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

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.

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.

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.

To establish a diagnostic model combining contrast-enhanced ultrasound (CEUS), human epididymis protein 4 (HE4), and Ovarian-Adnexal Reporting and Data Systems (O-RADS) US v2022, verify its diagnostic efficacy, and compare it with subjective evaluation.

From January 2018 to August 2021 (the test group) and from September 2021 to September 2022 (the validation group), the data of patients classified as O-RADS US v2022 categories 2 to 5 who underwent adnexal ultrasound examinations were prospectively and continuously collected. In the test group, univariate and multivariate analyses were used to explore the relationship between age, body mass index (BMI), maximum diameter of the lesion, menopausal status, HE4, cancer antigen 125 (CA125), and the characteristics of CEUS and malignant lesions. Selecting independent influencing factors to construct diagnostic model, which was validated in the external validation group and compared with subjective evaluation.

The test group included 563 patients (mean age, 48.7 ± 13.2), and the validation group included 246 patients (mean age, 47.6 ± 12.9). Univariate and multivariate analyses showed that enhancement time, enhancement intensity, dynamic changes, and HE4 were independent influencing factors for predicting adnexal malignant tumors. In the validation group, the sensitivities and specificities of O-RADS US v2022, O-RADS US v2022 + CEUS, O-RADS US v2022 + CEUS + HE4, and subjective assessment were 88.89% and 70.69%, 94.44% and 79.31%, 91.67% and 92.53%, and 93.09% and 89.66% respectively. In addition, the combined diagnostic performance of O-RADS US v2022, CEUS and HE4 (AUC = 0.980) was higher than that of O-RADS US v2022 alone (AUC = 0.876, P < 0.001) and the combination of O-RADS US v2022 + CEUS (AUC = 0.908, P < 0.001), and was comparable to the subjective evaluation (AUC = 0.963, P = 0.192).

The combined diagnostic model of O-RADS US v2022, CEUS and HE4 can improve the specificity of adnexal ultrasound diagnosis without sacrificing sensitivity, and it has high reliability.

To evaluate the diagnostic accuracy and reliability of the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound v2019 in classifying adnexal masses (AMs) and compare the old and updated systems (v2022).

This prospective study enrolled 977 consecutive women with suspected AMs from three institutions between January 2022 and December 2023. Ultrasound examinations were performed by three experienced radiologists who categorized AMs according to O-RADS ultrasound v2019. The same radiologists retrospectively reviewed the stored ultrasound images and provided the O-RADS ultrasound v2022 classification. Histopathology was used as the reference standard to calculate the diagnostic accuracy of the O-RADS versions in predicting malignant AMs. Inter-observer agreement (IOA) of the O-RADS scoring results was evaluated using the Fleiss kappa (κ) test.

The final analysis included 803 women with 855 AMs (219 (25.6%) malignant and 636 (74.4%) benign). Both O-RADS versions demonstrated good diagnostic accuracy, with area under the curve (AUC) values ranging from 0.906 to 0.923 (v2019) and 0.919 to 0.936 (v2022). The updated v2022 showed a slightly higher accuracy (82.5-86.7% vs. 80.7-85.3%), sensitivity (93.6-95.0% vs. 92.2-94.1%), and specificity (78.1-84.1% vs. 76.1-82.9%) compared to v2019. The IOA for the overall O-RADS classification was perfect for both versions (κ = 0.96-0.97).

The O-RADS ultrasound classification system demonstrated good diagnostic accuracy and reliability in predicting malignant AMs, with the updated v2022 showing modest improvements.

Question Accurate classification of adnexal masses is essential for management. Can updated O-RADS ultrasound v2022 improve diagnostic accuracy and reliability compared to v2019 in predicting malignancies? Findings O-RADS ultrasound v2022 demonstrated slightly higher diagnostic accuracy for identifying malignant adnexal masses compared to v2019, reflecting modest improvements in risk stratification and clinical decision-making. Clinical relevance The updated O-RADS ultrasound v2022 provides improved risk stratification for adnexal masses, enhancing diagnostic confidence, supporting more precise clinical decision-making, and improving patient outcomes through timely intervention or tailored management strategies in ovarian cancer care.

Female adnexal malignancies, while relatively uncommon, exhibit high mortality rates due to often-late diagnosis. The serine/threonine kinase 11 (STK11) is a tumor suppressor gene, and its inactivation or mutation often leads to an autosomal dominant genetic disorder known as Peutz-Jeghers syndrome (PJS), which is associated with ovarian and cervical cancers. STK11-associated adnexal tumors mostly originate from the ovary, with a low incidence rate but high metastasis rates worldwide. In addition to surgery and chemotherapy, it is necessary to optimize relevant screening policy and targeted therapy. STK11-associated adnexal tumors are difficult to diagnose by histopathology. Although genetic testing involves higher costs, it can serve as a primary preventive measure for high-risk populations with STK11-associated tumors. A more intensive screening program (MISP) is needed for individuals with significant clinical symptoms and a family history of PJS. These tumors may be adequately treated with fertility-sparing surgery in young women with lower malignant potential tumors. Prophylactic adnexectomy, chemotherapy, and immunotherapy may offer potential clinical benefits but also pose significant challenges. Therefore, surgery should be undertaken with careful and comprehensive consideration of the patient's age, reproductive history, risk of malignancy, genetic mutation lineages, post-operative complications, and other conditions. Further research is essential to develop better screening, diagnostic, and treatment strategies.

Ovarian cancer (OC) is the most pathogenic gynecological malignant tumor in the world. Due to the difficulty of early diagnosis, most of patients developed chemo-resistance and recurrence during/after chemotherapy.

CCK8 and flow cytometry were utilized to assess drug sensitivity and apoptosis in parental and drug resistant cell lines. CYLD knockdown or overexpressed cells were employed to investigate its regulatory involvement in DDP resistance. Clinical tumor samples have been utilized to investigate the clinical relevance of CYLD. The drug synergistic effects were investigated through drug combination methods and a nude mice model with ABCB1 inhibitor or HER3 inhibitor.

In this study, we found that CYLD levels were significantly reduced in DDP-resistant cancer tissues and cells compared to the normal tissues and cells. CYLD knockdown in DDP-sensitive cells was sufficient to converse the cells to become DDP resistant by reducing cell apoptosis through increasing Bcl-XL and inhibiting Bax, and by increasing drug efflux via upregulating ABCB1 expression. HER3 expression levels were substantially higher in resistant cancer tissues and cells, and HER3 was the upstream facilitator of suppressing CYLD expression via STAT3 signaling. Furthermore, overexpression of CYLD in resistant cells increased sensitivity to platinum-based chemotherapy both in vitro and in vivo. ABCB1 was a key downstream target of CYLD for regulating tumor growth and therapeutic resistance both in vitro and in vivo, CYLD knockdown promoted the translocation of p65 to nucleus which increased ABCB1 expression through transcriptional activation. High expression levels of HER3 rendered CYLD suppression, consequently, mediated DDP resistance by blocking cell apoptosis pathways and promoting the drug efflux in ovarian cancer.

Our findings identify novel HER3/CYLD/ABCB1 axis that regulate tumor growth and DDP resistance, which may be used as potential novel therapeutic target(s) to overcome ovarian cancer DDP resistance.

Accurately predicting metastatic cancer to the adnexa, stage I and advanced ovarian cancer before surgery is crucial. The ADNEX model, based on ultrasound, is currently the only prediction model that can differentiate between these types. This study aims to analyze MRI features and diagnostic value in malignant ovarian tumors mis-subclassified by the ADNEX model, considering their diverse histopathologic types.

From January 2018 to September 2022, 164 patients with pathologically confirmed ovarian malignancies were selected from those who were examined by ultrasound. The clinical and MRI characteristics of 51 patients mis-subclassified by the ADNEX model were compared with histopathological types.

A total of 30 were confirmed with primary ovarian cancer (5 with HGSOC, 14 with CCC, 2 with EC, 4 with MC, 2 with GCT, 1 with YST, 1 with immature teratoma, and 1 with dysgerminoma). There were 21 patients who had metastatic ovarian tumors (10 with colorectal cancer, 4 with gastric cancer, 2 with uterine cervical cancer, 3 with endometrial cancer, 1 with breast cancer, and 1 with LAMN). The only significant difference between the two groups was in CEA. The mean diameters of the primary and metastatic ovarian tumors were 10.29 cm (range: 3.61 cm-26.02 cm) and 8.58 cm (range: 3.10 cm-20.30 cm), respectively. A total of 42 masses were lobulated (82.35%, 42/51), and 26 masses were solid-cystic (26/51, 50.98%). There was a significant difference between CCC and other tumors, with mean ADC values of 1.01 × 10-3 mm2/s (range: 0.68-1.28×10-3 mm2/s) and 0.74×10-3 mm2/s (range: 0.48-0.99×10-3 mm2/s), respectively (P=0.000). A total of 50 masses presented isointense-T1, hyperintense-T2, and hyperintense-DWI signal on MRI (50/51,98.04%). There were 33 masses that showed intensive enhancement (33/51,64.71%). There were 17 masses who had necrosis (17/51, 33.33%), with the majority being HGSOC and ovarian metastases from colorectal and gastric cancers (12/17, 70.59%). There were 19 masses that presented hemorrhage (19/51,37.25%), with the majority being CCC (10/19, 52.63%). A total of 46 masses were diagnosed correctly by MRI (46/51,90.20%). There were 35 and 15 masses that were rated as O-RADS score 5 and score 4, respectively. One mass was rated as score 3.

DWI signal, ADC value, degree of enhancement, and characteristic components within the mass on MRI can provide supplementary information for malignant ovarian tumors mis-subclassified by the ADNEX model.

Ovarian cancer (OC) remains the most lethal gynecologic malignancy with limited effective treatment options. Oncolytic viruses (OVs) have emerged as a promising therapeutic approach for cancer treatment, capable of selectively infecting and lysing cancer cells while stimulating anti-tumor immune responses. Preclinical studies have demonstrated significant tumor regression and prolonged survival in OC models using various OVs, such as herpes simplex. Early-phase clinical trials have shown a favorable safety profile, though the impact on patient survival has been modest. Current research focuses on combining OVs with other treatments like immune checkpoint inhibitors to enhance their efficacy. We provide a comprehensive overview of the current understanding and future directions for utilizing OVs in the management of OC.

This study is to analyze and compare the diagnostic efficacy of the ADNEX model and O-RADS in Northeast China for benign and malignant ovarian-adnexal tumors. From July 2020 to February 2022, ultrasound images of 312 ovarian-adnexal masses included in the study were analyzed retrospectively, and the properties of these masses were identified using the ADNEX model and O-RADS. The diagnostic efficiency of the ADNEX model and O-RADS was analyzed using a ROC curve, and the capacities of the two models in differentiating benign and malignant ovarian masses at the optimum cutoff value were compared, as well as the consistency of their diagnosis results was evaluated. The study included 312 ovarian-adnexal masses, including 145 malignant masses and 167 benign masses from 287 patients with an average age of (46.8 ± 11.3) years. The AUC of the ADNEX model was 0.974, and the optimum cutoff value was the risk value > 24.2%, with the corresponding sensitivity and specificity being 97.93 and 86.83, respectively. The AUC of the O-RADS was 0.956, and the optimum cutoff value was > O-RADS 3, with the corresponding sensitivity and specificity being 97.24 and 85.03, respectively. The AUCs of the two models were 0.924 and 0.911 at the optimum cutoff values, with no statistical differences between them (P = 0.284). Consistency analysis: the kappa values of the two models for the determination and pathological results of masses were 0.840 and 0.815, respectively, and that for the diagnostic outcomes was 0.910. Both the ADNEX model and O-RADS had good diagnostic performance in people from Northeast China. Their diagnostic capabilities were similar, and diagnostic results were highly consistent at the optimum cutoff values.

Evolving evidence suggests both protein consumption and particulate matter less than 2.5 micrometers (PM2.5) might be related to ovarian cancer (OC) mortality. However, no epidemiological studies have explored their potential interaction.

The objective of this study was to explore the association of dietary protein, PM2.5, and their interaction with the survival of OC patients.

A prospective cohort study was carried out, which encompassed 658 newly diagnosed OC patients (18-79 years) residing in China. Dietary protein intakes were collected through a food frequency questionnaire examination, including total protein and protein from diverse sources. Average residential PM2.5 concentrations were evaluated using satellite-derived models. We calculated the hazard ratio (HR) and its 95 % confidence interval (CI) by adjusting for multiple variables using Cox proportional risk models. By assessing the relative excess risk due to interaction (RERI) arising from the interplay between PM2.5 exposure and dietary protein intake, we explored the additive interaction between the two. Multiplicative interaction was assessed through a cross-product interaction term.

During a median follow-up of 37.60 months, 123 deaths were documented. As for all-cause mortality, the multivariate-adjusted HRs (95 % CIs) in the highest vs. the lowest tertile were 0.57 (0.35-0.93), 0.60 (0.36-0.99), and 0.58 (0.37-0.90) for intakes of fish, egg, as well as fruit/vegetable protein, respectively (all P for trend < 0.05). A positive association between PM2.5 exposure and all-cause mortality was observed (HR=1.52; 95 % CI: 1.13-2.05, per interquartile range increment). Notably, dietary fish, egg, and fruit/vegetable protein modified these associations, as patients with lower intakes had significantly higher PM2.5-related mortality in the cohort (all P for interaction < 0.05).

This study provides evidence linking the potential interactions between dietary fish, egg, and fruit/vegetable protein intake and PM2.5 exposure on all-cause mortality of OC patients. Our study demonstrates the importance of adherence to a certain protein diet in reducing PM2.5-related mortality risk for OC patients.

To apply the International Ovarian Tumor Analysis (IOTA) predictive models, the logistic regression model 2 (LR2) and the IOTA Assessment of Different NEoplasias in the adneXa (ADNEX), in patients with ovarian masses and to compare their performance in preoperative discrimination between benign and malignant adnexal lesions.

This was a retrospective diagnostic accuracy study with prospectively collected data, performed between January 2019 and December 2022, in a single tertiary gynecologic oncology center in Greece. The study included women with an adnexal lesion which underwent surgery within 6 months after of using the LR2 and ADNEX protocol to assess the risk of malignancy. Correlation of the ultrasound findings with the postoperative histopathological analysis was performed. Receiver-operating characteristics (ROC) curve analysis was used to determine the diagnostic accuracy of the models to classify tumors; sensitivity and specificity were determined for each model and their performance was compared.

Of the136 participants, 117 (86%) had benign ovarian masses and 19 (14%) had malignant tumors. The area under the ROC curve (AUC) of the LR2 model was 0.84 (95% CI 0.74-0.93), which was significantly higher than the AUC for ADNEX model: 0.78 (95% CI 0.67-0.89). At a cut off > 10%, the LR2 model had the highest sensitivity 89.5% (95% CI 66.9-98.7) and specificity 85.1% (95% CI 76.9-91.2) compared to ADNEX model [sensitivity 84.2% (95% CI 60.4-96.6) and specificity 71.8% (95% CI 62.7-79.7)].

IOTA LR2 had the highest accuracy in differentiating between benign and malignant ovarian masses. IOTA LR2 and ADNEX models were both useful tools in discriminating between benign and malignant ovarian masses.

Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors continues to pose significant challenges due to variability in image performance, resulting in a lack of objectivity that relies heavily on the expertise of medical professionals. This challenge can be addressed through the emergence and advancement of radiomics, which enables high-throughput extraction of valuable information from conventional medical images. Furthermore, radiomics can integrate with genomics, a novel approach termed radiogenomics, which allows for a more comprehensive, precise, and personalized assessment of tumor biological features. In this review, we present an extensive overview of the application of radiomics and radiogenomics in diagnosing and predicting ovarian tumors. The findings indicate that artificial intelligence methods based on imaging can accurately differentiate between benign and malignant ovarian tumors, as well as classify their subtypes. Moreover, these methods are effective in forecasting survival rates, treatment outcomes, metastasis risk, and recurrence for patients with OC. It is anticipated that these advancements will function as decision-support tools for managing OC while contributing to the advancement of precision medicine.

Epithelial ovarian cancer is aggressive and causes high mortality among women worldwide. Members of the plakin family are essential to maintain cytoskeletal integrity and key cellular processes. In this study we characterised the expression of plakins, particularly plectin (PLEC), periplakin (PPL), envoplakin (EVPL), and EMT-related proteins by immunohistochemistry in n = 48 patients' samples to evaluate a potential correlation of plakin expression with EMT as EOC progresses. These tissue plakin and EMT expression analyses were further evaluated by in vitro cell line expression and correlated with the expression of these molecules using publicly available datasets such as Cancer Genome Atlas (TCGA) and Clinical Proteome Tumour Analysis Consortium (CPTAC) datasets. We demonstrate that the expression of PPL and PLEC plakins is decreased in high-grade compared to low-grade EOCs with mixed EMT marker protein expression. This is supported by the correlation of high PPL and PLEC expression with an epithelial rather than mesenchymal phenotype. Our data suggest a partial loss of plakin expression as EOC tumours progress. This may impact the connections of plakins with membrane-bound receptors, which impede the downstream signalling required for the initiation of EMT as the tumours progress.

Due to improved understanding of ovarian cancer pathogenesis, we have an unprecedented chance to decrease the burden of disease by maximizing opportunities for prevention. Innovations in surgical options for prevention stem from the discovery that many cases directly or indirectly arise from the fallopian tube. Surgical prevention with salpingectomy alone decreases risk by ≥50%. Effective hormonal and nonhormonal chemopreventive agents are also available. Risk stratification is key to ensuring that options for prevention are appropriately matched to individual risk profile. This evidence-based review provides a critical appraisal of the translational health research endeavors supporting ovarian cancer prevention in clinical practice.

Ovarian cancer remains a leading cause of death among women, largely due to its asymptomatic early stages and high mortality when diagnosed late. Early detection significantly improves survival rates, and the Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) is currently the most commonly used method, but has limitations in specificity and accuracy. While O-RADS US has standardized reporting, its sensitivity can lead to the misdiagnosis of benign masses as malignant, resulting in overtreatment. This study aimed to construct a nomogram model based on the O-RADS US and clinical and laboratory indicators to predict the malignancy risk of adnexal cystic-solid masses.

This retrospective study collected data from patients with adnexal cystic-solid masses who underwent ultrasonography and were pathologically confirmed between January 2021 and December 2023 at the First Affiliated Hospital of Shenzhen University. They were categorized into benign and malignant groups according to pathological findings. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select the most relevant predictors of ovarian cancer. A nomogram model was constructed, and its diagnostic performance was calculated. We bootstrapped the data 500 times to perform internal verification, drew a calibration curve to verify the prediction ability, and performed a decision curve analysis to assess clinical usefulness.

A total of 399 patients with adnexal cystic-solid masses were included in this study: 327 in the benign group and 72 in the malignant group. Five predictors associated with the risk of malignancy of adnexal cystic-solid masses were selected using LASSO regression: O-RADS, acoustic shadowing, postmenopausal status, CA125, and HE4. The area under the curve, sensitivity, specificity, accuracy, positive and negative predictive values of the nomogram were 0.909, 83.3%, 82.9%, 83.0%, 51.7%, and 95.8%, respectively. The calibration curve of the nomogram showed good consistency between the predicted and actual probabilities, and the decision curve showed good clinical usefulness.

The nomogram model based on O-RADS US and clinical and laboratory indicators can be used to predict the risk of malignancy in adnexal cystic-solid masses, with high predictive performance, good calibration, and clinical usefulness.

The study aimed to compare the diagnostic efficacy of the machine learning models with expert subjective assessment (SA) in assessing the malignancy risk of ovarian tumors using transvaginal ultrasound (TVUS).

The retrospective single-center diagnostic study included 1555 consecutive patients from January 2019 to May 2021. Using this dataset, Residual Network(ResNet), Densely Connected Convolutional Network(DenseNet), Vision Transformer(ViT), and Swin Transformer models were established and evaluated separately or combined with Cancer antigen 125 (CA 125). The diagnostic performance was then compared with SA.

Of the 1555 patients, 76.9% were benign, while 23.1% were malignant (including borderline). When differentiating the malignant from ovarian tumors, the SA had an AUC of 0.97 (95% CI, 0.93-0.99), sensitivity of 87.2%, and specificity of 98.4%. Except for Vision Transformer, other machine learning models had diagnostic performance comparable to that of the expert. The DenseNet model had an AUC of 0.91 (95% CI, 0.86-0.95), sensitivity of 84.6%, and specificity of 95.1%. The ResNet50 model had an AUC of 0.91 (0.85-0.95). The Swin Transformer model had an AUC of 0.92 (0.87-0.96), sensitivity of 87.2%, and specificity of 94.3%. There was a statistically significant difference between the Vision Transformer and SA, and between the Vision Transformer and Swin Transformer models (AUC: 0.87 vs. 0.97, P = 0.01; AUC: 0.87 vs. 0.92, P = 0.04). Adding CA125 did not improve the diagnostic performance of the models in distinguishing benign and malignant ovarian tumors.

The deep learning model of TVUS can be used in ovarian cancer evaluation, and its diagnostic performance is comparable to that of expert assessment.

CA125 is recommended by many countries as the primary screening test for ovarian cancer. But there are patients with ovarian cancer having normal CA125. We hope to identify the types of EOC with normal CA125 levels better by building a refined model based on the ultrasound radiomics, thus providing precise medical treatment for patients.

We included 58 patients with EOC with normal CA125 from 2 centres, who were confirmed by preoperative ultrasound and pathology. We extracted 1130 radiomics features based on the tumour's region of interest from the most typical ultrasound image of each patient. We selected radiomics and clinical features by LASSO and logistic regression to construct Rad-score and clinical models, respectively. Receiver operating characteristic curves judged their test efficacy. On the basis of the combined model, we developed a nomogram.

Area under the curves (AUCs) of 0.93 and 0.83 were achieved in both the training and test groups for the combined model. There were similar AUCs between the Rad-score and clinical models of 0.82 and 0.80, respectively. By analysing the calibration curves, it was determined that the nomogram matched actual observations in the training cohort.

Ultrasound radiomics can differentiate type I and type II EOC with normal CA125 levels.

This study is the first to focus on EOC cases with normal level of CA125. The subset of patients constituting 20% of the disease population may require more refined radiomics models.

To externally and prospectively validate the International Ovarian Tumor Analysis (IOTA) Simple Rules (SRs), Logistic Regression model 2 (LR2) and Assessment of Different NEoplasias in the adneXa (ADNEX) model in a Portuguese population, comparing these approaches with subjective assessment and the risk-of-malignancy index (RMI), as well as with each other. This study also aimed to retrospectively validate the IOTA two-step strategy, using modified benign simple descriptors (MBDs) followed by the ADNEX model in cases in which MBDs were not applicable.

This was a prospective multicenter diagnostic accuracy study conducted between January 2016 and December 2021 of consecutive patients with an ultrasound diagnosis of at least one adnexal tumor, who underwent surgery at one of three tertiary referral centers in Lisbon, Portugal. All ultrasound assessments were performed by Level-II or -III sonologists with IOTA certification. Patient clinical data and serum CA 125 levels were collected from hospital databases. Each adnexal mass was classified as benign or malignant using subjective assessment, RMI, IOTA SRs, LR2 and the ADNEX model (with and without CA 125). The reference standard was histopathological diagnosis. In the second phase, all adnexal tumors were classified retrospectively using the two-step strategy (MBDs + ADNEX). Sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios and overall accuracy were determined for all methods. Receiver-operating-characteristics curves were constructed and corresponding areas under the curve (AUC) were determined for RMI, LR2, the ADNEX model and the two-step strategy. The ADNEX model calibration plots were constructed using locally estimated scatterplot smoothing (LOESS).

Of the 571 patients included in the study, 428 had benign disease and 143 had malignant disease (prevalence of malignancy, 25.0%), of which 42 had borderline ovarian tumor, 93 had primary invasive adnexal cancer and eight had metastatic tumors in the adnexa. Subjective assessment had an overall sensitivity of 97.9% and a specificity of 83.6% for distinguishing between benign and malignant lesions. RMI showed high specificity (95.6%) but very low sensitivity (58.7%), with an AUC of 0.913. The IOTA SRs were applicable in 80.0% of patients, with a sensitivity of 94.8% and specificity of 98.6%. The IOTA LR2 had a sensitivity of 84.6%, specificity of 86.9% and an AUC of 0.939, at a malignancy risk cut-off of 10%. At the same cut-off, the sensitivity, specificity and AUC for the ADNEX model with vs without CA 125 were 95.8% vs 98.6%, 82.5% vs 79.7% and 0.962 vs 0.960, respectively. The ADNEX model gave heterogeneous results for distinguishing between benign masses and different subtypes of malignancy, with the highest AUC (0.991) for discriminating benign masses from primary invasive adnexal cancer Stages II-IV, and the lowest AUC (0.696) for discriminating primary invasive adnexal cancer Stage I from metastatic lesion in the adnexa. The calibration plot suggested underestimation of the risk by the ADNEX model compared with the observed proportion of malignancy. The MBDs were applicable in 26.3% (150/571) of cases, of which none was malignant. The two-step strategy using the ADNEX model in the second step only, with and without CA 125, had AUCs of 0.964 and 0.961, respectively, which was similar to applying the ADNEX model in all patients.

The IOTA methods showed good-to-excellent performance in the Portuguese population, outperforming RMI. The ADNEX model was superior to other methods in terms of accuracy, but interpretation of its ability to distinguish between malignant subtypes was limited by sample size and large differences in the prevalence of tumor subtypes. The IOTA MBDs are reliable in identifying benign disease. The two-step strategy comprising application of MBDs followed by the ADNEX model if MBDs are not applicable, is suitable for daily clinical practice, circumventing the need to calculate the risk of malignancy in all patients. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Ovarian cancer (OC), particularly high-grade serous carcinoma (HGSC), is a leading cause of gynecological cancer mortality due to late diagnosis and chemoresistance. While studies on OC cell lines have shown that overexpression of the ATP7A membrane transporter correlates with resistance to platinum-based drugs (PtBMs) and cross-resistance to copper (Cu), clinical evidence is lacking. The functionality of ceruloplasmin (CP), the main Cu-transporting protein in the blood, is dependent on, among other things, ATP7A activity. This study investigated ATP7A expression and CP levels as potential biomarkers for predicting responses to PtBMs. We included 28 HGSC patients who underwent neoadjuvant chemotherapy (NACT). ATP7A expression in ovarian and peritoneal tissues before NACT and in peritoneal and omental tissues after NACT was analyzed via qPCR, and CP levels in ascites and plasma were measured via ELISA before and after NACT. In total, 54% of patients exhibited ATP7A expression in pretreatment tissue (ovary and/or peritoneum), while 43% of patients exhibited ATP7A expression in tissue after treatment (peritoneum and/or omentum). A significant association was found between higher ATP7A expression in the peritoneum before NACT and an unfavorable CA-125 elimination rate constant k (KELIM) score. Patients with omental ATP7A expression had significantly higher plasma mean CP levels before NACT. Plasma CP levels decreased significantly after NACT, and higher CP levels after NACT were associated with a shorter platinum-free interval (PFI). These findings suggest that the ATP7A transporter and CP have the potential to serve as predictive markers of chemoresistance, but further research is needed to validate their clinical utility.

Research reveals that 1% of neoplasms in females under 17 years of age are ovarian neoplasms and though usually benign, malignant tumors may occur in the pediatric age group. This review considers various current concepts of these tumors including the epidemiology, risk factors, clinical presentations, diagnosis, differential diagnosis, and treatment options including the need to provide fertility-sparing surgery as well as their potential impacts on the psychological well-being of children and adolescents. We gathered data from the published articles ranging from studies, meta-analyses, retrospective studies, and reviews. We focused on the articles published in English between January 1, 2000, and August 31, 2023. Only a few articles published prior to 2000 were included for historical perspective.

This abstract describes a case of the growth of a serous borderline tumour recurrence and cyst to papillary projection ratio with associated ultrasound images. The aetiology, presentation and management of such cases are explored and compared to the literature.

Although cancer-associated fibroblast (CAF) heterogeneity is well-established, the impact of chemotherapy on CAF populations remains poorly understood. Here we address this question in high-grade serous ovarian cancer (HGSOC), in which we previously identified 4 CAF populations. While the global content in stroma increases in HGSOC after chemotherapy, the proportion of FAP+ CAF (also called CAF-S1) decreases. Still, maintenance of high residual CAF-S1 content after chemotherapy is associated with reduced CD8+ T lymphocyte density and poor patient prognosis, emphasizing the importance of CAF-S1 reduction upon treatment. Single cell analysis, spatial transcriptomics and immunohistochemistry reveal that the content in the ECM-producing ANTXR1+ CAF-S1 cluster (ECM-myCAF) is the most affected by chemotherapy. Moreover, functional assays demonstrate that ECM-myCAF isolated from HGSOC reduce CD8+ T-cell cytotoxicity through a Yes Associated Protein 1 (YAP1)-dependent mechanism. Thus, efficient inhibition after treatment of YAP1-signaling pathway in the ECM-myCAF cluster could enhance CD8+ T-cell cytotoxicity. Altogether, these data pave the way for therapy targeting YAP1 in ECM-myCAF in HGSOC.

Undertreatment of ovarian cancer is common among older women. We aimed to evaluate the treatment modalities offered to older patients and their impact on overall survival (OS).

The study identified 5,055 patients with high-grade serous ovarian cancer and 3584 patients with advanced stage (IIIC + IV) disease from the Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2010, to December 31, 2017. We performed comparisons of OS and ovarian cancer-specific survival (OCSS) across age groups using a Cox proportional hazards model.

Very elderly patients (≥ 75 years old) received treatment with significantly less surgical complexity, such as no lymphadenectomy (59.7% vs. 48.6%; p < 0.001) and a lower rate of optimal debulking surgery (44.0% vs. 52.7%; p < 0.001), as well as lower rates of chemotherapy (78.2% vs. 89.4%; P<0.001) and standard treatment (70.6% vs. 85%; p < 0.001). High proportions of both very elderly and elderly patients received neoadjuvant chemotherapy (NACT), with no significant difference (38.7% vs. 36.2%; P = 0.212). Patients aged ≥ 75 years had significantly worse OS and OCSS.

With increasing age, the survival rate of women with ovarian cancer decreases significantly. Noticeably fewer ovarian cancer patients aged over 75 years receive standard treatments, and more very elderly patients are treated with NACT.

Ovarian cancer (OC) is the female genital malignancy with the highest lethality. Patients present a poor prognosis mainly due to the late clinical presentation allied with the common acquisition of chemoresistance and a high rate of tumour recurrence. Effective screening, accurate diagnosis, and personalised multidisciplinary treatments are crucial for improving patients' survival and quality of life. This comprehensive narrative review aims to describe the current knowledge on the aetiology, prevention, diagnosis, and treatment of OC, highlighting the latest significant advancements and future directions. Traditionally, OC treatment involves the combination of cytoreductive surgery and platinum-based chemotherapy. Although more therapeutical approaches have been developed, the lack of established predictive biomarkers to guide disease management has led to only marginal improvements in progression-free survival (PFS) while patients face an increasing level of toxicity. Fortunately, because of a better overall understanding of ovarian tumourigenesis and advancements in the disease's (epi)genetic and molecular profiling, a paradigm shift has emerged with the identification of new disease biomarkers and the proposal of targeted therapeutic approaches to postpone disease recurrence and decrease side effects, while increasing patients' survival. Despite this progress, several challenges in disease management, including disease heterogeneity and drug resistance, still need to be overcome.

Approximately 3/4 of ovarian cancers are diagnosed in advanced stages, with the high-grade epithelial ovarian carcinoma (EOC) accounting for 90% of the cases. EOC present high genomic instability and somatic loss-of-function variants in genes associated with homologous recombination mutational repair pathway (HR), such as BRCA1 and BRCA2, and in TP53. The identification of germline variants in HR genes in EOC is relevant for treatment of platinum resistant tumors and relapsed tumors with therapies based in synthetic lethality such as PARP inhibitors. Patients with somatic variants in HR genes may also benefit from these therapies. In this work was analyzed the frequency of somatic variants in BRCA1, BRCA2, and TP53 in an EOC cohort of Brazilian patients, estimating the proportion of variants in tumoral tissue and their association with progression-free survival and overall survival.

The study was conducted with paired blood/tumor samples from 56 patients. Germline and tumoral sequences of BRCA1, BRCA2, and TP53 were obtained by massive parallel sequencing. The HaplotypeCaller method was used for calling germline variants, and somatic variants were called with Mutect2.

A total of 26 germline variants were found, and seven patients presented germline pathogenic or likely pathogenic variants in BRCA1 or BRCA2. The analysis of tumoral tissue identified 52 somatic variants in 41 patients, being 43 somatic variants affecting or likely affecting protein functionality. Survival analyses showed that tumor staging was associated with overall survival (OS), while the presence of somatic mutation in TP53 was not associated with OS or progression-free survival.

Frequency of pathogenic or likely pathogenic germline variants in BRCA1 and BRCA2 (12.5%) was lower in comparison with other studies. TP53 was the most altered gene in tumors, with 62.5% presenting likely non-functional or non-functional somatic variants, while eight 14.2% presented likely non-functional or non-functional somatic variants in BRCA1 or BRCA2.

Cancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived exosomes (IOCEs) subgroups in ovarian cancer (OC) and establish a prognostic model for OC patients based on immune-related IOCEs.

The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq data, as well as clinical and prognostic information. Consensus clustering analysis was performed to identify two IOCEs-associated subgroups. Kaplan-Meier analysis was used to compare the overall survival (OS) between IOCEs-high and IOCEs-low subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the mechanisms and biological effects of differentially expressed genes (DEGs) between the two subtypes. Besides, an IOCE-related prognostic model of OC was constructed by Lasso regression analysis, and the signature was validated using GSE140082 as the validation set.

In total, we obtained 21 differentially expressed IOCEs in OC, and identified two IOCE-associated subgroups by consensus clustering. IOCE-low subgroup showed a favorable prognosis while IOCE-high subgroup had a higher level of immune cell infiltration and immune response. GSEA showed that pathways in cancer and immune response were mainly enriched in IOCE-high subgroup. Thus, IOCE-high subgroup may benefit more in immunotherapy treatment. In addition, we constructed a risk model based on nine IOCE-associated genes (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6).

We developed a novel stratification system for OV based on IOCE signature, which could be used to estimate the prognosis as well as immunotherapy for OC patient.

Among the primary causes of mortality in today's world is cancer. Many drugs are employed to give lengthy and severe chemotherapy and radiation therapy, like nitrosoureas (Cisplatin, Oxaliplatin), Antimetabolites (5-fluorouracil, Methotrexate), Topoisomerase inhibitors (Etoposide), Mitotic inhibitors (Doxorubicin); such treatment is associated with significant adverse effects. Antitumor antibiotics have side effects similar to chemotherapy and radiotherapy. Selenium (Se) is an essential trace element for humans and animals, and additional Se supplementation is required, particularly for individuals deficient in Se. Due to its unique features and high bioactivities, selenium nanoparticles (SeNPs), which act as a supplement to counter Se deficiency, have recently gained worldwide attention. This study presented a safer and more economical way of preparing stable SeNPs. The researcher has assessed the antiproliferative efficiency of SeNPs-based paclitaxel delivery systems against tumor cells in vitro with relevant mechanistic visualization. SeNPs stabilized by Pluronic F-127 were synthesized and studied. The significant properties and biological activities of PTX-loaded SeNPs on cancer cells from the lungs, breasts, cervical, and colons. In one study, SeNPs were formulated using chitosan (CTS) polymer and then incorporated into CTS/citrate gel, resulting in a SeNPs-loaded chitosan/citrate complex; in another study, CTS was used in the synthesis of SeNPs and then situated into CTS/citrate gel, resulting in Se loaded nanoparticles. These formulations were found to be more successful in cancer treatment.

Ovarian clear cell carcinoma (OCCC) is a subtype of epithelial ovarian cancer (EOC) that is associated with higher interleukin-6 (IL-6) levels, and suppression of the Janus kinase 2/Signal transducer and activator of transription 3 (JAK2/STAT3) pathway may contribute to the suppression of this cancer. This study aims to compare the anti-cancer effect of pterostilbene (PSB) and 2'- and 3'-hydroxypterostilbene (2HPSB and 3HPSB, respectively) on the JAK2/STAT3 pathway.

In vitro experiments with the OCCC cell line TOV21G and a xenograft nude mouse model are used to achieve the study aims. The results showed that 3HPSB has the greatest anti-proliferative and pro-apoptotic effects of the three compounds studied. Activation of the JAK2/STAT3 pathway and the nuclear translocation of STAT3 are effectively inhibited by 3HPSB and PSB. Both 3HPSB and PSB can effectively suppress tumor growth, which is mediated by the inhibition of JAK2/STAT3 phosphorylation.

This is the first study to compare the efficacy of PSB, 3HPSB, and the newly identified compound 2HPSB regarding ovarian cancer. Moreover, targeting JAK2/STAT3 is shown to be a potentially effective strategy for OCCC treatment. This study is expected to provide new insights into the potential of the abovementioned phytochemicals for development as adjuvants for cancer treatment in the future.

Ovarian cancer (OC) is a prevalent neoplastic condition affecting women. Extracellular vesicles (EVs), nano-sized membrane vesicles, are secreted by various cells in both physiological and pathological states. The profound interplay between EVs and the tumor microenvironment (TME) in ovarian cancer is crucial. In this review, we explores the pivotal role of EVs in facilitating intercellular communication between cancer cells and the TME, emphasizing the potential of EVs as promising diagnostic markers and innovative therapeutic targets for ovarian cancer. The comprehensive analysis outlines the specific mechanisms by which EVs engage in communication with the constituents of the TME, including the modulation of tumor growth through EVs carrying matrix metalloproteinases (MMPs) and EV-mediated inhibition of angiogenesis, among other factors. Additionally, the we discuss the potential clinical applications of EVs that target the TME in ovarian cancer, encompassing the establishment of novel treatment strategies and the identification of novel biomarkers for early detection and prognosis. Finally, this review identifies novel strategies for therapeutic interventions, such as utilizing EVs as carriers for drug delivery and targeting specific EV-mediated signaling pathways. In summary, this manuscript offers valuable insights into the role of EVs in ovarian cancer and highlights the significance of comprehending intercellular communication in the realm of cancer biology.

To develop deep learning (DL) prediction models using transvaginal ultrasound (TVS), transabdominal ultrasound (TAS), and color Doppler flow imaging (CDFI) of TVS (CDFI_TVS) to automatically predict benign or malignant ovarian tumors.

This retrospective study included women with ovarian tumors who underwent ultrasound between August 2018 and October 2022. Histopathological analysis was used as a reference standard. The dataset was preprocessed by clipping, flipping, and rotating images to generate a larger, more complicated, and diverse dataset to improve accuracy and generalizability. The dataset was then divided into training (80%) and test (20%) sets. The weights of the models, modified from the residual network (ResNet) with the TVS, TAS, and CDFI_TVS images (hereafter, referred to as DLTVS , DLTAS , and DLCDFI_TVS , respectively) were developed. The area under the receiver operating characteristic curve (AUC) analysis in the test set was used to compare the predictive value of DL for malignancy.

A total of 2340 images from 1350 women with adnexal masses were included. DLTVS had an AUC of 0.95 (95% CI: 0.93-0.97) for classifying malignant and benign ovarian tumors, comparable with that of DLTAS (AUC, 0.95; 95% CI: 0.91-0.98; p = 0.96) and DLCDFI_TVS (AUC, 0.88; 95% CI: 0.84-0.93; p = 0.02). Decision curve analysis indicated that DLTVS performed better than DLTAS and DLCDFI_TVS .

We developed DL models based on TVS, TAS, and CDFI_TVS on ultrasound images to predict benign and malignant ovarian tumors with high diagnostic performance. The DLTVS model had the best prediction compared with the DLTAS and DLCDFI_TVS models.

To assess the consistency of Ovarian-Adnexal Reporting and Data System (O-RADS) lexicon interpretation between senior and junior sonologists and to investigate its impact on O-RADS classification and diagnostic performance.

We prospectively studied 620 patients with adnexal lesions, all of whom underwent transvaginal or transrectal ultrasound performed by a senior sonologist (R1) who selected the O-RADS lexicon description and O-RADS category for the lesion after the examination. Meanwhile, the junior sonologist (R2) analyzed the images retained by R1 and divided the lesion in the same way. Pathological findings were used as a reference standard. kappa (к) statistics were used to assess the interobserver agreement.

Of the 620 adnexal lesions, 532 were benign and 88 were malignant. When using the O-RADS lexicon, R1 and R2 had almost perfect agreement regarding lesion category, external contour of solid lesions, presence of papillary inside cystic lesions, and fluid echogenicity (к: 0.81-1.00). Substantial agreement in solid components, acoustic shadow, vascularity and O-RADS categories (к: 0.61-0.80). Consistency in classifying classic benign lesions in the O-RADS category was only moderate (к = 0.535). No significant difference in diagnostic performance between them using O-RADS (P = 0.1211).

There was good agreement between senior and junior sonologists in the interpretation of the O-RADS lexicon and in the classification of O-RADS, except for a moderate agreement in the interpretation and classification of classic benign lesions. Differences in O-RADS category delineation between sonologists had no significant effect on the diagnostic performance of O-RADS.

Serous epithelial ovarian cancer, classified as either high-grade (90%) or low-grade (10%), varies in molecular, histological, and clinicopathological presentation. Low-grade serous ovarian cancer (LGSOC) is a rare histologic subtype that lacks disease-specific evidence-based treatment regimens. However, LGSOC is relatively chemo-resistant and has a poor response to traditional treatments. Alternative treatments, including biologic therapies such as bevacizumab, have shown some activity in LGSOC. Thus, the objective of this systematic review is to determine the effect and safety of bevacizumab in the treatment of LGSOC. Following PRISMA guidelines, Medline ALL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase all from the OvidSP platform, ClinicalTrials.gov, International Clinical Trials Registry Platform, International Standard Randomised Controlled Trial Number Registry were searched from inception to February 2022. Articles describing bevacizumab use in patients with LGSOC were included. Article screening, data extraction, and critical appraisal of included studies were completed by two independent reviewers. The effect of bevacizumab on the overall response rate, progression-free survival, overall survival, and adverse effects were summarized. The literature search identified 3064 articles, 6 of which were included in this study. A total of 153 patients were analyzed; the majority had stage IIIC cancer (56.2%). The overall median response rate reported in the studies was 47.5%. Overall, bevacizumab is a promising treatment for LGSOC, with response rates higher than traditional treatment modalities such as conventional chemotherapy, and is often overlooked as a treatment tool. A prospective clinical trial evaluating the use of bevacizumab in LGSOC is necessary to provide greater evidence and support these findings.

Ovarian cancers are a heterogeneous group of malignant tumors that differ with respect to pathogenesis, morphology, molecular features, and behavior. Pathologists and clinicians need to be aware of the advances in diagnosis and the changes which occur after chemotherapy to offer the optimal treatment to each patient. The present work aims to study the morphologic and immunohistochemical (IHC) profile of primary ovarian cancers with an assessment of post-chemotherapy changes. A total of 51 cases were included in the study from June 2017 to June 2019 (prospective and retrospective). The demographic and clinical details of the patients were collected. The gross and microscopic features of the tumors were studied, and the post-chemotherapy changes were evaluated. A chi-square test was used to determine the association of tumor morphology, the chemotherapy response score (CRS), and stage of the tumor with survival (PFS and OS). The mean patient age was 47.5 years, and high-grade serous carcinoma (66.6%) (HGSC) was the most common subtype followed by mucinous carcinoma and endometrioid carcinoma. Immunohistochemical analysis with WT1 and p53 helped in the diagnosis of HGSC. The CRS was 1 and 2 in most of the cases. The follow-up for patients of HGSC was available for a period of 1-27 months with a mean survival for primary resection of 24 months and for post-NACT resection was 17 months. This difference was not statistically significant (p = 0.38). High-grade serous carcinoma was the most common ovarian cancer in our series, and immunohistochemistry played an important role in the diagnosis. We could not demonstrate any survival benefit of preoperative chemotherapy in our series.

To describe the clinical and sonographic features of ovarian benign Brenner tumor (BBT) and malignant Brenner tumor (MBT), and to compare performance of four diagnostic models in differentiating them.

Fifteen patients with BBTs and nine patients with MBTs were retrospectively identified in our institution from January 2003 and December 2021. One ultrasound examiner categorized each mass according to ovarian-adnexal reporting and data system (O-RADS), international ovarian tumor analysis (IOTA) Simple Rules Risk (SR-Risk) assessment and assessment of different neoplasias in the adnexa (ADNEX) models with/without CA125. Receiver operating characteristic curves were generated to compare diagnostic performance.

Patients with MBT had higher CA125 serum level (62.5% vs. 6.7%, P = 0.009) and larger maximum diameter of lesion (89 mm vs. 43 mm, P = 0.009) than did those with BBT. BBT tended to have higher prevalence of calcifications (100% vs. 55.6%, P = 0.012) and acoustic shadowing (93.3% vs. 33.3%, P = 0.004), and lower color scores manifesting none or minimal flow (100.0% vs. 22.2%, P < 0.001). Areas under curves of O-RADS, IOTA SR-Risk and ADNEX models with/without CA125 were 0.896, 0.913, 0.892 and 0.896, respectively. There were no significant differences between them.

BBTs are often small solid tumors with sparse color Doppler signals, which contain calcifications with posterior acoustic shadowing. The most common pattern of MBT is a large multilocular-solid or solid mass with irregular tumor borders, and most were moderately or richly vascularized at color Doppler. These four models have excellent performance in distinguishing them.

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.

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).

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.

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.

Patients with ovarian cancer who undergo multivisceral surgery usually require intensive care monitoring postoperatively. In view of the ever-fewer numbers of high-care/intensive care beds and the introduction of fast-track treatment concepts, it is increasingly being suggested that these patients should be cared for postoperatively in 24-h Post Anesthesia Care Units (PACU24). No analyses have been carried out to date to investigate whether such a postoperative care concept might be associated with a potential increase in postoperative complications in this patient cohort.

A PACU24 unit was set up in our institution in 2015 and it has become the primary postoperative care pathway for patients with ovarian cancer who have undergone cytoreductive (debulking) surgery. A structured, retrospective analysis of data from patients treated before (control group) and after (PACU group) the introduction of this care concept was carried out, with a particular focus on postoperative complications and secondary admission to an intensive care unit where necessary.

The data of 42 patients were analyzed for the PACU group and 45 patients for the control group. According to the analysis, the preoperative and surgical data of both groups were comparable (age, ASA, BMI, FIGO stage, duration of surgery, blood loss). The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM score) as a measure for the risk of postoperative complications was higher in the PACU group (11.1% vs. 9.7%, p = 0.001). Patients in the PACU group underwent bowel resection with anastomosis significantly more often (76.3% vs. 33.3%, p < 0.001), although the extent of surgery was otherwise comparable. The total number, type and severity of postoperative complications and the duration of the overall stay in hospital did not differ between the two groups. None of the patients required secondary transfer from the PACU or normal ward to an intensive care unit (ICU).

Our data support the assumption that the care concept of transferring patients to a PACU24 represents a safe and cost-saving care pathway for the postoperative care of patients even after complex gynecological-oncological procedures.