METHODS

Pubmed, Embase, Web of Science, and Cochrane Library databases were comprehensively retrieved from database inception untill February 16, 2023. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was adopted to evaluate the risk of bias in the original studies. Sub-group analyses of ML were conducted according to clinical features and radiomics features. We separately discussed the discriminative value of ML for borderline vs benign and borderline vs malignant tumors.

RESULTS

Eighteen studies involving 12,778 subjects were included in our analysis. The modeling variables mainly consisted of radiomics features (n=13) and a small number of clinical features (n=5). When distinguishing between borderline and benign tumors, the ML model based on radiomic features achieved a c-index of 0.782 (95% CI: 0.732-0.831), sensitivity of 0.75 (95% CI: 0.67-0.82), and specificity of 0.75 (95% CI: 0.67-0.81) in the validation set. When distinguishing between borderline and malignant tumors, the ML model based on radiomic features achieved a c-index of 0.916 (95% CI: 0.891-0.940), sensitivity of 0.86 (95% CI: 0.78-0.91), and specificity of 0.88 (95% CI: 0.82-0.92) in the validation set. In addition, we analyzed the discriminatory ability of radiologists and found that their sensitivity was 0.26 (95% CI: 0.12-0.46) and specificity was 0.94 (95% CI: 0.90-0.97).

CONCLUSIONS

ML has tremendous potential in the preoperative diagnosis and differentiation of borderline ovarian tumors and may be more accurate than radiologists in diagnosing and differentiating borderline ovarian tumors.

An explainable machine learning model to solid adnexal masses diagnosis based on clinical data and qualitative ultrasound indicators

BACKGROUND

Accurate characterization of newly diagnosed a solid adnexal lesion is a key step in defining the most appropriate therapeutic approach. Despite guidance from the International Ovarian Tumor Analyzes Panel, the evaluation of these lesions can be challenging. Recent studies have demonstrated how machine learning techniques can be applied to clinical data to solve this diagnostic problem. However, ML models can often consider as black-boxes due to the difficulty of understanding the decision-making process used by the algorithm to obtain a specific result.

AIMS

For this purpose, we propose an Explainable Artificial Intelligence model trained on clinical characteristics and qualitative ultrasound indicators to predict solid adnexal masses diagnosis.

MATERIALS & METHODS

Since the diagnostic task was a three-class problem (benign tumor, invasive cancer, or ovarian metastasis), we proposed a waterfall classification model: a first model was trained and validated to discriminate benign versus malignant, a second model was trained to distinguish nonmetastatic versus metastatic malignant lesion which occurs when a patient is predicted to be malignant by the first model. Firstly, a stepwise feature selection procedure was implemented. The classification performances were validated on Leave One Out scheme.

RESULTS

The accuracy of the three-class model reaches an overall accuracy of 86.36%, and the precision per-class of the benign, nonmetastatic malignant, and metastatic malignant classes were 86.96%, 87.27%, and 77.78%, respectively.

DISCUSSION

SHapley Additive exPlanations were performed to visually show how the machine learning model made a specific decision. For each patient, the SHAP values expressed how each characteristic contributed to the classification result. Such information represents an added value for the clinical usability of a diagnostic system.

CONCLUSIONS

This is the first work that attempts to design an explainable machine-learning tool for the histological diagnosis of solid masses of the ovary.

Imaging of a Pelvic Mass: Uterine

The most common origin of a non-uterine pelvic mass is from the ovary. Ultrasound is the initial imaging modality of choice, additional imaging with computed tomography (CT) and/or magnetic resonance imaging (MRI) is performed in selected cases. Adnexal masses are also encountered as incidental findings during ultrasound, CT or MRI. Many of the adnexal masses that are surgically removed are benign. For optimal outcome and cost effective management, noninvasive risk stratification of such adnexal masses is necessary when discovered incidentally or when identified in a patient with a clinically detected pelvic mass. The American College of Radiology Ovarian-Adnexal Reporting Data System is a pattern-based scoring system for adnexal masses imaged with ultrasound and MRI, which assists clinicians to guide in the appropriate management based on evidence-based risk categories. Non-ovarian and non-uterine pelvic masses include fallopian tube abnormalities, paraovarian cysts, peritoneal inclusion cysts, and rare causes include masses that arise from the gastrointestinal tract or the sacrum. To distinguish non-ovarian masses from an ovarian tumor, a critical step is to identify a normal appearing ovary separate from the pelvic mass. This may be challenging in the post-menopausal woman with an atrophic ovary. MRI is a useful adjunctive modality in such cases. Extraovarian masses typically displace pelvic side wall vasculature medially, compress, encase or medially displace the ureters.

Comparison of the diagnostic efficiency between the O-RADS US risk stratification system and doctors' subjective judgment

BACKGROUND

This study aimed to compare the diagnostic efficiency of Ovarian-Adnexal Reporting and Data System (O-RADS) and doctors' subjective judgment in diagnosing the malignancy risk of adnexal masses.

METHODS

This was an analysis of 616 adnexal masses between 2017 and 2020. The clinical findings, preoperative ultrasound images, and pathological diagnosis were recorded. Each adnexal mass was evaluated by doctors' subjective judgment and O-RADS by two senior doctors and two junior doctors. A mass with an O-RADS grade of 1 to 3 was a benign tumor, and a mass with an O-RADS grade of 4-5 was a malignant tumor. All outcomes were compared with the pathological diagnosis.

RESULTS

Of the 616 adnexal masses, 469 (76.1%) were benign, and 147 (23.9%) were malignant. There was no difference between the area under the curve of O-RADS and the subjective judgment for junior doctors (0.83 (95% CI: 0.79-0.87) vs. 0.79 (95% CI: 0.76-0.83), p = 0.0888). The areas under the curve of O-RADS and subjective judgment were equal for senior doctors (0.86 (95% CI: 0.83-0.89) vs. 0.86 (95% CI: 0.83-0.90), p = 0.8904). O-RADS had much higher sensitivity than the subjective judgment in detecting malignant tumors for junior doctors (84.4% vs. 70.1%) and senior doctors (91.2% vs. 81.0%). In the subgroup analysis for detecting the main benign lesions of the mature cystic teratoma and ovarian endometriosic cyst, the junior doctors' diagnostic accuracy was obviously worse than the senior doctors' on using O-RADS.

CONCLUSIONS

O-RADS had excellent performance in predicting malignant adnexal masses. It could compensate for the lack of experience of junior doctors to a certain extent. Better performance in discriminating various benign lesions should be expected with some complement.

Ultrasound Features and Clinical Outcome of Patients with Ovarian Masses Diagnosed during Pregnancy: Experience of Single Gynecological Ultrasound Center

(1) Background: The number of adnexal masses detected during pregnancy has increased due to the use of first-trimester screening and increasingly advanced maternal age. Despite their low risk of malignancy, other risks associated with these masses include torsion, rupture and labor obstruction. Correct diagnosis and management are needed to guarantee both maternal and fetal safety. Adnexal masses may be troublesome to classify during pregnancy due to the increased volume of the uterus and pregnancy-related hormonal changes. Management should be based on ultrasound examination to provide the best treatment. The aim of this study was to describe the ultrasound features of ovarian masses detected during pregnancy and to optimize and personalize their management with the expertise of gynecologists, oncologists and sonographers. (2) Methods: Clinical, ultrasound, histological parameters and type of management (surveillance vs. surgery) were retrospectively retrieved. Patient management, perinatal outcomes and follow-up were also evaluated. (3) Results: according to the literature, these masses are most frequently benign, ultrasound follow-up is the best management, and obstetric outcomes are not considerably influenced by the presence of adnexal masses. (4) Conclusions: the management of patients with ovarian masses detected during pregnancy should be based on ultrasound examination, and a centralization in referral centers for ovarian masses should be considered.

Subjective assessment and IOTA ADNEX model in evaluation of adnexal masses in patients with history of breast cancer

OBJECTIVE

To evaluate the performance of subjective assessment and the Assessment of Different NEoplasias in the adneXa (ADNEX) model in discriminating between benign and malignant adnexal tumors and between metastatic and primary adnexal tumors in patients with a personal history of breast cancer.

METHODS

This was a retrospective single-center study including patients with a history of breast cancer who underwent surgery for an adnexal mass between 2013 and 2020. All patients had been examined with transvaginal or transrectal ultrasound using a standardized examination technique and all ultrasound reports had been stored and were retrieved for the purposes of this study. The specific diagnosis suggested by the original ultrasound examiner in the retrieved report was analyzed. For each mass, the ADNEX model risks were calculated prospectively and the highest relative risk was used to categorize each into one of five categories (benign, borderline, primary Stage I, primary Stages II-IV or metastatic ovarian cancer) for analysis of the ADNEX model in predicting the specific tumor type. The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal tumors and between primary and metastatic adnexal tumors was evaluated, using final histology as the reference standard.

RESULTS

Included in the study were 202 women with a history of breast cancer who underwent surgery for an adnexal mass. At histology, 93/202 (46.0%) masses were benign, 76/202 (37.6%) were primary malignancies (four borderline and 72 invasive tumors) and 33/202 (16.3%) were metastases. The original ultrasound examiner classified correctly 79/93 (84.9%) benign adnexal masses, 72/76 (94.7%) primary adnexal malignancies and 30/33 (90.9%) metastatic tumors. Subjective ultrasound evaluation had a sensitivity of 93.6%, specificity of 84.9% and accuracy of 89.6%, while the ADNEX model had higher sensitivity (98.2%) but lower specificity (78.5%), with similar accuracy (89.1%), in discriminating between benign and malignant ovarian masses. Subjective evaluation had a sensitivity of 51.5%, specificity of 88.8% and accuracy of 82.7% in distinguishing metastatic and primary tumors (including benign, borderline and invasive tumors), and the ADNEX model had a sensitivity of 63.6%, specificity of 84.6% and similar accuracy (81.2%).

CONCLUSIONS

The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal masses in this series of patients with history of breast cancer was relatively similar. Both subjective assessment and the ADNEX model demonstrated good accuracy and specificity in discriminating between metastatic and primary tumors, but the sensitivity was low. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Validation of the diagnostic efficacy of O-RADS in adnexal masses

The aim of this study was to validate the performance of the Ovarian-Adnexal Reporting and Data Systems (O-RADS) series models proposed by the American College of Radiology (ACR) in the preoperative diagnosis of adnexal masses (AMs). Two experienced sonologists examined 218 patients with AMs and gave the assessment results after the examination. Pathological findings were used as a reference standard. Of the 218 lesions, 166 were benign and 52 were malignant. Based on the receiver operating characteristic (ROC) curve, we defined a malignant lesion as O-RADS > 3 (i.e., lesions in O-RADS categories 4 and 5 were malignant). The area under the curve (AUC) of O-RADS (v2022) was 0.970 (95% CI 0.938-0.988), which wasn't statistically significantly different from the O-RADS (v1) combined Simple Rules Risk (SRR) assessment model with the largest AUC of 0.976 (95% CI 0.946-0.992) (p = 0.1534), but was significantly higher than the O-RADS (v1) (AUC = 0.959, p = 0.0133) and subjective assessment (AUC = 0.918, p = 0.0255). The O-RADS series models have good diagnostic performance for AMs. Where, O-RADS (v2022) has higher accuracy and specificity than O-RADS (v1). The accuracy and specificity of O-RADS (v1), however, can be further improved when combined with SRR assessment.

Application of Ultrasound Scores (Subjective Assessment, Simple Rules Risk Assessment, ADNEX Model, O-RADS) to Adnexal Masses of Difficult Classification

BACKGROUND

Ultrasound features help to differentiate benign from malignant masses, and some of them are included in the ultrasound (US) scores. The main aim of this work is to describe the ultrasound features of certain adnexal masses of difficult classification and to analyse them according to the most frequently used US scores.

METHODS

Retrospective studies of adnexal lesions are difficult to classify by US scores in women undergoing surgery. Ultrasound characteristics were analysed, and masses were classified according to the Subjective Assessment of the ultrasonographer (SA) and other US scores (IOTA Simple Rules Risk Assessment-SRRA, ADNEX model with and without CA125 and O-RADS).

RESULTS

A total of 133 adnexal masses were studied (benign: 66.2%, n:88; malignant: 33.8%, n:45) in a sample of women with mean age 56.5 ± 7.8 years. Malignant lesions were identified by SA in all cases. Borderline ovarian tumors (n:13) were not always detected by some US scores (SRRA: 76.9%, ADNEX model without and with CA125: 76.9% and 84.6%) nor were serous carcinoma (n:19) (SRRA: 89.5%), clear cell carcinoma (n:9) (SRRA: 66.7%) or endometrioid carcinoma (n:4) (ADNEX model without CA125: 75.0%). While most teratomas and serous cystadenomas have been correctly differentiated, other benign lesions were misclassified because of the presence of solid areas or papillae. Fibromas (n:13) were better identified by SA (23.1% malignancy), but worse with the other US scores (SRRA: 69.2%, ADNEX model without and with CA125: 84.6% and 69.2%, O-RADS: 53.8%). Cystoadenofibromas (n:10) were difficult to distinguish from malignant masses via all scores except SRRA (SA: 70.0%, SRRA: 20.0%, ADNEX model without and with CA125: 60.0% and 50.0%, O-RADS: 90.0%). Mucinous cystadenomas (n:12) were misdiagnosed as malignant in more than 15% of the cases in all US scores (SA: 33.3%, SRRA: 16.7%, ADNEX model without and with CA125: 16.7% and 16.7%, O-RADS:41.7%). Brenner tumors are also difficult to classify using all scores.

CONCLUSION

Some malignant masses (borderline ovarian tumors, serous carcinoma, clear cell carcinoma, endometrioid carcinomas) are not always detected by US scores. Fibromas, cystoadenofibromas, some mucinous cystadenomas and Brenner tumors may present solid components/papillae that may induce confusion with malignant lesions. Most teratomas and serous cystadenomas are usually correctly classified.

Can the ultrasound microcystic pattern accurately predict borderline ovarian tumors?

OBJECTIVE

To investigate whether the ultrasound microcystic pattern (MCP) can accurately predict borderline ovarian tumors (BOTs).

METHODS

A retrospective collection of 393 patients who met the inclusion criteria was used as the study population. Indicators that could well identify BOT in different pathological types of tumors were derived by multivariate unordered logistic regression analysis. Finally, the correlation between ultrasound MCP and pathological features was analyzed.

RESULTS

(1) MCP was present in 55 of 393 ovarian tumors, including 34 BOTs (34/68, 50.0%), 16 malignant tumors (16/88, 18.2%), and 5 benign tumors (5/237, 2.1%). (2) Univariate screening showed significant differences (P < 0.05) in patient age, CA-125 level, ascites, > 10 cyst locules, a solid component, blood flow, and MCP among BOTs, benign ovarian tumors, and malignant ovarian tumors. (3) Multivariate unordered logistic regression analysis showed that the blood flow, > 10 cyst locules, and MCP were significant factors in identifying BOTs (P < 0.05). (4) The pathology of ovarian tumors with MCP showed "bubble"- or "fork"- like loose tissue structures.

CONCLUSION

MCP can be observed in different pathological types of ovarian tumors and can be used as a novel sonographic marker to differentiate between BOTs, benign tumors and malignant tumors. MCP may arise as a result of anechoic cystic fluid filling the loose tissue gap.

Ultrasound Features and Ultrasound Scores in the Differentiation between Benign and Malignant Adnexal Masses

BACKGROUND

Several ultrasound (US) features help ultrasound experts in the classification of benign vs. malignant adnexal masses. US scores serve in this differentiation, but they all have misdiagnoses. The main objective of this study is to evaluate what ultrasound characteristics are associated with malignancy influencing ultrasound scores.

METHODS

This is a retrospective analysis of ultrasound features of adnexal lesions of women managed surgically. Ultrasound characteristics were analyzed, and masses were classified by subjective assessment of the ultrasonographer (SA) and other ultrasound scores (IOTA Simple Rules Risk Assessment SRRA, ADNEX model, and O-RADS).

RESULTS

Of a total of 187 adnexal masses studied, 134 were benign (71.7%) and 53 were malignant (28.3%). SA, IOTA SRRA, ADNEX model with or without CA125 and O-RADS had high levels of sensitivity (93.9%, 81.1%, 94.3%, 88.7%, 98.1%) but lower specificity (80.2%, 82.1%, 82.8%, 77.6%, 73.1%) with similar AUC (0.87, 0.87, 0.92, 0.90, 0.86). Ultrasound features significantly related with malignancy were the presence of irregular contour, absence of acoustic shadowing, vascularized solid areas, ≥1 papillae, vascularized septum, and moderate-severe ascites.

CONCLUSION

IOTA SRRA, ADNEX model, and O-RADS can help in the classification of benign and malignant masses. Certain ultrasound characteristics studied in ultrasound scores are associated with malignancy.

Do Exophytic and Endophytic Patterns in Borderline Ovarian Tumors Have Different Prognostic Implications? A Large Multicentric Experience

Borderline ovarian tumor (BOT) accounts for 15-20% of all epithelial ovarian tumors. Concerns have arisen about the clinical and prognostic implications of BOT with exophytic growth patterns. We retrospectively reviewed all cases of BOT patients surgically treated from 2015 to 2020. Patients were divided into an endophytic pattern (with intracystic tumor growth and intact ovarian capsule) and an exophytic pattern (with tumor growth outside the ovarian capsule) group. Among the 254 patients recruited, 229 met the inclusion criteria, and of these, 169 (73.8%) belonged to the endophytic group. The endophytic group showed more commonly an early FIGO stage than the exophytic group (100.0% vs. 66.7%, p < 0.001). Furthermore, tumor cells in peritoneal washing (20.0% vs. 0.6%, p < 0.001), elevated Ca125 levels (51.7% vs. 31.4%, p = 0.003), peritoneal implants (0 vs. 18.3%, p < 0.001), and invasive peritoneal implants (0 vs. 5%, p = 0.003) were more frequently observed in the exophytic group. The survival analysis showed 15 (6.6%) total recurrences, 9 (5.3%) in the endophytic and 6 (10.0%) patients in the exophytic group (p = 0.213). At multivariable analysis, age (p = 0.001), FIGO stage (p = 0.002), fertility-sparing surgery (p = 0.001), invasive implants (p = 0.042), and tumor spillage (p = 0.031) appeared significantly associated with recurrence. Endophytic and exophytic patterns in borderline ovarian tumors show superimposable recurrence rates and disease-free survival.

Performance of IOTA Simple Rules Risks, ADNEX Model, Subjective Assessment Compared to CA125 and HE4 with ROMA Algorithm in Discriminating between Benign, Borderline and Stage I Malignant Adnexal Lesions

BACKGROUND

Borderline ovarian tumors (BOTs) and early clinical stage malignant adnexal masses can make sonographic diagnosis challenging, while the clinical utility of tumor markers, e.g., CA125 and HE4, or the ROMA algorithm, remains controversial in such cases.

OBJECTIVE

To compare the IOTA group Simple Rules Risk (SRR), the ADNEX model and the subjective assessment (SA) with serum CA125, HE4 and the ROMA algorithm in the preoperative discrimination between benign tumors, BOTs and stage I malignant ovarian lesions (MOLs).

METHODS

A multicenter retrospective study was conducted with lesions classified prospectively using subjective assessment and tumor markers with the ROMA. The SRR assessment and ADNEX risk estimation were applied retrospectively. The sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-) were calculated for all tests.

RESULTS

In total, 108 patients (the median age: 48 yrs, 44 postmenopausal) with 62 (79.6%) benign masses, 26 (24.1%) BOTs and 20 (18.5%) stage I MOLs were included. When comparing benign masses with combined BOTs and stage I MOLs, SA correctly identified 76% of benign masses, 69% of BOTs and 80% of stage I MOLs. Significant differences were found for the presence and size of the largest solid component (p = 0.0006), the number of papillary projections (p = 0.01), papillation contour (p = 0.008) and IOTA color score (p = 0.0009). The SRR and ADNEX models were characterized by the highest sensitivity (80% and 70%, respectively), whereas the highest specificity was found for SA (94%). The corresponding likelihood ratios were as follows: LR+ = 3.59 and LR- = 0.43 for the ADNEX; LR+ = 6.40 and LR- = 0.63 for SA and LR+ = 1.85 with LR- = 0.35 for the SRR. The sensitivity and specificity of the ROMA test were 50% and 85%, respectively, with LR+ = 3.44 and LR- = 0.58. Of all the tests, the ADNEX model had the highest diagnostic accuracy of 76%.

CONCLUSIONS

This study demonstrates the limited value of diagnostics based on CA125 and HE4 serum tumor markers and the ROMA algorithm as independent modalities for the detection of BOTs and early stage adnexal malignant tumors in women. SA and IOTA methods based on ultrasound examination may present superior value over tumor marker assessment.

A New Insight on Exophytic Serous Borderline Adnexal Tumors: Specific Sonographic Features

OBJECTIVES

To characterize and compare the sonographic features of exophytic serous borderline ovarian tumors (ESBOT) with those of high-grade serous carcinoma of the ovary (HGSC).

METHODS

Seven patients with histological diagnosis of ESBOT diagnosed between 2011 and 2019 and 10 consecutive cases of HGSC detected during 2019, both depicting an exophytic growth pattern, were identified retrospectively. The sonographic imaging of the masses was reassessed and characterized according to the International Ovarian Tumor Analysis terms.

RESULTS

A unilateral irregular solid adnexal mass was demonstrated in all patients with ESBOT. The mass typically wrapped an apparently normal ovary, with a clear demarcation line depicted between them and it contained tiny cystic inclusions and calcifications. On color Doppler study of all the ESBOT cases, a unique vascular pattern could be demonstrated: an intratumoral vascular bundle originating from the ovarian vessels and supplying a rich radial blood flow to the tumor periphery. These characteristic morphological and color Doppler features could not be observed in any of the HGSC cases (P < .001). In 42.8% of the patients with ESBOT, additional unilocular-solid components (ipsilateral or contralateral) could be detected, whereas all the HGSC patients presented with a multilocular-solid tumor morphology (P < .001). The interface of the external mass border with the adjacent pelvic walls was regular in all the cases with ESBOT, whereas in 80% of HGSC patients, it was irregular, suggesting invasiveness (P = .002).

CONCLUSIONS

ESBOT can mimic HGSC. Our results suggest that ESBOT has specific B-mode and color Doppler features, enabling differentiation from HGSC and planning appropriate intervention.

The value of contrast-enhanced ultrasonography in differential diagnosis of benign and malignant ovarian sex cord stromal tumors

BACKGROUND

Sex cord-stromal tumors (SCSTs) are uncommon neoplasms that are typically difficult to diagnose before surgery due to limited experience in their medical imaging. Contrast-enhanced ultrasonography (CEUS) can evaluate the microvessel density of tumors, and the microvessel density of malignant tumors is significantly greater than that of benign tumors, so this provides a method for CEUS to differentiate benign and malignant tumors.

METHODS

The CEUS diagnoses of 31 patients with pathologically confirmed SCSTs were retrospectively analyzed and compared to conventional ultrasound-based diagnoses. Based on the pathological results, the patients were divided into benign and non-benign groups. Using pathology as the gold standard, four-table data were used to evaluate the authenticity of conventional ultrasonography and CEUS.

RESULTS

Among these 31 SCST patients, only the size of the lesion and the stripy hypoenhancement on CEUS differed significantly between the benign group and the non-benign group (P<0.05). In the benign group (n=25), 22 patients showed sparse stripes of hypoenhancement, 1 showed no enhancement, and 2 showed hyperenhancement. In 5 cases of malignant SCSTs, 4 showed hyperenhancement (with non-enhanced areas inside the tumor), and 1 showed sparse strips of hypoenhancement; in 1 case of borderline SCST, the tumor showed uniform hyperenhancement. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy rate of the conventional ultrasound diagnoses for the 31 SCST patients were 52.0%, 16.7%, 72.2%, 7.7%, and 45.2%, respectively. In relation to CEUS, sparse strips of hypoenhancement or no enhancement were valuable diagnostic criteria for diagnosing benign SCSTs. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy rate of CEUS were 92.0%, 83.3%, 95.8%, 71.4%, and 90.3%, respectively. The accuracy of CEUS was higher than that of conventional US, and the difference was statistically significant (χ2=14.467, P=0.000).

CONCLUSIONS

Sparse strips of hypoenhancement or no enhancement on CEUS are the characteristic manifestations of benign SCSTs, and hyperenhancement (with a non-enhanced area observable inside the mass) may be suggestive of malignant tumors. CEUS significantly improved the differentiation of benign and malignant SCSTs.

The Multimodal Ultrasound Features of Ovarian Serous Surface Papillary Borderline Tumor

Aim

Ovarian serous surface papillary borderline tumor (OSSPBT) is very rare. Combined with clinical and pathological features, we aim to investigate the multimodal ultrasound features of OSSPBT.

Patients and Methods

There were only 18 patients diagnosed with OSSPBT among the 142 patients who were diagnosed with borderline serous ovarian tumor by pathology from June 2008 to December 2020 in our hospital. Their clinical data, conventional ultrasound, two-dimensional contrast-enhanced ultrasound (2D-CEUS), three-dimensional contrast-enhanced ultrasound (3D-CEUS) characteristics, pathology, and prognosis were retrospectively analyzed.

Results

The 18 patients had no specific clinical symptoms. Multiple implantable nodules were found in 8 patients (44.4%), ascites in 13 patients (72.2%), and elevated carbohydrate antigen 125 (CA125) in 15 patients (83.3%). After excluding 2 misdiagnosed patients from 18 patients, 26 tumors in 16 patients (6 unilateral and 10 bilateral) were studied. Conventional ultrasound findings of OSSPBT showed that large solid masses around normal ovary without capsule, and numerous small dense anechoic areas were observed in the parenchyma of the lesion, with strong speckle echo ("blizzard" sign) of varying degrees. The 2D-CEUS and 3D-CEUS showed a normal ovary in the center surrounded by a radial blood supply of OSSPBT with thick and irregular branches. Histopathologically, the papillary fibrous stalk of OSSPBT had a large number of sand bodies and tortuous dilated microvessels. All patients had no recurrence after surgery, and two of them delivered successfully through assisted reproductive technology.

Conclusion

OSSPBT has a good prognosis. Its conventional ultrasound is characterized by irregular solid masses surrounding normal ovaries and a large number of "blizzard" signs. It showed low enhancement of eccentricity with irregular radial branches centered on the ovary by CEUS.

Imaging in gynecological disease (23): clinical and ultrasound characteristics of ovarian carcinosarcoma

OBJECTIVE

To describe the clinical and ultrasound characteristics of ovarian carcinosarcoma.

METHODS

This was a retrospective multicenter study. Patients with a histological diagnosis of ovarian carcinosarcoma, who had undergone preoperative ultrasound examination between 2010 and 2019, were identified from the International Ovarian Tumor Analysis (IOTA) database. Additional patients who were examined outside of the IOTA study were identified from the databases of the participating centers. The masses were described using the terms and definitions of the IOTA group. Additionally, two experienced ultrasound examiners reviewed all available images to identify typical ultrasound features using pattern recognition.

RESULTS

Ninety-one patients with ovarian carcinosarcoma who had undergone ultrasound examination were identified, of whom 24 were examined within the IOTA studies and 67 were examined outside of the IOTA studies. Median age at diagnosis was 66 (range, 33-91) years and 84/91 (92.3%) patients were postmenopausal. Most patients (67/91, 73.6%) were symptomatic, with the most common complaint being pain (51/91, 56.0%). Most tumors (67/91, 73.6%) were International Federation of Gynecology and Obstetrics (FIGO) Stage III or IV. Bilateral lesions were observed on ultrasound in 46/91 (50.5%) patients. Ascites was present in 38/91 (41.8%) patients. The median largest tumor diameter was 100 (range, 18-260) mm. All ovarian carcinosarcomas contained solid components, and most were described as solid (66/91, 72.5%) or multilocular-solid (22/91, 24.2%). The median diameter of the largest solid component was 77.5 (range, 11-238) mm. Moderate or rich vascularization was found in 78/91 (85.7%) cases. Retrospective analysis of ultrasound images and videoclips using pattern recognition in 73 cases revealed that all tumors had irregular margins and inhomogeneous echogenicity of the solid components. Forty-seven of 73 (64.4%) masses appeared as a solid tumor with cystic areas. Cooked appearance of the solid tissue was identified in 28/73 (38.4%) tumors. No pathognomonic ultrasound sign of ovarian carcinosarcoma was found.

CONCLUSIONS

Ovarian carcinosarcomas are usually diagnosed in postmenopausal women and at an advanced stage. The most common ultrasound appearance is a large solid tumor with irregular margins, inhomogeneous echogenicity of the solid tissue and cystic areas. The second most common pattern is a large multilocular-solid mass with inhomogeneous echogenicity of the solid tissue. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

The challenging screen detection of ovarian cancer in BRCA mutation carriers adhering to a 6-month follow-up program: results from a 6-years surveillance

OBJECTIVE

Approximately 25% of ovarian cancer (OC) cases are related to an inherited predisposition. Genetic mutations for the oncosuppressor genes BRCA1 and 2 have the best-known linkage to a higher incidence of OC and breast cancer, in approximately 70% to 80% of hereditary OC cases. To provide the first comprehensive clinical description of screen-detected (SD) OCs during a 6-years surveillance of a cohort of young BRCA carriers and carriers who refuse risk-reducing salpingo-oophorectomy.

METHODS

A prospective cohort study in a university hospital describing 191 women with BRCA1 and 2 mutations adhering continuously to our surveillance between 2015 and 2020, including a 6-monthly evaluation of cancer antigen 125 (CA 125) with concomitant transvaginal ultrasound (TVUS) performed by a dedicated specialist. Main outcomes were tumor's laterality, CA 125 at diagnosis, TVUS and computed tomography (CT) findings.

RESULTS

Risk-reducing salpingo-oophorectomy was performed in 58/191 (30.4%) of mutation carriers during the study period (one OC case identified). Nine SD-OCs and no interval OCs were found in the remaining 133 women. OCs (FIGO stage I or II: 88.9%) occur mainly in BRCA 1 (77.8%), being bilateral in 85.7% BRCA 1 and unilateral in 100% BRCA 2. No lesions involved only the tubes: left ovaries/tubes were more frequently involved. We have described three new possible scenarios regarding imaging: 1) Evident cases (33.3%, TVUS and CT obvious for OC, CA 125 sensitivity: 100%), 2) Possible cases (55.6%, TVUS and CT are in general accordance, documenting new TVUS signs: increased solid pattern of the ovary with peripheral cortical small cysts, hypoechoic circular mass near the ovary, intraparenchymal small hyperechoic foci), and 3) Hidden cases (11.1%, the smallest lesion but the highest stage (IIIA2), with CA 125 44.2 U/mL and concomitant endometrial hyperplasia).

CONCLUSIONS

Different diagnostic tools must integrate to ensure early diagnosis of OC in BRCA mutation carriers adhering to a follow-up program.

Ultrasound features of polypoid endometriosis: a case report and a short review of Literature

Introduction:

Polypoid endometriosis is a rare variant of endometriosis characterized by histological features resembling an endometrial polyp. Lesions frequently affect the ovaries presenting as adnexal masses which may mimic malignancy, with an extremely complex differential diagnosis due to the poor evidence reported in Literature.

Case description:

In this report, we describe the case of a 43 years old woman referred to pelvic transvaginal ultrasound examination for recurrent abdominal pain, in whom sonography revealed a pelvic mass with features highly suspicious for ovarian carcinoma. Surgical removal allowed histopathological diagnosis of polypoid endometriosis, with no signs of malignancy. At ultrasound examination, the lesion appeared as a multilocular-solid mass, with low-level echogenicity of cystic content, multiple papillary projections, and solid areas with high vascularization and apparent infiltration of the uterus. At retrospective review of the sonographic images after pathological examination, some features mirroring the histological architecture of polypoid endometriosis could be identified in the solid components of the mass: these included the hyperechoic appearance, the rounded outline of the intracystic projections, and the vascularization pattern with a single central vessel with branching.

Conclusions:

To date, this is the first work providing a detailed ultrasonographic description of polypoid endometriosis using shared terms and definitions and relating these findings with available evidence about radiologic and histopathologic features. The report shows how this condition could strongly mimick ovarian malignancy, though several sonographic features can be identified reflecting the histopathological patterns of those lesions.

Diagnosis of Ovarian Neoplasms Using Nomogram in Combination With Ultrasound Image-Based Radiomics Signature and Clinical Factors

Objectives: To establish and validate a nomogram integrating radiomics signatures from ultrasound and clinical factors to discriminate between benign, borderline, and malignant serous ovarian tumors. Materials and methods: In this study, a total of 279 pathology-confirmed serous ovarian tumors collected from 265 patients between March 2013 and December 2016 were used. The training cohort was generated by randomly selecting 70% of each of the three types (benign, borderline, and malignant) of tumors, while the remaining 30% was included in the validation cohort. From the transabdominal ultrasound scanning of ovarian tumors, the radiomics features were extracted, and a score was calculated. The ability of radiomics to differentiate between the grades of ovarian tumors was tested by comparing benign vs borderline and malignant (task 1) and borderline vs malignant (task 2). These results were compared with the diagnostic performance and subjective assessment by junior and senior sonographers. Finally, a clinical-feature alone model and a combined clinical-radiomics (CCR) model were built using predictive nomograms for the two tasks. Receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA) were performed to evaluate the model performance. Results: The US-based radiomics models performed satisfactorily in both the tasks, showing especially higher accuracy in the second task by successfully discriminating borderline and malignant ovarian serous tumors compared to the evaluations by senior sonographers (AUC = 0.789 for seniors and 0.877 for radiomics models in task one; AUC = 0.612 for senior and 0.839 for radiomics model in task 2). We showed that the CCR model, comprising CA125 level, lesion location, ascites, and radiomics signatures, performed the best (AUC = 0.937, 95%CI 0.905-0.969 in task 1, AUC = 0.924, 95%CI 0.876-0.971 in task 2) in the training as well as in the validation cohorts (AUC = 0.914, 95%CI 0.851-0.976 in task 1, AUC = 0.890, 95%CI 0.794-0.987 in task 2). The calibration curve and DCA analysis of the CCR model more accurately predicted the classification of the tumors than the clinical features alone. Conclusion: This study integrates novel radiomics signatures from ultrasound and clinical factors to create a nomogram to provide preoperative diagnostic information for differentiating between benign, borderline, and malignant ovarian serous tumors, thereby reducing unnecessary and risky biopsies and surgeries.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumors

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumors, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

Ultrasound evaluation of ovarian masses and assessment of the extension of ovarian malignancy

The current review sums up the literature on the diagnostic performance of models to predict malignancy in adnexal masses and the ability of ultrasound to make a specific diagnosis in adnexal masses. A summary of the role of ultrasound in assessing the extension of malignant ovarian disease is also provided.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumours

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumours, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumours and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumours and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

Ultrasound, macroscopic and histological features of serous epithelial ovarian carcinomas

We present a video showing two cases of serous epithelial ovarian carcinomas. The first video shows clinical, ultrasound, macroscopic, and histological features of a patient with high grade serous ovarian carcinoma. The second video presents clinical, ultrasound, macroscopic, and histological features of a patient with low grade serous ovarian carcinoma.

Imaging modalities in fertility preservation in patients with gynecologic cancers

Fertility preservation is an integral component of clinical decision-making and treatment design. However, the selection criteria on imaging for patients eligible for fertility preservation is still unclear. The present review aimed to summarize the main findings reported in both the literature and international guidelines on the role of imaging in the selection of patients for fertility preservation. A search strategy was developed and applied to PubMed, Scopus, Web of Science, and EMBASE to identify previous citations reporting imaging and fertility preservation in patients with gynecological cancer. We also retrieved the published guidelines on the eligibility criteria for fertility-sparing treatment of gynecological neoplasms. A description of the internal multidisciplinary guidelines, clinically in use in our institution, is provided with representative clinical cases. The literature review revealed 1291 articles and 18 of these were selected for the analysis. Both ultrasound and MRI represented the primary imaging methods for selecting patients for fertility preservation in cervical and endometrial cancers. Eligibility criteria of fertility-sparing management in patients with cervical cancer were: tumor size <2 cm, tumor distance from the internal os >1 cm, and no parametrium invasion. For patients with endometrial cancer, these included no myometrial and cervical stroma invasion. Both ultrasound and MRI play a key role in characterizing adnexal masses. These modalities provide a useful tool in identifying small ovarian lesions, thus key in the surveillance of patients after fertility sparing surgery. However, efficacy in excluding disease beyond the ovary remains limited. This review provides an update of the literature and schematic outline for the counseling and management of patients with the desire for fertility preservation.

Misdiagnosis of High-grade Serous Ovarian Cancer With BRCA Mutation as Endometriotic Cyst Due to Its Unique Gross Morphology: A Case Report and Literature Review

It is believed that high-grade serous ovarian cancer (HGSOC) is a solid or multilocular-solid cancer. Here, we report the case of a 40-yr-old woman with a left ovarian unilocular cyst. Ultrasonography and computed tomographic examination confirmed that the cyst was thin-walled and homogenous in thickness without mural nodules. It was considered to be an endometriotic cyst. Left ovarian cyst excision specimens proved it to be HGSOC after pathologic examination. Therefore, the patient underwent radical surgery for HGSOC. Pathologic examination of radical resection specimens confirmed that the HGSOC was still in FIGO stage IA and no fallopian tube lesion was found. Considering that the patient had a history of breast cancer in both the breasts at a young age, it was hypothesized that the breast cancer susceptibility gene (BRCA) gene may have a germline mutation. Next-generation sequencing confirmed the BRCA1 (c.3770_3771delAG) germline mutation in this patient. Previous studies have reported the special morphological characteristics and growth pattern of HGSOC with BRCA mutation in the advanced stage. Our case demonstrates that HGSOC with the BRCA mutation can also be a unilocular cyst with a thin wall and uniform thickness without a mural nodule, and in the early stage, may have unique gross morphology.

Performance of the IOTA ADNEX Model on Selected Group of Patients with Borderline Ovarian Tumours

Background and objectives: ultrasound is considered to be the primary tool for preoperative assessment of ovarian masses; however, the discrimination of borderline ovarian tumours (BOTs) is challenging, and depends highly on the experience of the sonographer. The Assessment of Different NEoplasias in the adneXa (ADNEX) model is considered to be a valuable diagnostic tool for preoperative assessment of ovarian masses; however, its performance for BOTs has not been widely studied, due to the low prevalence of these tumours. The aim of this study was to evaluate the performance of ADNEX model for preoperative diagnosis of BOTs. Methods: retrospective analysis of preoperative ultrasound datasets of patients diagnosed with BOTs on the final histology after performed surgery was done at a tertiary oncogynaecology centre during the period of 2012–2018. Results: 85 patients were included in the study. The performance of ADNEX model based on absolute risk (AR) improved with the selection of a more inclusive cut-off value, varying from 47 (60.3%) correctly classified cases of BOTs, with the selected cut-off of 20%, up to 67 (85.9%) correctly classified cases of BOTs with the cut-off value of 3%. When relative risk (RR) was used to classify the tumours, 59 (75.6%) cases were identified correctly. Forty (70.2%) cases of serous and 16 (72.7%) cases of mucinous BOTs were identified when AR with a 10% cut-off value was applied, compared to 44 (77.2%) and 15 (68.2%) cases of serous and mucinous BOTs, correctly classified by RR. The addition of Ca125 improved the performance of ADNEX model for all BOTs in general, and for different subtypes of BOTs. However, the differences were insignificant. Conclusions: The International Ovarian Tumour Analysis (IOTA) ADNEX model performs well in discriminating BOTs from other ovarian tumours irrespective of the subtype. The calculation based on RR or AR with the cut-off value of at least 10% should be used when evaluating for BOTs.

Therapeutic Approach to Low-Grade Serous Ovarian Carcinoma: State of Art and Perspectives of Clinical Research

Low-grade serous ovarian carcinoma (LGSOC) is a distinct pathologic and clinical entity, characterized by less aggressive biological behavior, lower sensitivity to chemotherapy and longer survival compared with high-grade serous ovarian carcinoma. LGSOC often harbors activating mutations of genes involved in mitogen activated protein kinase (MAPK) pathway. Patients with disease confined to the gonad(s) should undergo bilateral salpingo-oophorectomy, total hysterectomy and comprehensive surgical staging, although fertility-sparing surgery can be considered in selected cases. Women with stage IA-IB disease should undergo observation alone after surgery, whereas observation, chemotherapy or endocrine therapy are all possible options for those with stage IC-IIA disease. Patients with advanced disease should undergo primary debulking surgery with the aim of removing all macroscopically detectable disease, whereas neoadjuvant chemotherapy followed by interval debuking surgery. After surgery, the patients can receive either carboplatin plus paclitaxel followed by endocrine therapy or endocrine therapy alone. Molecularly targeted agents, and especially MEK inhibitors and Cyclin-dependent kinase (CDK) inhibitors, are currently under evaluation. Additional research on the genomics of LGSOC and clinical trials on the combination of MEK inhibitors with hormonal agents, other molecularly targeted agents or metformin, are strongly warranted to improve the prognosis of patients with this malignancy.

MRI-Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study

BACKGROUND

Preoperative differentiation of borderline from malignant epithelial ovarian tumors (BEOT from MEOT) can impact surgical management. MRI has improved this assessment but subjective interpretation by radiologists may lead to inconsistent results.

PURPOSE

To develop and validate an objective MRI-based machine-learning (ML) assessment model for differentiating BEOT from MEOT, and compare the performance against radiologists' interpretation.

STUDY TYPE

Retrospective study of eight clinical centers.

POPULATION

In all, 501 women with histopathologically-confirmed BEOT (n = 165) or MEOT (n = 336) from 2010 to 2018 were enrolled. Three cohorts were constructed: a training cohort (n = 250), an internal validation cohort (n = 92), and an external validation cohort (n = 159).

FIELD STRENGTH/SEQUENCE

Preoperative MRI within 2 weeks of surgery. Single- and multiparameter (MP) machine-learning assessment models were built utilizing the following four MRI sequences: T₂ -weighted imaging (T₂ WI), fat saturation (FS), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), and contrast-enhanced (CE)-T₁ WI.

ASSESSMENT

Diagnostic performance of the models was assessed for both whole tumor (WT) and solid tumor (ST) components. Assessment of the performance of the model in discriminating BEOT vs. early-stage MEOT was made. Six radiologists of varying experience also interpreted the MR images.

STATISTICAL TESTS

Mann-Whitney U-test: significance of the clinical characteristics; chi-square test: difference of label; DeLong test: difference of receiver operating characteristic (ROC).

RESULTS

The MP-ST model performed better than the MP-WT model for both the internal validation cohort (area under the curve [AUC] = 0.932 vs. 0.917) and external validation cohort (AUC = 0.902 vs. 0.767). The model showed capability in discriminating BEOT vs. early-stage MEOT, with AUCs of 0.909 and 0.920, respectively. Radiologist performance was considerably poorer than both the internal (mean AUC = 0.792; range, 0.679-0.924) and external (mean AUC = 0.797; range, 0.744-0.867) validation cohorts.

DATA CONCLUSION

Performance of the MRI-based ML model was robust and superior to subjective assessment of radiologists. If our approach can be implemented in clinical practice, improved preoperative prediction could potentially lead to preserved ovarian function and fertility for some women.

LEVEL OF EVIDENCE

Level 4.

TECHNICAL EFFICACY

Stage 2. J. Magn. Reson. Imaging 2020;52:897-904.

[Borderline Ovarian Tumours: CNGOF Guidelines for Clinical Practice - Imaging]

OBJECTIVE

To determine the place of imaging and the performance of different imaging techniques (transvaginal ultrasound with or without Doppler, scoring, CT, MRI) to differentiate benign tumour, borderline ovarian tumour (BOT) and malignant ovarian tumor. Differentiate the histological subtypes of BOT (serous, sero-mucinous, mucinous) and prediction in imaging of the possibility of conservative treatment.

METHODS

The research was carried out over the last 16 years using the terms "MeSH" based on the query of the Medline® database and supplemented by the review of references contained in the meta-analyzes, systematic reviews and original articles included.

RESULTS

Endo-vaginal and suprapubic ultrasonography is recommended for analysis of an ovarian mass (grade A). In the case of ultrasound by a referent, subjective analysis is the recommended technique (grade A). In case of echography by a non-referent, the use of "Simple Rules" is recommended (grade A) and should be best combined with subjective analysis to rejoin the performance of a sonographer refer (grade A). In cases of undetermined ovarian lesions in endovaginal ultrasound and suprapubic ultrasound, it is recommended to perform a pelvic MRI (grade A). The MRI protocol should include T2, T1, T1 sequences with fat saturation, diffusion, injected dynamics, and after gadolinium injection (grade B). To characterize an MRI-adnexal image, it is recommended to include a risk score for malignancy (ADNEX-MR/O-RADS) (grade C) in the report and to formulate an anatomopathological hypothesis (Grade C). The predictive signs of benignity in front of a cyst with endocystic vegetations are the low number, the small size, the presence of calcifications and the absence of Doppler flow in case of size greater than 10mm in echography (LP 4) and a curve of type 1 MRI (LP4). MRI is recommended for suspicious lesions of BOT in ultrasound (grade B) or indeterminate lesions in ultrasound (grade A). There is no data to support the usefulness of CT or PET-CT for BOT. Morphological criteria in ultrasound and MRI exist to differentiate BOT from invasive tumors regardless of grade (NP 2). Pelvic MRI is recommended to characterize a tumor suggestive of ultrasound BOT (grade C). No recommendations can be made about the use of combined ultrasound, biological, and menopausal status scores for the diagnosis of BOT. The diagnostic performance of imaging to detect peritoneal implants of BOT is not known. The assessment of the invasiveness of peritoneal implants of imaging BOT has not been evaluated. The association of macroscopic signs in MRI makes it possible to differentiate the different subtypes - serous, sero-mucinous and mucinous (intestinal type) - of BOT, despite the overlap of certain presentations (LP3). The analysis of macroscopic MRI signs must be performed to differentiate the different subtypes of TFO (grade C). No recommendation can be made on imaging prediction of the possibility of conservative BOT treatment.

New sonographic marker of borderline ovarian tumor: microcystic pattern of papillae and solid components

OBJECTIVE

To describe and evaluate the utility of a new sonographic microcystic pattern, which is typical of borderline ovarian tumor (BOT) papillary projections, solid component(s) and/or septa, as a new ultrasound marker that is capable of distinguishing BOT from other adnexal masses, and to present/obtain histologic confirmation.

METHODS

In this retrospective study, we identified women with a histologic diagnosis of BOT following surgical resection who had undergone preoperative transvaginal ultrasound (TVS) examination. All images were reviewed for presence or absence of thin-walled, fluid-filled cluster(s) of 1-3-mm cystic formations, associated with solid component(s), papillary projections and/or septa. From the same cases, histopathologic slides of each BOT were examined for presence of any of these microcystic features which had been identified on TVS. To confirm that the microcystic TVS pattern is unique to BOTs, we also selected randomly from our ultrasound and surgical database 20 cases of epithelial ovarian cancer and 20 cases of benign cystadenoma, for review by the same pathologists. To confirm the novelty of our findings, we searched PubMed for literature published in the English language between 2010 and 2018 to determine whether the association between microcystic tissue pattern and BOT has been described previously.

RESULTS

Included in the final analysis were 62 patients (67 ovaries) with preoperative TVS and surgically confirmed BOT on pathologic examination. The mean patient age at surgery was 39.8 years. The mean BOT size at TVS was 60.7 mm. Of the 67 BOTs, 47 (70.1%) were serous, 15 (22.4%) were mucinous and five (7.5%) were seromucinous. We observed on TVS a microcystic pattern in the papillary projections, solid component(s) and/or septa in 60 (89.6%) of the 67 BOTs, including 46 (97.9%) of the 47 serous BOTs, 11 (73.3%) of the 15 mucinous BOTs and three (60.0%) of the five seromucinous BOTs. On microscopic evaluation, 60 (89.6%) of the 67 samples had characteristic 1-3-mm fluid-filled cysts similar to those seen on TVS. In seven cases there was a discrepancy between sonographic and histologic observation of a microcystic pattern. The 20 cystadenomas were mostly unilocular and/or multilocular and largely avascular. None of them or the 20 epithelial ovarian malignancies displayed microcystic characteristics, either on TVS or at histology. On review of 23 published articles in the English medical literature, containing 163 sonographic images of BOT, we found that, while all images contained it, there was no description of the microcystic tissue pattern.

CONCLUSION

We report herein a novel sonographic marker of BOT, a 'microcystic pattern' of BOT papillary projections, solid component(s) and/or septa. This was seen in the majority of both serous and mucinous BOT cases. Importantly, based on comparison of sonographic images and histopathology of benign entities and malignancies, the microcystic appearance seems to be unique to BOTs. No similar description has been published previously. Utilization of this new marker should help to identify BOT correctly, discriminating it from ovarian cancer and benign ovarian pathology, and should ensure appropriate clinical and surgical management. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Imaging and Differential Diagnosis of Ovarian Cancer

Ovarian cancer is the seventh most common cancer affecting women. Despite advances in cancer control and healthcare in general, mortality from ovarian cancer remains unacceptably high due to diagnosis at an advanced stage of the disease. The 5-year survival rate is 47.4% because a majority of ovarian cancers are diagnosed when advanced. Only 14.9% of ovarian cancers are diagnosed when localized where the survival rate is 92.3%. Mortality rate reduction by screening has not been proven in women at an average risk for ovarian cancer. Ultrasound remains the primary modality for assessment of ovarian tumors. The need for standardizing terminology is critical for optimal assessment of the risk of malignancy in an ovarian tumor. The international ovarian tumor analysis group and more recently the American College of Radiology Ovarian - Adnexal Reporting and Data System Committee have published standardized lexicon for ovarian lesions and encourage ultrasound imagers to adopt this standardized terminology. The aim is to apply the lexicon for risk stratification to allow for consistent follow-up and management. Various methodologies have been tested for characterization of adnexal tumors and to assess risk of malignancy preoperatively. Risk assessment models have been studied against the gold standard of a pattern recognition approach and subjective assessment by an experienced imager. The morphologic patterns of ovarian tumors are detailed and features that are more discriminatory than others in suggesting an ovarian malignancy are described. The imaging pathologic correlation for different tumor types is presented. A brief summary of the ovarian cancer pathologic types and staging of cancer is presented. Finally, the current role of transvaginal sonography as a screening modality for ovarian cancer is discussed. Recently published data show encouraging results, that a multimodal approach of screening for ovarian cancer using transvaginal sonography in women with an elevated CA-125 may prove beneficial and cost effective.

Low-grade epithelial ovarian cancer: what a radiologist should know

Ovarian cancer accounts for the death of over 100,000 females every year and is the most lethal gynecological malignancy. Low-grade serous ovarian carcinoma (LGSOC) and high-grade serous ovarian carcinoma (HGSOC) have been found to represent two distinct entities based on their molecular differences, clinical course, and response to chemotherapy. Currently, all ovarian cancers are staged according to the revised staging system of the International Federation of Gynecology and Obstetrics (FIGO). Imaging plays an integral role in the diagnosis, staging, and follow-up of ovarian cancers. This review will be based on the two-tier grading system of epithelial ovarian cancers, with the main emphasis on serous ovarian cancer, and the role of imaging to characterize low-grade vs high-grade tumors and monitor disease recurrence during follow-up.

Role of CA125/CEA ratio and ultrasound parameters in identifying metastases to the ovaries in patients with multilocular and multilocular-solid ovarian masses

OBJECTIVES

To investigate ultrasound features and the best cut-off value of the cancer antigen 125/carcinoembryonic antigen (CA125/CEA) ratio to discriminate ovarian metastases from benign and primary malignant ovarian neoplasms in two selected groups of morphological ovarian masses, namely multilocular masses with five or more locules and multilocular-solid masses.

METHODS

Patients with multilocular (five or more locules) or multilocular-solid ovarian masses, operated on within 3 months of ultrasound examination, and with tumor markers (CEA and CA125) available at diagnosis, were identified retrospectively from three ultrasound centers. The masses were described using the International Ovarian Tumor Analysis (IOTA) terminology. Ultrasound and clinical characteristics were compared between those with an ovarian neoplasm (including benign and primary malignant neoplasms) and those with an ovarian metastasis. Receiver-operating characteristics curve (ROC) analysis was used to evaluate the ability of CA125, CEA and CA125/CEA to differentiate between ovarian neoplasms and ovarian metastases, and their predictive performance was assessed.

RESULTS

In total, 350 (88.4%) patients with an ovarian neoplasm (including 99 benign, 43 borderline and 197 primary epithelial ovarian carcinomas, seven malignant rare tumors and four other types of invasive ovarian tumor) and 46 (11.6%) patients with an ovarian metastasis were analyzed. On ultrasound examination, ovarian neoplasms were smaller than ovarian metastases (median largest diameter, 97 (range, 20-387) mm vs 146 (range, 43-259) mm, respectively; P < 0.0001) and presented with a lower number of cysts with > 10 locules (18.9% vs 54.3%; P < 0.0001). ROC curve analysis showed that the best cut-off value of CEA for distinguishing between ovarian neoplasms and ovarian metastases was 2.33 ng/mL. The predictive performance of this CEA cut-off value was: area under the curve (AUC), 0.791 (95% CI, 0.711-0.870); accuracy, 73.7%; sensitivity, 73.1%; specificity, 78.3%; positive predictive value (PPV), 96.2%; and negative predictive value (NPV), 27.7%. The best cut-off value of CA125/CEA for distinguishing between ovarian neoplasms and ovarian metastases was 11.92. The predictive performance of this CA125/CEA cut-off value was: AUC, 0.758 (95% CI, 0.683-0.833); accuracy, 79.8%; sensitivity, 82.3%; specificity, 60.9%; PPV, 94.1%; and NPV, 31.1%.

CONCLUSIONS

CA125/CEA ratio and CEA alone did not show any significant difference in their ability to distinguish between ovarian neoplasms (including benign and malignant) and ovarian metastases in masses with multilocular and those with multilocular-solid morphology. Therefore, in this morphological subgroup of ovarian masses, CEA alone is sufficient to differentiate between ovarian neoplasms and ovarian metastases. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Imaging in gynecological disease (14): clinical and ultrasound characteristics of ovarian clear cell carcinoma

OBJECTIVE

To describe the clinical and ultrasound characteristics of ovarian pure clear cell carcinoma.

METHODS

This was a retrospective study involving data from 11 ultrasound centers. From the International Ovarian Tumor Analysis (IOTA) database, 105 patients who had undergone preoperative ultrasound examination by an experienced ultrasound examiner between 1999 and 2016 were identified with a histologically confirmed pure clear cell carcinoma of the ovary. An additional 47 patients diagnosed with pure clear cell carcinoma between 1999 and 2016 and with available complete preoperative ultrasound reports were identified retrospectively from the databases of the departments of gynecological oncology in the participating centers. The ultrasound images of all tumors were described using IOTA terminology. Clinical and ultrasound characteristics were analyzed for the whole group, and separately, for patients with and those without histologically confirmed endometriosis, and for patients with evidence of tumor developing from endometriosis.

RESULTS

Median age of the 152 patients was 53.5 (range, 28-92) years and 92/152 (60.5%) tumors were FIGO Stage I. Most tumors (128/152, 84.2%) were unilateral. On ultrasound examination, all tumors contained solid components and 36/152 (23.7%) were completely solid masses. The median largest diameter of the lesion was 117 (range, 25-310) mm. Papillary projections were present in 58/152 (38.2%) masses and, in most of these (51/56, 91.1%), vascularized papillary projections were seen. Information regarding the presence, site and type of pelvic endometriosis at histology was available for 130/152 patients. Endometriosis was noted in 54 (41.5%) of these. In 24/130 (18.6%) patients, the tumor was judged to have developed from endometriosis. Patients with, compared to those without, evidence of tumor developing from endometriosis were younger (median 47.5 vs 55.0 years, respectively), and ground-glass echogenicity of cyst fluid was more common in pure clear cell cancers developing from endometriosis (10/20 vs 13/79 (50.0% vs 16.5%), respectively).

CONCLUSIONS

Ovarian pure clear cell carcinoma is usually diagnosed at an early stage and typically appears as a large unilateral mass with solid components. Patients with clear cell carcinoma developing from endometriosis are younger than other patients with clear cell carcinoma, and clear cell cancers developing from endometriosis more often manifest ground-glass echogenicity of cyst fluid. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Imaging in gynecological disease (13): clinical and ultrasound characteristics of endometrioid ovarian cancer

OBJECTIVE

To describe the clinical and ultrasound characteristics of ovarian pure endometrioid carcinomas.

METHODS

This was a retrospective multicenter study of patients with a histological diagnosis of pure endometrioid carcinoma. We identified 161 patients from the International Ovarian Tumor Analysis (IOTA) database who had undergone preoperative ultrasound examination by an experienced ultrasound examiner between 1999 and 2016, and another 78 patients from the databases of the departments of gynecological oncology in the participating centers. All tumors were described using IOTA terminology. In addition, one author reviewed all available ultrasound images and described them using pattern recognition.

RESULTS

Median age of the 239 patients was 55 years (range, 19-88 years). On ultrasound examination, two (0.8%) endometrioid carcinomas were described as unilocular cysts, three (1.3%) as multilocular cysts, 37 (15.5%) as unilocular-solid cysts, 115 (48.1%) as multilocular-solid cysts and 82 (34.3%) as solid masses. Median largest tumor diameter was 102.5 mm (range, 20-300 mm) and median largest diameter of the largest solid component was 63 mm (range, 9-300 mm). Papillary projections were present in 70 (29.3%) masses. Most cancers (188 (78.7%)) were unilateral. In 49 (20.5%) cases, the cancer was judged by the pathologist to develop from endometriosis. These cancers, compared with those without evidence of tumor developing from endometriosis, more often manifested papillary projections on ultrasound (46.9% (23/49) vs 24.7% (47/190)), were less often bilateral (8.2% (4/49) vs 24.7% (47/190)) and less often associated with ascites (6.1% (3/49) vs 28.4% (54/190)) and fluid in the pouch of Douglas (24.5% (12/49) vs 48.9% (93/190)). Retrospective analysis of available ultrasound images using pattern recognition revealed that many tumors without evidence of tumor developing from endometriosis (36.3% (41/113)) had a large central solid component entrapped within locules, giving the tumor a cockade-like appearance.

CONCLUSIONS

Endometrioid cancers are usually large, unilateral, multilocular-solid or solid tumors. The ultrasound characteristics of endometrioid carcinomas developing from endometriosis differ from those without evidence of tumor developing from endometriosis, the former being more often unilateral cysts with papillary projections and no ascites. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.