A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer

The malignant transformation of endometriosis: Is there a left lateral predisposition of ovarian clear cell and endometrioid carcinomas?

INTRODUCTION

Endometriosis affects 10% of women of reproductive age. There is evidence for a left lateral predisposition of endometriotic lesions and a 1.9-fold greater risk of ovarian cancer in endometriosis. The aim of this study is to determine whether a left lateral predisposition of ovarian clear-cell carcinoma (CCC) and endometrioid carcinoma (EC) exists.

MATERIALS AND METHODS

A retrospective cohort study of all EC and CCC patients in Northern Ireland between March-2011 and June-2018. ANOVA was used to analyse preoperative prediction of stage, chi-squared (χ2) was used to compare left- and right-sided masses. Survival was estimated using Kaplan-Meier and log-rank test. A p-value <0.05 was considered significant.

RESULTS

158 patients were identified (95 EC, 55 CCC, 8 mixed). Mean age was 57.65 years with 69% presenting at stage 1. The mean CA125 was 559 U/mL (p = 0.850) and mean abdominal mass size was 14.12 cm (p = 0.732). The most common presenting symptom was an abdominal mass (37%). Despite 67% of patients having endometriosis on final pathology, only 8.9% had a known history pre-operatively. 51% of tumours were located on the left (p = 0.036). For unilateral tumours this was significant for EC (P = 0.002) but not for CCC (P = 0.555). The 1-, 3- and 5-year overall survival for all types/stages was 85%, 78% and 71% respectively.

CONCLUSION

While CCC and EC are associated with endometriosis, only EC exhibits a left lateral predisposition. There is no association between preoperative CA125 or abdominal mass size and stage of disease.

Utility of a Multi-Marker Panel with Ultrasound for Enhanced Classification of Adnexal Mass

Pre-surgical clinical assessment of an adnexal mass typically relies on transvaginal ultrasound for comprehensive morphological assessment, with further support provided by biomarker measurements and clinical evaluation. Whilst effective for masses that are obviously benign or malignant, a large proportion of masses remain sonographically indeterminate at surgical referral. As a consequence, post-surgical diagnoses of benign disease can outnumber malignancies up to 9-fold, while less than 50% of cancer cases receive a primary referral to a gynecological oncology specialist. We recently described a blood biomarker signature (multi-marker panel-MMP) that differentiated patients with benign from malignant ovarian disease with high accuracy. In this study, we have examined the use of the MMP, both individually and in combination with transvaginal ultrasound, as an alternative tool to CA-125 for enhanced decision making in the pre-surgical referral process.

Surgical treatment for pulmonary metastasis from ovarian cancer: a retrospective case series

BACKGROUND

Distant metastases of ovarian cancer are rarely detected alone. The effectiveness of surgical intervention for pulmonary metastases from ovarian cancer remains uncertain. This study aimed to investigate the clinicopathologic characteristics and outcomes of patients undergoing resection for pulmonary metastasis from ovarian cancer.

CASE PRESENTATION

The clinicopathologic characteristics and outcomes of radical surgery for pulmonary metastasis from ovarian cancer were investigated. Out of 537 patients who underwent pulmonary metastasis resection at two affiliated hospitals between 2010 and 2021, four (0.74%) patients who underwent radical surgery for pulmonary metastasis from ovarian cancer were included. The patients were aged 67, 47, 21, and 59 years; the intervals from primary surgery to detection of pulmonary metastasis from ovarian cancer were 94, 21, 36, and 50 months; and the overall survival times after pulmonary metastasectomy were 53, 50, 94, and 34 months, respectively. Three of the four patients experienced recurrence after pulmonary metastasectomy. Further, preoperative carbohydrate antigen (CA) 125 levels were normal in two surviving patients and elevated in the two deceased patients.

CONCLUSION

In this study, three of the four patients experienced recurrence after pulmonary metastasectomy, but all patients survived for > 30 months after surgery. Patients with ovarian cancer and elevated CA125 levels may not be optimal candidates for pulmonary metastasectomy. To establish appropriate criteria for pulmonary metastasectomy in patients with ovarian cancer, further research on a larger patient cohort is warranted.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass

OBJECTIVE

To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI).

METHODS

In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls.

RESULTS

Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups.

CONCLUSION

This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

Ovarian cancer risk among older patients with stable adnexal masses

BACKGROUND

Few studies have evaluated the risk of cancer among older patients with stable adnexal masses in community-based settings to determine the duration of observation time needed.

OBJECTIVE

This study aimed to assess the ovarian cancer risk among older patients with stable adnexal masses on ultrasound.

STUDY DESIGN

This was a retrospective cohort study of patients in a large community-based health system aged ≥50 years with an adnexal mass <10 cm on ultrasound between 2016 and 2020 who had at least 1 follow-up ultrasound performed ≥6 weeks after initial ultrasound. Masses were considered stable on follow-up examination if they did not exhibit an increase of >1 cm in the greatest dimension or a change in standardized reported ultrasound characteristics. Ovarian cancer risk was determined at increasing time intervals of stability after initial ultrasound.

RESULTS

Among 4061 patients with stable masses, the average age was 61 years (range, 50-99), with an initial mass size of 3.8 cm (range, 0.2-9.9). With a median follow-up of 3.7 years, 11 cancers were detected, with an absolute risk of 0.27%. Ovarian cancer risk declined with longer duration of stability, from 0.73 (95% confidence interval, 0.30-1.17) per 1000 person-years at 6 to 12 weeks, 0.63 (95% confidence interval, 0.19-1.07) at 13 to 24 weeks, 0.44 (95% confidence interval, 0.01-0.87) at 25 to 52 weeks, and 0.00 (95% confidence interval, 0.00-0.00) at >52 weeks. Expressed as number needed to reimage, ongoing ultrasound imaging would be needed for 369 patients whose masses show stability at 6 to 12 weeks, 410 patients at 13 to 24 weeks, 583 patients at 25 to 52 weeks, and >1142 patients with stable masses at 53 to 104 weeks to detect 1 case of ovarian cancer.

CONCLUSION

In a diverse community-based setting, among patients aged ≥50 years with an adnexal mass that was stable for at least 6 weeks after initial ultrasound, the risk of ovarian cancer was very low at 0.27%. Longer demonstrated duration of stability was associated with progressively lower risk, with no cancer cases observed after 52 weeks of stability. These findings suggest that the benefit of ultrasound monitoring of stable masses beyond 12 months is minimal and may be outweighed by potential risks of repeated imaging.

Clinical practice guidelines for molecular tumor marker, 2nd edition review part 2

In recent years, rapid advancement in gene/protein analysis technology has resulted in target molecule identification that may be useful in cancer treatment. Therefore, "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" was published in Japan in September 2021. These guidelines were established to align the clinical usefulness of external diagnostic products with the evaluation criteria of the Pharmaceuticals and Medical Devices Agency. The guidelines were scoped for each tumor, and a clinical questionnaire was developed based on a serious clinical problem. This guideline was based on a careful review of the evidence obtained through a literature search, and recommendations were identified following the recommended grades of the Medical Information Network Distribution Services (Minds). Therefore, this guideline can be a tool for cancer treatment in clinical practice. We have already reported the review portion of "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" as Part 1. Here, we present the English version of each part of the Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition.

Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer

One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.

Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool

Ovarian cancer is one of the most aggressive and significant malignant tumor forms in the female reproductive system. It is the leading cause of death among gynecological cancers owing to its metastasis. Since its preliminary disease symptoms are lacking, it is imperative to develop early diagnostic biomarkers to aid in treatment optimization and personalization. In this vein, microRNAs, which are short sequence non-coding molecules, displayed great potential as highly specific and sensitive biomarker. miRNAs have been extensively advocated and proven to serve an instrumental part in the clinical management of cancer, especially ovarian cancer, by promoting the cancer cell progression, invasion, delayed apoptosis, epithelial-mesenchymal transition, metastasis of cancer cells, chemosensitivity and resistance and disease therapy. Here, we cover our present comprehension of the most up-to-date microRNA-based approaches to detect ovarian cancer, as well as current diagnostic and treatment strategies, the role of microRNAs as oncogenes or tumor suppressor genes, and their significance in ovarian cancer progression, prognosis, and therapy.

Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery

BACKGROUND

Several diagnostic prediction models to help clinicians discriminate between benign and malignant adnexal masses are available. This study is a head-to-head comparison of the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with that of the Risk of Ovarian Malignancy Algorithm (ROMA).

METHODS

This is a retrospective study based on prospectively included consecutive women with an adnexal tumour scheduled for surgery at five oncology centres and one non-oncology centre in four countries between 2015 and 2019. The reference standard was histology. Model performance for ADNEX and ROMA was evaluated regarding discrimination, calibration, and clinical utility.

RESULTS

The primary analysis included 894 patients, of whom 434 (49%) had a malignant tumour. The area under the receiver operating characteristic curve (AUC) was 0.92 (95% CI 0.88-0.95) for ADNEX with CA125, 0.90 (0.84-0.94) for ADNEX without CA125, and 0.85 (0.80-0.89) for ROMA. ROMA, and to a lesser extent ADNEX, underestimated the risk of malignancy. Clinical utility was highest for ADNEX. ROMA had no clinical utility at decision thresholds <27%.

CONCLUSIONS

ADNEX had better ability to discriminate between benign and malignant adnexal tumours and higher clinical utility than ROMA.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov NCT01698632 and NCT02847832.

Comparison of Simple Ultrasound Rules by International Ovarian Tumor Analysis (IOTA) with RMI-1 and RMI-4 (Risk of Malignancy Index) in Preoperative Differentiation of Benign and Malignant Adnexal Masses

Background

IOTA proposed Simple Ultrasound Rules in 2009 for preoperative diagnosis of ovarian masses based on ultrasound only. It is an accurate, simple and inexpensive method. RMI, however, requires CA125 level. While RMI-4 is the latest, RMI-1 is still the most widely used method. The present study was done to compare IOTA Rules with RMI-1 and RMI-4.

Purpose

To differentiate benign and malignant adnexal masses preoperatively using IOTA simple rules and compare its accuracy with RMI-1 and RMI-4.

Methods

A prospective observational study was performed from 1st November 2019 to 31st March 2021 in the Department of Obstetrics and Gynaecology, ABVIMS and Dr. RML Hospital, New Delhi. This study was conducted on 70 patients with adnexal masses who underwent pre-operative evaluation using IOTA Simple Rules, RMI-1 and RMI-4. Histopathology was used to compare the results.

Results

Out of 70 patients, 59 (84.3%) cases were benign and 11 (15.7%) were malignant. The IOTA Rules were applicable to 60 cases (85.7%), and the results were inconclusive in 10 cases (14.3%). Where applicable, the sensitivity and specificity of the IOTA Rules (88.9% and 94.1%, respectively) were significantly higher than RMI-1 (45.5% and 93.2%, respectively) and RMI-4 (45.5% and 89.8%, respectively). When inconclusive results were included as malignant, the sensitivity of the IOTA Rules increased (88.9% vs 90.9%); however, the specificity decreased (94.1% vs 81.4%).

Conclusion

IOTA Simple Rules were more accurate at diagnosing benign from malignant adnexal masses than RMI-1 and RMI-4. However, the rules were not applicable to 14% of the cases.

Investigating harms of testing for ovarian cancer - psychological outcomes and cancer conversion rates in women with symptoms of ovarian cancer: A cohort study embedded in the multicentre ROCkeTS prospective diagnostic study

OBJECTIVE

To investigate psychological correlates in women referred with suspected ovarian cancer via the fast-track pathway, explore how anxiety and distress levels change at 12 months post-testing, and report cancer conversion rates by age and referral pathway.

DESIGN

Single-arm prospective cohort study.

SETTING

Multicentre. Secondary care including outpatient clinics and emergency admissions.

POPULATION

A cohort of 2596 newly presenting symptomatic women with a raised CA125 level, abnormal imaging or both.

METHODS

Women completed anxiety and distress questionnaires at recruitment and at 12 months for those who had not undergone surgery or a biopsy within 3 months of recruitment.

MAIN OUTCOME MEASURES

Anxiety and distress levels measured using a six-item short form of the State-Trait Anxiety Inventory (STAI-6) and the Impact of Event Scale - Revised (IES-r) questionnaire. Ovarian cancer (OC) conversion rates by age, menopausal status and referral pathway.

RESULTS

Overall, 1355/2596 (52.1%) and 1781/2596 (68.6%) experienced moderate-to-severe distress and anxiety, respectively, at recruitment. Younger age and emergency presentations had higher distress levels. The clinical category for anxiety and distress remained unchanged/worsened in 76% of respondents at 12 months, despite a non-cancer diagnosis. The OC rates by age were 1.6% (95% CI 0.5%-5.9%) for age <40 years and 10.9% (95% CI 8.7%-13.6%) for age ≥40 years. In women referred through fast-track pathways, 3.3% (95% CI 1.9%-5.7%) of pre- and 18.5% (95% CI 16.1%-21.0%) of postmenopausal women were diagnosed with OC.

CONCLUSIONS

Women undergoing diagnostic testing display severe anxiety and distress. Younger women are especially vulnerable and should be targeted for support. Women under the age of 40 years have low conversion rates and we advocate reducing testing in this group to reduce the harms of testing.

Exploration of Preliminary Objective Triage by Menopause Score and CA 125 Result Prior to Accelerating Fast-Track Booking for Suspected Ovarian Cancer-A Role for the Pathway Navigator?

The 28-days-to-diagnosis pathway is the current expected standard of care for women with symptoms of ovarian cancer in the UK. However, the anticipated conversion rate of symptoms to cancer is only 3%, and use of the pathway is increasing. A rapid triage at the moment of receipt of the referral might allow resources to be allocated more appropriately. In secondary care, multidisciplinary teams (MDTs) use the risk of malignancy index (RMI) score, (multiply menopausal status pre = 1 or post = 3 × ultrasound score = 0 - 3 × the CA 125 level), using a score of >200, to triage urgency and management in possible ovarian cancer cases. The most powerful determinant of the RMI score variables is CA 125 level, an objective number. Could a simple modification of the RMI score retain a high sensitivity for cancer whilst improving specificity and, consequently, decrease the morbidity of false-positive classification? To test this hypothesis, a retrospective evaluation of an ovarian two-week-wait telephone clinic of one consultant gynaecological oncologist was undertaken. Enquiry re menopause status was scored as one for pre- and three for postmenopausal or uncertain. CA 125 levels of >67 u/mL for premenopausal and >23 u/mL for postmenopausal women were used to precipitate urgent cross-sectional imaging requests and MDT opinions. These CA 125 cut thresholds were calculated using an assumption that the RMI imaging score, regardless of whether the result was available, could be three. We contemplate that women who did not exceed a provisional RMI score of >200 might be informed they are extremely unlikely to have cancer, removed from the malignancy tracker and appropriate follow-up arranged. One hundred and forty consecutive cases were analysed; 43% were deemed premenopausal and 57% postmenopausal. Twenty of the women had cancer, eighteen (90%) of whom had an RMI > 200. One hundred and twenty were benign, and only twenty-three (19%) classified as urgent cases in need of accelerated referral to imaging. In contrast, CA 125 > 35 u/mL, whilst retaining the sensitivity of 90%, misclassified 36 (30%) of the benign cases. It is possible that a telephone triage via a questionnaire determining menopausal status and the CA 125 result could offer a sensitivity for cancer of 90% and urgent expert review of under 20% of benign cases. This rapid initial telephone assessment could be presented by a trained pathway navigator, physician associate or nurse specialist. Substantial savings in NHS cancer services resources, anxieties all around and reduced patient morbidity may occur as a result.

Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4

Ovarian cancer (OC) is the most lethal gynaecologic malignancy, attributed to its insidious growth, non-specific symptoms and late presentation. Unfortunately, current screening modalities are inadequate at detecting OC and many lack the appropriate specificity and sensitivity that is desired from a screening test. Nearly 70% of cases are diagnosed at stage III or IV with poor 5-year overall survival. Therefore, the development of a sensitive and specific biomarker for early diagnosis and screening for OC is of utmost importance. Currently, diagnosis is guided by CA125, the patient's menopausal status and imaging features on ultrasound scan. However, emerging evidence suggests that a combination of CA125 and HE4 (another serum biomarker) and patient characteristics in a multivariate index assay may provide a higher specificity and sensitivity than either CA125 and HE4 alone in the early detection of OC. Other attempts at combining various serum biomarkers into one multivariate index assay such as OVA1, ROMA and Overa have all shown promise. However, significant barriers exist before these biomarkers can be implemented in clinical practice. This article aims to provide an up-to-date review of potential biomarkers for screening and early diagnosis of OC which may have the potential to transform its diagnostic landscape.

Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound

Ultrasound-based models exist to support the classification of adnexal masses but are subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine learning (ML) model capable of automating the classification of adnexal masses. In this retrospective study, transvaginal ultrasound scan images with linked diagnoses (ultrasound subjective assessment or histology) were extracted and segmented from Imperial College Healthcare, UK (ICH development dataset; n = 577 masses; 1444 images) and Morgagni-Pierantoni Hospital, Italy (MPH external dataset; n = 184 masses; 476 images). A segmentation and classification model was developed using convolutional neural networks and traditional radiomics features. Dice surface coefficient (DICE) was used to measure segmentation performance and area under the ROC curve (AUC), F1-score and recall for classification performance. The ICH and MPH datasets had a median age of 45 (IQR 35-60) and 48 (IQR 38-57) years old and consisted of 23.1% and 31.5% malignant cases, respectively. The best segmentation model achieved a DICE score of 0.85 ± 0.01, 0.88 ± 0.01 and 0.85 ± 0.01 in the ICH training, ICH validation and MPH test sets. The best classification model achieved a recall of 1.00 and F1-score of 0.88 (AUC:0.93), 0.94 (AUC:0.89) and 0.83 (AUC:0.90) in the ICH training, ICH validation and MPH test sets, respectively. We have developed an end-to-end radiomics-based model capable of adnexal mass segmentation and classification, with a comparable predictive performance (AUC 0.90) to the published performance of expert subjective assessment (gold standard), and current risk models. Further prospective evaluation of the classification performance of this ML model against existing methods is required.

Paradigm Shift: A Comprehensive Review of Ovarian Cancer Management in an Era of Advancements

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.

Artificial Intelligence in Ultrasound Diagnoses of Ovarian Cancer: A Systematic Review and Meta-Analysis

Ovarian cancer is the sixth most common malignancy, with a 35% survival rate across all stages at 10 years. Ultrasound is widely used for ovarian tumour diagnosis, and accurate pre-operative diagnosis is essential for appropriate patient management. Artificial intelligence is an emerging field within gynaecology and has been shown to aid in the ultrasound diagnosis of ovarian cancers. For this study, Embase and MEDLINE databases were searched, and all original clinical studies that used artificial intelligence in ultrasound examinations for the diagnosis of ovarian malignancies were screened. Studies using histopathological findings as the standard were included. The diagnostic performance of each study was analysed, and all the diagnostic performances were pooled and assessed. The initial search identified 3726 papers, of which 63 were suitable for abstract screening. Fourteen studies that used artificial intelligence in ultrasound diagnoses of ovarian malignancies and had histopathological findings as a standard were included in the final analysis, each of which had different sample sizes and used different methods; these studies examined a combined total of 15,358 ultrasound images. The overall sensitivity was 81% (95% CI, 0.80-0.82), and specificity was 92% (95% CI, 0.92-0.93), indicating that artificial intelligence demonstrates good performance in ultrasound diagnoses of ovarian cancer. Further prospective work is required to further validate AI for its use in clinical practice.

Application of medical imaging in ovarian cancer: a bibliometric analysis from 2000 to 2022

Background

Ovarian cancer (OC) is the most lethal tumor within the female reproductive system. Medical imaging plays a significant role in diagnosis and monitoring OC. This study aims to use bibliometric analysis to explore the current research hotspots and collaborative networks in the application of medical imaging in OC from 2000 to 2022.

Methods

A systematica search for medical imaging in OC was conducted on the Web of Science Core Collection on August 9, 2023. All reviews and articles published from January 2000 to December 2022 were downloaded, and an analysis of countries, institutions, journals, keywords, and collaborative networks was perfomed using CiteSpace and VOSviewer.

Results

A total of 5,958 publications were obtained, demonstrating a clear upward trend in annual publications over the study peroid. The USA led in productivity with 1,373 publications, and Harvard University emerged as the most prominent institution with 202 publications. Timmerman D was the most prolific contributor with 100 publications, and Gynecological Oncology led in the number of publications with 296. The top three keywords were "ovarian cancer" (1,256), "ultrasound" (725), and "diagnosis" (712). In addition, "pelvic masses" had the highest burst strength (25.5), followed by "magnetic resonance imaging (MRI)" (21.47). Recent emergent keywords such as "apoptosis", "nanoparticles", "features", "accuracy", and "human epididymal protein 4 (HE 4)" reflect research trends in this field and may become research hotspots in the future.

Conclusion

This study provides a comprehensive summary of the key contributions of OC imaging to field's development over the past 23 years. Presently, primary areas of OC imaging research include MRI, targeted therapy of OC, novel biomarker (HE 4), and artificial intelligence. These areas are expected to influence future research endeavors in this field.

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.

A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer

Ovarian cancer remains the most lethal of gynecological malignancies, with the 5-year survival below 50%. Currently there is no simple and effective pre-surgical diagnosis or triage for patients with malignancy, particularly those with early-stage or low-volume tumors. Recently we discovered that CXCL10 can be processed to an inactive form in ovarian cancers and that its measurement has diagnostic significance. In this study we evaluated the addition of processed CXCL10 to a biomarker panel for the discrimination of benign from malignant disease. Multiple biomarkers were measured in retrospectively collected plasma samples (n = 334) from patients diagnosed with benign or malignant disease, and a classifier model was developed using CA125, HE4, Il6 and CXCL10 (active and total). The model provided 95% sensitivity/95% specificity for discrimination of benign from malignant disease. Positive predictive performance exceeded that of "gold standard" scoring systems including CA125, RMI and ROMA% and was independent of menopausal status. In addition, 80% of stage I-II cancers in the cohort were correctly identified using the multi-marker scoring system. Our data suggest the multi-marker panel and associated scoring algorithm provides a useful measurement to assist in pre-surgical diagnosis and triage of patients with suspected ovarian cancer.

Current and Emerging Strategies for Tubo-Ovarian Cancer Diagnostics

Tubo-ovarian cancer is the most lethal gynaecological cancer. More than 75% of patients are diagnosed at an advanced stage, which is associated with poorer overall survival. Symptoms at presentation are vague and non-specific, contributing to late diagnosis. Multimodal risk models have improved the diagnostic accuracy of adnexal mass assessment based on patient risk factors, coupled with findings on imaging and serum-based biomarker tests. Newly developed ultrasonographic assessment algorithms have standardised documentation and enable stratification of care between local hospitals and cancer centres. So far, no screening test has proven to reduce ovarian cancer mortality in the general population. This review is an update on the evidence behind ovarian cancer diagnostic strategies.

Simple rules, O-RADS, ADNEX and SRR model: Single oncologic center validation of diagnostic predictive models alone and combined (two-step strategy) to estimate the risk of malignancy in adnexal masses and ovarian tumors

OBJECTIVE

To compare performance of Assessment of Different NEoplasias in the adneXa (ADNEX model), Ovarian-Adnexal Reporting and Data System (O-RADS), Simple Rules Risk (SRR) assessment and the two-step strategy based on the application of Simple Rules (SR) followed by SRR and SR followed by ADNEX in the pre-operative discrimination between benign and malignant adnexal masses (AMs).

METHODS

We conducted a retrospective study from January-2018 to December-2021 in which consecutive patients with at AMs were recruited. Accuracy metrics included sensitivity (SE) and specificity (SP) with their 95% confidence intervals (CI) were calculated for ADNEX, O-RADS and SRR. When SR was inconclusive a "two-step strategy" was adopted applying SR + ADNEX model and SR + SRR assessment.

RESULTS

A total of 514 women were included, 400 (77.8%) had a benign ovarian tumor and 114 (22.2%) had a malignant tumor. At a threshold malignancy risk of >10%, the SE and SP of ADNEX model, O-RADS and SRR were: 0.92 (95% CI, 0.86-0.96) and 0.88 (95% CI, 0.85-0.91); 0.93 (95% CI, 0.87-0.97) and 0.89 (95% CI, 0.96-0.92); 0.88 (95% CI, 0.80-0.93) and 0.84 (95% CI, 0.80-0.87), respectively. When we applied SR, 109 (21.2%) cases resulted inconclusive. The SE and SP of two-step strategy SR + SRR assessment and SR + ADNEX model were 0.88 (95% CI, 0.80-0.93) and 0.92 (95% CI, 0.89-0.94), SR + ADNEX model 0.90 (95% CI, 0.83-0.95) and 0.93 (95% CI, 0.90-0.96), respectively.

CONCLUSIONS

O-RADS presented the highest SE, similar to ADNEX model and SR + ADNEX model. However, the SR + ADNEX model presented the higher performance accuracy with the higher SP and PPV. This two-step strategy, SR and ADNEX model applicated to inconclusive SR, is convenient for clinical evaluation.

Evaluating the Frequency and Characteristics of Unexpected Ovarian Malignancy in Postmenopausal Women Who Have Undergone Laparoscopic Surgery for Adnexal Masses - A Review of Five Years

Aim The aim of this study was to estimate the frequent existence of unexpected ovarian malignant lesions after laparoscopic surgery for an apparent benign adnexal mass and assess its clinical and ultrasound characteristics in postmenopausal women. Methods We re-examined the hospital records of 96 cases of postmenopausal women who underwent laparoscopic surgery for benign adnexal mass over five years. The age of the patient, parity, ultrasound findings, tumor markers level, intraoperative findings, and histopathological report were collected. Pearson's Chi-squared test and Fisher's exact test were used for statistical analysis, and a p-value of <0.05 was accepted as statistically significant. Results Of a total of 96, benign adnexal mass was in 93 (96.83%), an unexpected ovarian malignancy was observed in two (2.08%) cases, and one (1.04%) had a borderline ovarian tumor. Tumor marker CA-125 was done for all those cases of adnexal mass in postmenopausal women, and not a single case was found to have above 35 IU/ml, defined as the cut-off value for CA-125. Statistically significant differences were observed between the benign and malignant groups in relation to symptoms (p<0.05), ultrasound score (p=0.001), and bilaterality (p=0.013) of the tumor mass. Conclusion In postmenopausal women, the critical concern for laparoscopic surgery of benign adnexal mass is unexpected malignancy. So it is essential to select patients carefully for laparoscopic surgery. If a benign-looking adnexal mass turned out to be malignant on the histopathological report, we should try to post the patient for subsequent staging laparotomy as soon as possible.

Adnexal Mass Imaging: Contemporary Guidelines for Clinical Practice

Several recent guidelines have been published to improve accuracy and consistency of adnexal mass imaging interpretation and to guide management. Guidance from the American College of Radiology (ACR) Appropriateness Criteria establishes preferred adnexal imaging modalities and follow-up. Moreover, the ACR Ovarian-Adnexal Reporting Data System establishes a comprehensive, unified set of evidence-based guidelines for classification of adnexal masses by both ultrasound and MR imaging, communicating risk of malignancy to further guide management.

Comparison of Human Epididymis Protein 4, Cancer Antigen 125, and Ultrasound Prediction Model in Differentiating Benign from Malignant Adnexal Masses

Background

This study aimed to compare the diagnostic performance of carcinogenic antigen (CA) 125, (HE)-4 (Human epididymis protein 4), and ultrasound (International Ovarian Tumor Analysis [IOTA]) Simple Rules individually and to derive a composite score in the differentiating ovarian cancer from benign ovarian mass.

Subjects and Methods

Consecutive patients (n = 100) with pelvic mass admitted during February 2018-August 2019 were included prospectively. Patients with either known case of epithelial ovarian cancer (EOC) or metastatic EOC were excluded. The primary outcome was to assess the sensitivity and specificity of CA-125, HE-4, and IOTA Simple Rules in predicting benign from malignant mass independently, while secondary outcome was derivation of a new model incorporating these variables using multivariate logistic regression analysis to predict benign from malignant lesions. Receiver operator curve (ROC) was drawn to redefine the best-performing cutoff values and difference between area under the ROC (AUROC) were compared by DeLong's method.

Results

Out of 100 cases of adnexal mass selected, the sensitivity and specificity of CA-125 were 73.8% and 77.6%, HE-4 were 90.5% and 87.9%, and IOTA Simple Rules were 92.9% and 81.0%. CA-125, HE-4, and IOTA Simple Rules were independently associated with the likelihood of malignancy/borderline (P < 0.001). The area under the curve for the "composite score" (AUC = 0.93) was the highest and was significantly better than that of CA-125 (AUC = 0.786) (P = 0.004 using DeLong's test) and comparable with HE-4 (AUROC = 0.90; P = 0.128 using DeLong's Test).

Conclusion

The sensitivity and specificity of HE-4 and IOTA Simple Rules for predicting malignant ovarian tumor was better than those of CA-125. The diagnostic performance of "composite score" was comparable to those of either HE-4 or IOTA Simple Rules and significantly better than CA-125.

Comparison of Four Risk of Malignancy Indices for Preoperative Evaluation of Ovarian Masses: A Prospective Observational Study

BACKGROUND

Ovarian cancer imposes a significant health burden worldwide. Although various tumor markers are available to diagnose ovarian cancer, low-resource countries like India require a humble marker or index. The Risk of Malignancy Index (RMI) has been found to be a simple yet promising tool that can be used for this purpose. In this study, we attempted to validate various RMIs with the help of menopausal status, ultrasonogram score, cancer antigen (CA) 125 value and compare all four RMIs, which would be useful to differentiate benign and malignant ovarian masses. This could be an essential tool, especially in low-resource settings.

METHOD

This prospective study was conducted at Kalinga Institute of Medical Sciences in Odisha, India, from September 2020 to September 2022 involving 191 patients with ovarian mass with histopathology, which was deemed the "gold standard" diagnostic tool. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RMI 1, 2, 3, and 4 were calculated and compared.  Results: Out of 191 patients, 32 (16%) had malignancy and 159 (83.2%) had benign pathology. It was apparent that RMI 4 was a better tool for the initial assessment of patients with ovarian masses with a sensitivity of 80.6%, specificity of 96.2%, PPV of 81%, NPV of 96% at a cutoff of 334, and an area under the curve value of 0.939.

CONCLUSION

RMI 4 followed by RMI 3 were relatively better indices than RMI 1 and RMI 2 for identifying benign and malignant ovarian masses. RMI 4 was a valuable and applicable method in diagnosing pelvic masses with a high risk of malignancy.

Advantages and Limitations of Ultrasound as a Screening Test for Ovarian Cancer

Ovarian cancer (OC) is the seventh most common malignancy diagnosed among women, the eighth leading cause of cancer mortality globally, and the most common cause of death among all gynecological cancers. Even though recent advances in technology have allowed for more accurate radiological and laboratory diagnostic tests, approximately 60% of OC cases are diagnosed at an advanced stage. Given the high mortality rate of advanced stages of OC, early diagnosis remains the main prognostic factor. Our aim is to focus on the sonographic challenges in ovarian cancer screening and to highlight the importance of sonographic evaluation, the crucial role of the operator΄s experience, possible limitations in visibility, emphasizing the importance and the necessity of quality assurance protocols that health workers have to follow and finally increasing the positive predictive value. We also analyzed how ultrasound can be combined with biomarkers (ex. CA-125) so as to increase the sensitivity of early-stage OC detection or, in addition to the gold standard examination, the CT (Computed tomography) scan in OC follow-up. Improvements in the performance and consistency of ultrasound screening could reduce the need for repeated examinations and, mainly, ensure diagnostic accuracy. Finally, we refer to new very promising techniques such as liquid biopsies. Future attempts in order to improve screening should focus on the identification of features that are unique to OC and that are present in early-stage tumors.

Diagnostic accuracy of the Copenhagen Index in ovarian malignancy: A meta-analysis

OBJECTIVE

To assess the diagnostic value of the Copenhagen index for ovarian malignancy.

METHODS

PubMed, Web of Science, the Cochrane Library, Embase, CBM, CNKI, and WanFang databases were searched throughout June 2021. Statistical analyses were performed using Stata 12, Meta-DiSc, and RevMan 5.3. The pooled sensitivity, specificity, and diagnostic odds ratio were calculated, the summary receiver operating characteristic curve was drawn, and the area under the curve was calculated.

RESULTS

Ten articles, including 11 studies with a total of 5266 patients, were included. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.82 [95% CI (0.80-0.83)], 0.88 [95% CI (0.87-0.89)], and 57.31 [95% CI (32.84-100.02)], respectively. The area under the summary receiver operating characteristics curve and the Q index were 0.9545 and 0.8966, respectively.

CONCLUSION

Our systematic review shows that the sensitivity and specificity of the Copenhagen index are high enough for it to be used in a clinical setting to provide accurate ovarian cancer diagnosis without considering menopausal status.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.

Psychological impact of simple scoring system for predicting early pregnancy outcome in pregnancy of uncertain viability: randomized controlled trial

OBJECTIVE

To investigate whether psychological wellbeing of women with an intrauterine pregnancy of uncertain viability can be modified during the waiting period to final diagnosis, by offering predictive information regarding the likely outcome of the pregnancy (chance of ongoing viability).

METHODS

This was a single-center two-arm randomized controlled trial conducted over 18 months at a teaching hospital in London, UK. Consecutive eligible women attending the early pregnancy assessment unit with an interim ultrasound finding of intrauterine pregnancy of uncertain viability were recruited. All women were offered a follow-up ultrasound scan after 14 days. Participants were randomized to receive a prediction score for ongoing viability at 14 days or routine care (control). Anxiety, depression and worry symptoms were assessed using validated self-report questionnaires (hospital anxiety and depression scale (HADS), Penn state worry questionnaire (PSWQ)) prior to randomization and at two further timepoints during the waiting period preceding final diagnosis. The change in psychological scores over the study period was analyzed. The secondary outcome was the perceived value of the risk prediction tool reported by participants.

RESULTS

A total of 278 women participated in this study. After adjusting for baseline scores, no difference in anxiety, depression or worry scores was demonstrated between control and intervention groups at either timepoint. Subgroup analysis, first of women with high initial anxiety (HADS > 11) or worry (PSWQ ≥ 45), and second of women with a more favorable predicted prognosis (≥ 75% chance of ongoing viability), demonstrated no difference between intervention and control groups. Despite this, 76/110 (69.1% (95% CI, 60.5-78.4%)) women who provided feedback in the intervention group found it to be helpful and 97/110 (88.2% (95% CI, 81.0-93.7%)) reported that they would use the tool again.

CONCLUSION

Current prediction tools may be useful for healthcare professionals to guide management and optimize utilization of early pregnancy resources. However, in this study, implementation of an accurate tool did not result in an objective measurable benefit to patients in terms of reduction in anxiety, depression and worry symptoms experienced during the waiting period to final outcome compared with women who did not receive a prediction score. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Ovarian Masses: The Value of Acoustic Shadowing on Ultrasound Examination

Adnexal lesions are a common finding in women and pose a clinical challenge since ovarian cancer is a highly lethal disease. However, most adnexal masses are benign, benefiting from a more conservative approach. In preoperative assessment, transvaginal ultrasound plays a key role in evaluating morphologic features that correlate with the risk of malignancy. The acoustic shadow is the loss of echo behind sound-absorbing components, such as calcifications or fibrous tissues, which are predominantly found in benign lesions. However, recognizing the acoustic shadow is a difficult skill to master, and its usefulness may be underappreciated.

Analysis of computer-aided diagnostics in the preoperative diagnosis of ovarian cancer: a systematic review

OBJECTIVES

Different noninvasive imaging methods to predict the chance of malignancy of ovarian tumors are available. However, their predictive value is limited due to subjectivity of the reviewer. Therefore, more objective prediction models are needed. Computer-aided diagnostics (CAD) could be such a model, since it lacks bias that comes with currently used models. In this study, we evaluated the available data on CAD in predicting the chance of malignancy of ovarian tumors.

METHODS

We searched for all published studies investigating diagnostic accuracy of CAD based on ultrasound, CT and MRI in pre-surgical patients with an ovarian tumor compared to reference standards.

RESULTS

In thirty-one included studies, extracted features from three different imaging techniques were used in different mathematical models. All studies assessed CAD based on machine learning on ultrasound, CT scan and MRI scan images. Per imaging method, subsequently ultrasound, CT and MRI, sensitivities ranged from 40.3 to 100%; 84.6-100% and 66.7-100% and specificities ranged from 76.3-100%; 69-100% and 77.8-100%. Results could not be pooled, due to broad heterogeneity. Although the majority of studies report high performances, they are at considerable risk of overfitting due to the absence of an independent test set.

CONCLUSION

Based on this literature review, different CAD for ultrasound, CT scans and MRI scans seem promising to aid physicians in assessing ovarian tumors through their objective and potentially cost-effective character. However, performance should be evaluated per imaging technique. Prospective and larger datasets with external validation are desired to make their results generalizable.

Copenhagen index (CPH-I) is more favorable than CA125, HE4, and risk of ovarian malignancy algorithm (ROMA): Nomogram prediction models with clinical-ultrasonographic feature for diagnosing ovarian neoplasms

Background

We aimed to analyze the benign and malignant identification efficiency of CA125, HE4, risk of ovarian malignancy algorithm (ROMA), Copenhagen Index (CPH-I) in ovarian neoplasms and establish a nomogram to improve the preoperative evaluation value of ovarian neoplasms.

Methods

A total of 3,042 patients with ovarian neoplasms were retrospectively classified according to postoperative pathological diagnosis [benign, n = 2389; epithelial ovarian cancer (EOC), n = 653]. The patients were randomly divided into training and test cohorts at a ratio of 7:3. Using CA125, HE4, ROMA, and CPH-I, Receiver operating characteristic (ROC) curves corresponding to different truncation values were calculated and compared, and optimal truncation values were selected. Clinical and imaging risk factors were calculated using univariate regression, and significant variables were selected for multivariate regression analysis combined with ROMA and CPH-I. Nomograms were constructed to predict the occurrence of EOC, and the accuracy was assessed by external validation.

Results

When the cutoff value of CA125, HE4, ROMA, and CPH-I was 100 U/ml, 70 pmol/L, 12.5/14.4% (premenopausal/postmenopausal) and 5%, respectively, the AUC was 0.674, 0.721, 0.750 and 0.769, respectively. From univariate regression, the clinical risk factors were older age, menopausal status, higher birth rate, hypertension, and diabetes; imaging risk factors were multilocular tumors, solid nodules, bilateral tumors, larger tumor diameter, and ascites. The AUC of the nomogram containing ROMA and CPH-I was 0.8914 and 0.9114, respectively, which was better than the prediction accuracies of CA125, HE4, ROMA, and CPH-I alone. The nomogram with CPH-I was significantly better than that with ROMA (P < 0.001), and a nomogram decision curve analysis (DCA) containing CPH-I seemed to have better clinical benefits than ROMA. For external validation of this nomogram containing ROMA and CPH-I, the C-indices were 0.889 and 0.900, and the calibration curves were close to 45°, showing good agreement with the predicted values.

Conclusion

We conclude that CPH-I and ROMA have higher diagnostic values in the preoperative diagnosis of EOC than other single tumor markers like CA125 or HE4. A nomogram based on CPH-I and ROMA with clinical and ultrasonic indicators had a better diagnostic value, and the CPH-I nomogram had the highest diagnostic efficacy.

Comparisons of Effectiveness in Differentiating Benign from Malignant Ovarian Masses between Conventional and Modified Risk of Malignancy Index (RMI)

OBJECTIVE

To compare the predictive performance in differentiating benign from malignant ovarian masses between the modified risk malignancy index (RMI) and the conventional RMI (RMI-1 and RMI-2).

METHODS

Women scheduled for elective surgery because of adnexal masses were recruited to undergo pelvic sonography within 24 h before surgery to assess the sonographic characteristics of the masses, focusing on loculi, solid part, ascites, bilateralness, papillary projection, and color flow mapping (CFM). Preoperative CA-125 levels were also measured. Modified RMI, RMI-1, and RMI-2 systems were used to predict malignant masses. The gold standard was pathological or intraoperative diagnosis.

RESULTS

A total of 342 ovarian masses, benign: 243 (71.1%); malignant: 99 (28.9%), meeting the inclusion criteria were analyzed. The sensitivity and the specificity of the modified RMI (87.9% and 81.9%) were significantly higher than those of RMI-1 (74.7% and 84.4%), and RMI-2 (79.8% and 81.1%, respectively). Based on ROC curves, the area under the curves were 0.930, 0.881 and 0.882 for modified RMI, RMI-1 and RMI-2, respectively.

CONCLUSION

Modified RMI had better predictive performance than the conventional RMI in differentiating between benign and malignant ovarian masses. Modified RMI may be useful to help general gynecologists or practitioners to triage patients with an adnexal mass, especially in settings of low resources.

Pathways to diagnosis of endometrial and ovarian cancer in the 45 and Up Study cohort

PURPOSE

To determine pathways to endometrial or ovarian cancer diagnosis by comparing health service utilization between cancer cases and matched cancer-free controls, using linked health records.

METHODS

From cancer registry records, we identified 238 incident endometrial and 167 ovarian cancer cases diagnosed during 2006-2013 in the Australian 45 and Up Study cohort (142,973 female participants). Each case was matched to four cancer-free controls on birthdate, sex, place of residence, smoking status, and body mass index. The use of relevant health services during the 13-18-, 7-12-, 0-6-, and 0-1-months pre-diagnosis for cases and the corresponding dates for their matched controls was determined through linkage with subsidized medical services and hospital records.

RESULTS

Healthcare utilization diverged between women with cancer and controls in the 0-6-months, particularly 0-1 months, pre-diagnosis. In the 0-1 months, 74.8% of endometrial and 50.3% of ovarian cases visited a gynecologist/gynecological oncologist, 11.3% and 59.3% had a CA125 test, 5.5% and 48.5% an abdominal pelvic CT scan, and 34.5% and 30.5% a transvaginal pelvic ultrasound, respectively (versus ≤ 1% of matched controls). Moreover, 25.1% of ovarian cancer cases visited an emergency department in the 0-1-months pre-diagnosis (versus 1.3% of matched controls), and GP visits were significantly more common for cases than controls in this period.

CONCLUSION

Most women with endometrial or ovarian cancer accessed recommended specialists and tests in the 0-1-months pre-diagnosis, but a high proportion of women with ovarian cancer visited an emergency department. This reinforces the importance of timely specialist referral.

Age and Referral Route Impact the Access to Diagnosis for Women with Advanced Ovarian Cancer

Purpose

The majority of women with ovarian cancer are diagnosed in late stages. Most women do have symptoms prior to diagnosis, sometimes several months before the diagnosis. The aim of this study was to evaluate the timeline from the first presentation of symptoms to a physician until there is a reasonable suspicion of cancer, among women diagnosed with advanced stage ovarian cancer. We wanted to investigate which symptoms were the most common and whether there are other factors affecting the time interval before the suspicion of cancer was confirmed.

Patients and Methods

This was a retrospective population-based cohort study of women diagnosed with advanced ovarian cancer between January 1, 2017 and December 31, 2019 who were referred to Skane University Hospital Lund, Sweden. Data were collected from electronic medical records at Skane University Hospital. The time interval was recorded as the time from first physician consultation with predefined symptoms to the date when there was a reasonable suspicion of ovarian cancer. Data processing and statistical analysis were performed with the statistical software R.

Results

Among the 249 patients included in this study, the median time interval from the first consultation to the reasonable suspicion of cancer was 24 days. The first consultation in specialized care had a 70% decrease in delay compared to primary care. Emergency consultations had a 52.2% decrease in time delay compared to planned consultations. Older age was associated with an increase in the geometric mean by 54.7%, comparing the first to the third quartile. The most common symptom was abdominal pain.

Conclusion

The length of time interval from first presentation with symptoms relating to ovarian cancer to reasonable suspicion of cancer was associated with whether the consultation was in primary or specialized care, emergency or planned visit and the patient's age.

Psychological impact of referral to an oncology hospital on patients with an ovarian mass

OBJECTIVES

In patients with an ovarian mass, a risk of malignancy assessment is used to decide whether referral to an oncology hospital is indicated. Risk assessment strategies do not perform optimally, resulting in either referral of patients with a benign mass or patients with a malignant mass not being referred. This process may affect the psychological well-being of patients. We evaluated cancer-specific distress during work-up for an ovarian mass, and patients' perceptions during work-up, referral, and treatment.

METHODS

Patients with an ovarian mass scheduled for surgery were enrolled. Using questionnaires we measured (1) cancer-specific distress using the cancer worry scale, (2) patients' preferences regarding referral (evaluated pre-operatively), and (3) patients' experiences with work-up and treatment (evaluated post-operatively). A cancer worry scale score of ≥14 was considered as clinically significant cancer-specific distress.

RESULTS

A total of 417 patients were included, of whom 220 (53%) were treated at a general hospital and 197 (47%) at an oncology hospital. Overall, 57% had a cancer worry scale score of ≥14 and this was higher in referred patients (69%) than in patients treated at a general hospital (43%). 53% of the patients stated that the cancer risk should not be higher than 25% to undergo surgery at a general hospital. 96% of all patients were satisfied with the overall work-up and treatment. No difference in satisfaction was observed between patients correctly (not) referred and patients incorrectly (not) referred.

CONCLUSIONS

Relatively many patients with an ovarian mass experienced high cancer-specific distress during work-up. Nevertheless, patients were satisfied with the treatment, regardless of the final diagnosis and the location of treatment. Moreover, patients preferred to be referred even if there was only a relatively low probability of having ovarian cancer. Patients' preferences should be taken into account when deciding on optimal cut-offs for risk assessment strategies.

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging

Background

Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of distinguishing between benign and malignant ovarian tumors. Numerous types of ovarian tumors exist, many of which exhibit similar characteristics that increase the ambiguity in clinical diagnosis. Using deep learning technology, we aimed to develop a method that rapidly and accurately assists the different diagnosis of ovarian tumors in ultrasound images.

Methods

Based on deep learning method, we used ten well-known convolutional neural network models (e.g., Alexnet, GoogleNet, and ResNet) for training of transfer learning. To ensure method stability and robustness, we repeated the random sampling of the training and validation data ten times. The mean of the ten test results was set as the final assessment data. After the training process was completed, the three models with the highest ratio of calculation accuracy to time required for classification were used for ensemble learning pertaining. Finally, the interpretation results of the ensemble classifier were used as the final results. We also applied ensemble gradient-weighted class activation mapping (Grad-CAM) technology to visualize the decision-making results of the models.

Results

The highest mean accuracy, mean sensitivity, and mean specificity of ten single CNN models were 90.51 ± 4.36%, 89.77 ± 4.16%, and 92.00 ± 5.95%, respectively. The mean accuracy, mean sensitivity, and mean specificity of the ensemble classifier method were 92.15 ± 2.84%, 91.37 ± 3.60%, and 92.92 ± 4.00%, respectively. The performance of the ensemble classifier is better than that of a single classifier in three evaluation metrics. Moreover, the standard deviation is also better which means the ensemble classifier is more stable and robust.

Conclusion

From the comprehensive perspective of data quantity, data diversity, robustness of validation strategy, and overall accuracy, the proposed method outperformed the methods used in previous studies. In future studies, we will continue to increase the number of authenticated images and apply our proposed method in clinical settings to increase its robustness and reliability.

Outcome and prognostic factors of unexpected ovarian carcinomas

BACKGROUND

We investigated risk factors influencing the outcome of unexpected ovarian carcinomas.

METHODS

We reviewed the ovarian carcinoma patients treated at atertiary medical institution between 2000 and 2017 and analyze the clinico-pathological characteristics, treatment strategies, recurrence status, and outcome.

RESULTS

A total of 112 women (65 primary laparoscopic surgery [LSC] and 47 laparotomic surgery [LAPA]) were included in the analysis. The LSC group had smaller ovarian tumors (10.5 ± 7.3 cm vs. 16.6 ± 8.7 cm, p = 0.031) and higher incidence of subsequent staging surgery (56.9% vs. 25.5%, p = 0.0001) compared to the LAPA group. There were 98/112 (86.6%) of early stages (I/II) diseases. The difference between the recurrent rate (27.7% vs. 31.9%), disease-free survival (DFS), and overall survival (OS) were not significant among surgical groups. In the multivariate analysis, FIGO stage (stage II hazard ratio [HR] 6.61, p = 0.007; stage III HR 8.40, p = 0.002) was the only prognostic factor for DFS. FIGO stage (stage II HR 20.78, p = 0.0001; stage III HR 7.99, p = 0.017), histological type (mucinous HR 12.49, p = 0.036), and tumor grade (grade 3 HR 35.01, p = 0.003) were independent prognostic factors for OS, while women with latency >28 days from primary to staging surgery had significantly poorer OS (p = 0.008). Women with latency >28 days between primary surgery and adjuvant chemotherapy had similar DFS (p = 0.31) and a trend of poorer OS (p = 0.064).

CONCLUSIONS

The prognosis of unexpected ovarian cancer is independent from the primary surgical procedure and comprehensive staging surgery should be performed at close proximity after the diagnosis of unexpected ovarian malignancy.

Emerging perspectives on growth factor metabolic relationships in the ovarian cancer ascites environment

The ascites ecosystem in ovarian cancer is inhabited by complex cell types and is bathed in an environment rich in cytokines, chemokines, and growth factors that directly and indirectly impact metabolism of cancer cells and tumor associated cells. This milieu of malignant ascites, provides a 'rich' environment for the disease to thrive, contributing to every aspect of advanced ovarian cancer, a devastating gynecological cancer with a significant gap in targeted therapeutics. In this perspective we focus our discussions on the 'acellular' constituents of this liquid malignant tumor microenvironment, and how they influence metabolic pathways. Growth factors, chemokines and cytokines are known modulators of metabolism and have been shown to impact nutrient uptake and metabolic flexibility of tumors, yet few studies have explored how their enrichment in malignant ascites of ovarian cancer patients contributes to the metabolic requirements of ascites-resident cells. We focus here on TGF-βs, VEGF and ILs, which are frequently elevated in ovarian cancer ascites and have all been described to have direct or indirect effects on metabolism, often through gene regulation of metabolic enzymes. We summarize what is known, describe gaps in knowledge, and provide examples from other tumor types to infer potential unexplored roles and mechanisms for ovarian cancer. The distribution and variation in acellular ascites components between patients poses both a challenge and opportunity to further understand how the ascites may contribute to disease heterogeneity. The review also highlights opportunities for studies on ascites-derived factors in regulating the ascites metabolic environment that could act as a unique signature in aiding clinical decisions in the future.

Diagnostics of Ovarian Tumors in Postmenopausal Patients

Early diagnosis of ovarian cancer remains an urgent issue owing to the continuing trend towards increasing incidence along with only marginal improvements in mortality and 5-year survival rates. Furthermore, there is a lack of a clear formulation of the concept of pathogenesis. The diagnostic values of tumor markers, their potential advantages and disadvantages, and their combination with radiation imaging methods and transvaginal sonography are discussed. More advanced imaging techniques, such as computed tomography and magnetic resonance imaging have proven too expensive for widespread use. According to the World Health Organization, more than half of the world’s population does not have access to diagnostic imaging. Consequently, there is high demand for a low-cost, reliable, and safe imaging system for detecting and monitoring cancer. Currently, there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and for determining surgical access and optimal surgical intervention measures in postmenopausal patients are lacking. Medical microwave radiometry shows promising results yielding an accuracy of 90%.

Molecular Biomarkers for the Early Detection of Ovarian Cancer

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

Feasibility and Safety of Laparoscopic Surgery in Large Ovarian Masses

Objectives

To evaluate the feasibility and safety of laparoscopic surgery for large ovarian masses with benign features.

Materials and Methods

Women who underwent laparoscopic surgery for an ovarian mass with benign features between 2017 and 2019 at a tertiary referral center were included in the retrospective study. Based on the size of the ovarian mass, the women were divided into the case and control groups of ≥10 cm and <10 cm, respectively. Clinical characteristics, operative findings, histopathological results, and complication rates of the groups were compared.

Results

A total of 260 women, 64 women with large masses and 196 with small masses were included in the study. The operation time, intraoperative cyst rupture rate, complication rate, and hospital stay were similar in the case and control groups (P > 0.05). The cyst aspiration rate (29.7% vs. 5.1%, P < 0.001) and the unexpected malignancy rate (7.8% vs. 0.0% P = 0.001) were significantly higher in the case group than in the control group.

Conclusion

Laparoscopic surgery was found feasible for the treatment of women with large ovarian masses. However, a higher unexpected malignancy rate requires the careful patient selection and appropriate counseling preoperatively in these cases.

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass

OBJECTIVE

To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood.

METHODS

This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared.

RESULTS

A total of 183 evaluable patients were enrolled (average age 56 years, range 19-91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0-98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2-65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9-93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3-97.8%) for stage I-II and 98.9% (95% CI 96.7-100%) for stage III-IV patients with epithelial ovarian cancer.

CONCLUSION

Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT02781272.

FUNDING SOURCE

This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).

The Intervention Probability Curve: Modeling the Practical Application of Threshold-Guided Decision-Making, Evaluated in Lung, Prostate, and Ovarian Cancers

BACKGROUND

Diagnostic prediction models are useful guides when considering lesions suspicious for cancer, as they provide a quantitative estimate of the probability that a lesion is malignant. However, the decision to intervene ultimately rests on patient and physician preferences. The appropriate intervention in many clinical situations is typically defined by clinically relevant, actionable subgroups based upon the probability of malignancy. However, the "all-or-nothing" approach of threshold-based decisions is in practice incorrect.

METHODS

Here, we present a novel approach to understanding clinical decision-making, the intervention probability curve (IPC). The IPC models the likelihood that an intervention will be chosen as a continuous function of the probability of disease. We propose the cumulative distribution function as a suitable model. The IPC is explored using the National Lung Screening Trial and the Prostate Lung Colorectal and Ovarian Screening Trial datasets.

RESULTS

Fitting the IPC results in a continuous curve as a function of pretest probability of cancer with high correlation (R2 &gt; 0.97 for each) with fitted parameters closely aligned with professional society guidelines.

CONCLUSIONS

The IPC allows analysis of intervention decisions in a continuous, rather than threshold-based, approach to further understand the role of biomarkers and risk models in clinical practice.

IMPACT

We propose that consideration of IPCs will yield significant insights into the practical relevance of threshold-based management strategies and could provide a novel method to estimate the actual clinical utility of novel biomarkers.

Patients' subjective assessment as a decisive predictor of malignancy in pelvic masses: results of a multicentric, prospective pelvic mass study

OBJECTIVE

The prognosis for ovarian cancer patients remains poor. A key to maximizing survival rates is early detection and treatment. This requires an accurate prediction of malignancy. Our study seeks to improve the accuracy of prediction by focusing on early subjective assessment of malignancy. We therefore investigated the assessment of patients themselves in comparison to the assessment of physicians.

METHODS

One thousand three hundred and thirty patients participated in a prospective and multicenter study in six hospitals in Berlin. Using univariate analysis and multivariate logistic regression models, we measured the accuracy of the early subjective assessment in comparison to the final histological outcome. Moreover, we investigated factors related to the assessment of patients and physicians.

RESULTS

The patients' assessment of malignancy is remarkably accurate. With a positive predictive value of 58%, the majority of patients correctly assessed a pelvic mass as malignant. With more information available, physicians achieved only a slightly more accurate prediction of 63%.

CONCLUSIONS

For the first time, our study considered subjective factors in the diagnostic process of pelvic masses. This paper demonstrates that the patients' personal assessment should be taken seriously as it can provide a significant contribution to earlier diagnosis and thus improved therapy and overall prognosis.

Predicting value of HE4 and CA125 markers for optimal cytoreductive surgery in ovarian cancer patients

We conducted a cross-sectional study to evaluate the role of serum levels of CA125 and HE4 in predicting optimal cytoreductive surgery. Eligible women who had been diagnosed with ovarian cancer based on both clinical and imaging criteria were enrolled in this study. Serum levels of CA 125 and HE4 were checked before surgery and all patients underwent complete surgical staging. After completion of the pathological evaluation, data were entered in SPSS version 23. One hundred and ten individuals were enrolled in our study. We divided cases between two groups: stage I to Ш b and stage Шc to IV. Serum level of HE4 >170 pmol/L can predict optimal cytoreductive surgery before operation. (sensitivity:80% and specificity 70%) and serum level of CA 125 > 320 UI/mL can predict optimal cytoreductive surgery before operation. (sensitivity:80% and specificity 70%). Our data demonstrated a negative predictive value of about 80% for both HE4 and CA125. Based on these cut-off, unnecessary surgery can be avoided in many cases, however, it is unwise to ignore clinical performance and radiological findings. Nevertheless, we can say the evaluation of tumor markers is feasible and helpful in predicting optimal surgery.