Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study.

BACKGROUND: Multiple risk-prediction models are used in clinical practice to triage patients as being at low risk or high risk of ovarian cancer. In the ROCkeTS study, we aimed to identify the best diagnostic test for ovarian cancer in symptomatic patients, through head-to-head comparisons of risk-prediction models, in a real-world setting. Here, we report the results for the postmenopausal cohort. METHODS: In this multicentre, prospective diagnostic accuracy study, we recruited newly presenting female patients aged 16-90 years with non-specific symptoms and raised CA125 or abnormal ultrasound results (or both) who had been referred via rapid access, elective clinics, or emergency presentations from 23 hospitals in the UK. Patients with normal CA125 and simple ovarian cysts of smaller than 5 cm in diameter, active non-ovarian malignancy, or previous ovarian malignancy, or those who were pregnant or declined a transvaginal scan, were ineligible. In this analysis, only postmenopausal participants were included. Participants completed a symptom questionnaire, gave a blood sample, and had transabdominal and transvaginal ultrasounds performed by International Ovarian Tumour Analysis consortium (IOTA)-certified sonographers. Index tests were Risk of Malignancy 1 (RMI1) at a threshold of 200, Risk of Malignancy Algorithm (ROMA) at multiple thresholds, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX) at thresholds of 3% and 10%, IOTA SRRisk model at thresholds of 3% and 10%, IOTA Simple Rules (malignant vs benign, or inconclusive), and CA125 at 35 IU/mL. In a post-hoc analysis, the Ovarian Adnexal and Reporting Data System (ORADS) at 10% was derived from IOTA ultrasound variables using established methods since ORADS was described after completion of recruitment. Index tests were conducted by study staff masked to the results of the reference standard. The comparator was RMI1 at the 250 threshold (the current UK National Health Service standard of care). The reference standard was surgical or biopsy tissue histology or cytology within 3 months, or a self-reported diagnosis of ovarian cancer at 12 month follow-up. The primary outcome was diagnostic accuracy at predicting primary invasive ovarian cancer versus benign or normal histology, assessed by analysing the sensitivity, specificity, C-index, area under receiver operating characteristic curve, positive and negative predictive values, and calibration plots in participants with conclusive reference standard results and available index test data. This study is registered with the International Standard Randomised Controlled Trial Number registry (ISRCTN17160843). FINDINGS: Between July 13, 2015, and Nov 30, 2018, 1242 postmenopausal patients were recruited, of whom 215 (17%) had primary ovarian cancer. 166 participants had missing, inconclusive, or other reference standard results; therefore, data from a maximum of 1076 participants were used to assess the index tests for the primary outcome. Compared with RMI1 at 250 (sensitivity 82·9% [95% CI 76·7 to 88·0], specificity 87·4% [84·9 to 89·6]), IOTA ADNEX at 10% was more sensitive (difference of -13·9% [-20·2 to -7·6], p<0·0001) but less specific (difference of 28·5% [24·7 to 32·3], p<0·0001). ROMA at 29·9 had similar sensitivity (difference of -3·6% [-9·1 to 1·9], p=0·24) but lower specificity (difference of 5·2% [2·5 to 8·0], p=0·0001). RMI1 at 200 had similar sensitivity (difference of -2·1% [-4·7 to 0·5], p=0·13) but lower specificity (difference of 3·0% [1·7 to 4·3], p<0·0001). IOTA SRRisk model at 10% had similar sensitivity (difference of -4·3% [-11·0 to -2·3], p=0·23) but lower specificity (difference of 16·2% [12·6 to 19·8], p<0·0001). IOTA Simple Rules had similar sensitivity (difference of -1·6% [-9·3 to 6·2], p=0·82) and specificity (difference of -2·2% [-5·1 to 0·6], p=0·14). CA125 at 35 IU/mL had similar sensitivity (difference of -2·1% [-6·6 to 2·3], p=0·42) but higher specificity (difference of 6·7% [4·3 to 9·1], p<0·0001). In a post-hoc analysis, when compared with RMI1 at 250, ORADS achieved similar sensitivity (difference of -2·1%, 95% CI -8·6 to 4·3, p=0·60) and lower specificity (difference of 10·2%, 95% CI 6·8 to 13·6, p<0·0001). INTERPRETATION: In view of its higher sensitivity than RMI1 at 250, despite some loss in specificity, we recommend that IOTA ADNEX at 10% should be considered as the new standard-of-care diagnostic in ovarian cancer for postmenopausal patients. FUNDING: UK National Institute of Heath Research.

Symptom-triggered testing detects early stage and low volume resectable advanced stage ovarian cancer.

OBJECTIVE: Symptom-triggered testing for ovarian cancer was introduced to the UK whereby symptomatic women undergo an ultrasound scan and serum CA125, and are referred to hospital within 2 weeks if these are abnormal. The potential value of symptom-triggered testing in the detection of early-stage disease or low tumor burden remains unclear in women with high grade serous ovarian cancer. In this descriptive study, we report on the International Federation of Gynecology and Obstetrics (FIGO) stage, disease distribution, and complete cytoreduction rates in women presenting via the fast-track pathway and who were diagnosed with high grade serous ovarian cancer. METHODS: We analyzed the dataset from Refining Ovarian Cancer Test accuracy Scores (ROCkeTS), a single-arm prospective diagnostic test accuracy study recruiting from 24 hospitals in the UK. The aim of ROCkeTS is to validate risk prediction models in symptomatic women. We undertook an opportunistic analysis for women recruited between June 2015 to July 2022 and who were diagnosed with high grade serous ovarian cancer via the fast-track pathway. Women presenting with symptoms suspicious for ovarian cancer receive a CA125 blood test and an ultrasound scan if the CA125 level is abnormal. If either of these is abnormal, women are referred to secondary care within 2 weeks. Histology details were available on all women who underwent surgery or biopsy within 3 months of recruitment. Women who did not undergo surgery or biopsy at 3 months were followed up for 12 months as per the national guidelines in the UK. In this descriptive study, we report on patient demographics (age and menopausal status), WHO performance status, FIGO stage at diagnosis, disease distribution (low/pelvic confined, moderate/extending to mid-abdomen, high/extending to upper abdomen) and complete cytoreduction rates in women who underwent surgery. RESULTS: Of 1741 participants recruited via the fast-track pathway, 119 (6.8%) were diagnosed with high grade serous ovarian cancer. The median age was 63 years (range 32-89). Of these, 112 (94.1%) patients had a performance status of 0 and 1, 30 (25.2%) were diagnosed with stages I/II, and the disease distribution was low-to-moderate in 77 (64.7%). Complete and optimal cytoreduction were achieved in 73 (61.3%) and 18 (15.1%). The extent of disease was low in 43 of 119 (36.1%), moderate in 34 of 119 (28.6%), high in 32 of 119 (26.9%), and not available in 10 of 119 (8.4%). Nearly two thirds, that is 78 of 119 (65.5%) women with high grade serous ovarian cancer, underwent primary debulking surgery, 36 of 119 (30.3%) received neoadjuvant chemotherapy followed by interval debulking surgery, and 5 of 119 (4.2%) women did not undergo surgery. CONCLUSION: Our results demonstrate that one in four women identified with high grade serous ovarian cancer through the fast-track pathway following symptom-triggered testing was diagnosed with early-stage disease. Symptom-triggered testing may help identify women with a low disease burden, potentially contributing to high complete cytoreduction rates.

Predictors of successful expectant and medical management of miscarriage: A systematic review.

INTRODUCTION: 15.3% of pregnancies result in miscarriage, management options include expectant, medical, or surgical. However, each patient has a range of variables, which makes navigating the available literature challenging when supporting individual patient decision-making. This systematic review aims to investigate whether there are any specific predictors for miscarriage management outcome. MATERIAL AND METHODS: The following databases were searched, from the start of each database up to April 2023: PubMed, Medline, and Google Scholar. Inclusion criteria were studies interrogating defined predictors for expectant or medical management of miscarriage success. Exclusion criteria were poor quality, review articles, trial protocols, and congress abstracts. Data collection was carried as per PRISMA guidelines. Quality assessment for each study was assessed using the QUIPS proforma. RESULTS: Relevant predictors include demographics, ultrasound features, presenting symptoms, and biochemical markers. Across the 24 studies there is heterogeneity in miscarriage definition, predictors reported, and management outcomes used. Associations with certain variables and miscarriage management outcomes are described. Ten studies assessed the impact of miscarriage type on expectant and/or medical management. The majority found that a diagnosis of incomplete miscarriage had a higher success rate following expectant or medical management compared to missed miscarriage or anembryonic pregnancy. CONCLUSIONS: We conclude that there is evidence supporting the possibility to offer personalized miscarriage management advice with case specific predictors. Further larger studies with consistent definitions of predictors, management, and outcomes are needed in order to better support women through the decision-making of miscarriage management.

The 'onion skin' sign of a low-grade appendiceal mucinous neoplasm: An incidental finding during early pregnancy assessment.

A low-grade appendiceal mucinous neoplasm (LAMN) is a cystic dilatation of the appendix resulting from the accumulation of mucinous secretions caused by a luminal obstruction. Although usually benign, pseudomyxoma peritonei may occur in the event of rupture, and 10% of cases may be secondary to appendiceal cystadenocarcinoma. A LAMN is both more common and more likely to have a malignant association in women, making it an entity with which practitioners of gynaecological ultrasound should be familiar. Although not the primary aim, early pregnancy ultrasound assessments can offer the diagnostic opportunity to identify pelvic pathology. A LAMN can be identified on ultrasonography by visualisation of an adnexal mass separate to the ovary, which due to the layers of secretions has a distinctive appearance previously likened to 'onion-skin' or 'whipped-cream'. Here, we describe an incidental finding of a LAMN during an early pregnancy assessment. Practitioners of early pregnancy ultrasound should be familiar with the characteristic morphology of this rare but important finding.

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.

Using online search activity for earlier detection of gynaecological malignancy.

BACKGROUND: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses. METHODS: This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235. RESULTS: The cohort had a median age of 53 years old (range 20-81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral. CONCLUSIONS: Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes.

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.

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.

Beta-human chorionic gonadotrophin point of care testing for the management of pregnancy of unknown location.

RESEARCH QUESTION: Does a commercially available quantitative beta-human chorionic gonadotrophin (BHCG) point of care testing (POCT) device improve workflow management in early pregnancy by performing comparably to gold standard laboratory methods, and is the performance of a validated pregnancy of unknown location (PUL) triage strategy maintained using POCT BHCG results? DESIGN: Women classified with a PUL between 2018 and 2021 at three early pregnancy units were included. The linear relationship of untreated whole-blood POCT and serum laboratory BHCG values was defined using coefficients and regression. Paired serial BHCG values were then incorporated into the validated M6 multinomial logistic regression model to stratify the PUL as at high risk or at low risk of clinical complications. The sensitivity and negative predictive value were assessed. The timings required for equivocal POCT and laboratory care pathways were compared. RESULTS: A total of 462 PUL were included. The discrepancy between 571 laboratory and POCT BHCG values was -5.2% (-6.2 IU/l), with a correlation coefficient of 0.96. The 133 PUL with paired 0 and 48 h BHCG values were compared using the M6 model. The sensitivity for high-risk outcomes (96.2%) and negative predictive values (98.5%) was excellent for both. Sample receipt and laboratory processing took 135 min (421 timings), compared with 12 min (91 timings) when using POCT (P < 0.0001). CONCLUSIONS: POCT BHCG values correlated well with laboratory testing measurements. The M6 model retained its performance when using POCT BHCG values. Using the model with POCT may improve workflow and patient care without compromising on effective PUL triage.

Ambulatory human chorionic gonadotrophin (hCG) testing: a verification of two hCG point of care devices.

OBJECTIVES: Quantitative human chorionic gonadotropin (hCG) measurements are used to manage women classified with a pregnancy of unknown location (PUL). Two point of care testing (POCT) devices that quantify hCG are commercially available. We verified the i-STAT 1 (Abbott) and the AQT 90 FLEX (Radiometer) prior to use in PUL triage. METHODS: Tests for precision, external quality assurance (EQA), correlation, hook effect and recovery were undertaken alongside a POCT usability assessment during this prospective multi-center verification. RESULTS: Coefficients of variation ranged between 4.0 and 5.1 % for the three i-STAT 1 internal quality control (IQC) solutions and between 6.8 and 7.3 % for the two AQT IQC solutions. Symmetric differences in POCT EQA results when compared with laboratory and EQA stock values ranged between 3.2 and 24.5 % for the i-STAT 1 and between 3.3 and 36.9 % for the AQT. Correlation coefficients (i-STAT 1: 0.96, AQT: 0.99) and goodness of fit curves (i-STAT 1: 0.92, AQT: 0.99) were excellent when using suitable whole blood samples. An hCG hook effect was noted with the i-STAT 1 between 572,194 and 799,089 IU/L, lower than the hook effect noted with the AQT, which was between 799,089 and 1,619,309 IU/L. When hematocrit concentration was considered in sample types validated for use with each device, hCG recovery was 108 % with the i-STAT 1 and 98 % with the AQT. The i-STAT 1 scored lower on usability overall (90/130) than the AQT (121/130, p<0.001, Mann-Whitney). CONCLUSIONS: Both hCG POCT devices were verified for use in clinical practice. Practical factors must also be considered when choosing which device to use in each unit.

Using simple clinical and ultrasound variables to develop a model to predict first trimester pregnancy viability.

INTRODUCTION: Early prediction of pregnancies destined to miscarry will allow couples to prepare for this common but often unexpected eventuality, and clinicians to allocate finite resources. We aimed to develop a prediction model combining clinical, demographic, and sonographic data as a clinical tool to aid counselling about first trimester pregnancy outcome. MATERIAL AND METHODS: This is a prospective, observational cohort study conducted at Queen Charlotte's and Chelsea Hospital, UK from March 2014 to May 2019. Women with confirmed intrauterine pregnancies between 5 weeks and their dating scan (11-14 weeks) were recruited. Participants attended serial ultrasound scans in the first trimester and at each visit recorded symptoms of vaginal bleeding, pelvic pain, nausea and vomiting using validated scoring tools. Pregnancies were followed up until the dating scan (11-14 weeks). Univariate and multivariate analyses were performed to predict first trimester viability. A model was developed with multivariable logistic regression, variables limited by feature selection, and bootstrapping with multiple imputation was used for internal validation. RESULTS: 1403 women were recruited and after exclusions, data were available for 1105. 160 women (14.5 %) experienced first trimester miscarriage and 945 women (85.5 %) had viable pregnancies at 11-14 weeks' gestation. The average gestational age at the initial visit (calculated from the menstrual dates) was 7 + 1 weeks (+/-12.2 days). A multivariable logistic regression model was developed to predict first trimester viability and included the variables: mean gestational sac diameter, presence of fetal heart pulsations, difference in gestational age from last menstrual period and from mean sac diameter on ultrasonography, current folic acid usage and maternal age. The model demonstrated good performance (optimism-corrected area under curve (AUC) 0.84, 95 % CI 0.81-0.87; optimism-corrected calibration slope 0.969). CONCLUSION: We have developed and internally validated a model to predict first trimester viability with good accuracy prior to the 11-14 week dating scan, which now needs to be externally validated prior to clinical use.

Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm.

BACKGROUND: Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic. METHODS: This retrospective cohort study used 5909 patients recruited from 1999 to 2012 for model development, and 3199 patients recruited from 2012 to 2015 for model validation. Patients were recruited at oncology referral or general centers and underwent an ultrasound examination and surgery ≤ 120 days later. We developed models using standard multinomial logistic regression (MLR), Ridge MLR, random forest (RF), XGBoost, neural networks (NN), and support vector machines (SVM). We used nine clinical and ultrasound predictors but developed models with or without CA125. RESULTS: Most tumors were benign (3980 in development and 1688 in validation data), secondary metastatic tumors were least common (246 and 172). The c-statistic (AUROC) to discriminate benign from any type of malignant tumor ranged from 0.89 to 0.92 for models with CA125, from 0.89 to 0.91 for models without. The multiclass c-statistic ranged from 0.41 (SVM) to 0.55 (XGBoost) for models with CA125, and from 0.42 (SVM) to 0.51 (standard MLR) for models without. Multiclass calibration was best for RF and XGBoost. Estimated probabilities for a benign tumor in the same patient often differed by more than 0.2 (20% points) depending on the model. Net Benefit for diagnosing malignancy was similar for algorithms at the commonly used 10% risk threshold, but was slightly higher for RF at higher thresholds. Comparing models, between 3% (XGBoost vs. NN, with CA125) and 30% (NN vs. SVM, without CA125) of patients fell on opposite sides of the 10% threshold. CONCLUSION: Although several models had similarly good performance, individual probability estimates varied substantially.

A core outcome set for trials in miscarriage management and prevention: An international consensus development study.

OBJECTIVE: To develop core outcome sets (COS) for miscarriage management and prevention. DESIGN: Modified Delphi survey combined with a consensus development meeting. SETTING: International. POPULATION: Stakeholder groups included healthcare providers, international experts, researchers, charities and couples with lived experience of miscarriage from 15 countries: 129 stakeholders for miscarriage management and 437 for miscarriage prevention. METHODS: Modified Delphi method and modified nominal group technique. RESULTS: The final COS for miscarriage management comprises six outcomes: efficacy of treatment, heavy vaginal bleeding, pelvic infection, maternal death, treatment or procedure-related complications, and patient satisfaction. The final COS for miscarriage prevention comprises 12 outcomes: pregnancy loss <24 weeks' gestation, live birth, gestation at birth, pre-term birth, congenital abnormalities, fetal growth restriction, maternal (antenatal) complications, compliance with intervention, patient satisfaction, maternal hospitalisation, neonatal or infant hospitalisation, and neonatal or infant death. Other outcomes identified as important were mental health-related outcomes, future fertility and health economic outcomes. CONCLUSIONS: This study has developed two core outcome sets, through robust methodology, that should be implemented across future randomised trials and systematic reviews in miscarriage management and prevention. This work will help to standardise outcome selection, collection and reporting, and improve the quality and safety of future studies in miscarriage.

Definition and Criteria for Diagnosing Cesarean Scar Disorder.

Importance: Approximately 60% of women develop a uterine niche after a cesarean delivery (CD). A niche is associated with various gynecological symptoms including abnormal uterine bleeding, pain, and infertility, but there is little consensus in the literature on the distinction between the sonographic finding of a niche and the constellation of associated symptoms. Objective: To achieve consensus on defining the clinical condition that constitutes a symptomatic uterine niche and agree upon diagnostic criteria and uniform nomenclature for this condition. Design, Setting, and Participants: A consensus based modified electronic Delphi (eDelphi) study, with a predefined Rate of Agreement (RoA) of 70% or higher. Experts were selected according to their expertise with niche-related consultations, publications, and participation in expert groups and received online questionnaires between November 2021 and May 2022. Main Outcomes and Measures: Definition, nomenclature, symptoms, conditions to exclude, and diagnostic criteria of an illness caused by a symptomatic uterine niche. Results: In total, 31 of the 60 invited experts (51.7%) participated, of whom the majority worked in university-affiliated hospitals (28 of 31 [90.3%]), specialized in benign gynecology (20 of 31 [64.5%]), and worked in Europe (24 of 31 [77.4%]). Three rounds were required to achieve consensus on all items. All participants underlined the relevance of a new term for a condition caused by a symptomatic niche and its differentiation from a sonographic finding only. Experts agreed to name this condition cesarean scar disorder, defined as a uterine niche in combination with at least 1 primary or 2 secondary symptoms (RoA, 77.8%). Defined primary symptoms were postmenstrual spotting, pain during uterine bleeding, technical issues with catheter insertion during embryo transfer, and secondary unexplained infertility combined with intrauterine fluid. Secondary symptoms were dyspareunia, abnormal vaginal discharge, chronic pelvic pain, avoiding sexual intercourse, odor associated with abnormal blood loss, secondary unexplained infertility, secondary infertility despite assisted reproductive technology, negative self-image, and discomfort during participation in leisure activities. Consensus was also achieved on certain criteria that should be met and conditions that should be excluded before making the diagnosis. Conclusions and Relevance: In this modified Delphi study, a panel of 31 international niche experts reached consensus for the constellation of symptoms secondary to a uterine niche and named it cesarean scar disorder.

External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups.

Importance: Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy. Objective: To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy. Design, Setting, and Participants: Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022. Exposures: Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy. Main Outcomes and Measures: Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information. Results: Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%). Conclusions and Relevance: The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.

Sonographic, Demographic, and Clinical Characteristics of Pre- and Postmenopausal Women with Endometrial Cancer; Results from a Post Hoc Analysis of the IETA4 (International Endometrial Tumor Analysis) Multicenter Cohort.

In this study, we conducted a comparative analysis of demographic, histopathological, and sonographic characteristics between pre- and postmenopausal women diagnosed with endometrial cancer, while also examining sonographic and anthropometric features in 'low' and 'intermediate/high-risk' cases, stratified by menopausal status. Our analysis, based on data from the International Endometrial Tumor Analysis (IETA) 4 cohort comprising 1538 women (161 premenopausal, 1377 postmenopausal) with biopsy-confirmed endometrial cancer, revealed that premenopausal women, compared to their postmenopausal counterparts, exhibited lower parity (median 1, IQR 0-2 vs. 1, IQR 1-2, p = 0.001), a higher family history of colon cancer (16% vs. 7%, p = 0.001), and smaller waist circumferences (median 92 cm, IQR 82-108 cm vs. 98 cm, IQR 87-112 cm, p = 0.002). Premenopausal women more often had a regular endometrial-myometrial border (39% vs. 23%, p < 0.001), a visible endometrial midline (23% vs. 11%, p < 0.001), and undefined tumor (73% vs. 84%, p = 0.001). Notably, despite experiencing a longer duration of abnormal uterine bleeding (median 5 months, IQR 3-12 vs. 3 months, 2-6, p < 0.001), premenopausal women more often had 'low' risk disease (78% vs. 46%, p < 0.001). Among sonographic and anthropometric features, only an irregular endometrial-myometrial border was associated with 'intermediate/high' risk in premenopausal women. Conversely, in postmenopausal women, multiple features correlated with 'intermediate/high' risk disease. Our findings emphasize the importance of considering menopausal status when evaluating sonographic features in women with endometrial cancer.

Miscarriage syndrome: Linking early pregnancy loss to obstetric and age-related disorders.

Upon embryo implantation, the uterine mucosa - the endometrium - transforms into a robust decidual matrix that accommodates the fetal placenta throughout pregnancy. This transition is driven by the differentiation of endometrial fibroblasts into specialised decidual cells. A synchronised influx of circulating natural killer (NK) cells and bone marrow-derived mesenchymal stem/progenitor cells (BM-MSC) is pivotal for decidual homeostasis and expansion in early pregnancy. We hypothesise that pathological signals interfering with the recruitment or activity of extrauterine cells at the maternal-fetal interface link miscarriage to subsequent adverse pregnancy outcomes, including further pregnancy losses and preterm labour. NK cells and BM-MSC are key homeostatic regulators in multiple tissues, pointing towards a shared aetiology between recurrent miscarriage and age-related disorders, including cardiometabolic disease. We propose the term 'miscarriage syndrome' to capture the health risks associated with miscarriage and discuss how this paradigm can inform clinical practice and accelerate the development of preventative strategies.

Nucleosome footprinting in plasma cell-free DNA for the pre-surgical diagnosis of ovarian cancer.

Fragmentation patterns of plasma cell-free DNA (cfDNA) are known to reflect nucleosome positions of cell types contributing to cfDNA. Based on cfDNA fragmentation patterns, the deviation in nucleosome footprints was quantified between diagnosed ovarian cancer patients and healthy individuals. Multinomial modeling was subsequently applied to capture these deviations in a per sample nucleosome footprint score. Validation was performed in 271 cfDNAs pre-surgically collected from women with an adnexal mass. We confirmed that nucleosome scores were elevated in invasive carcinoma patients, but not in patients with benign or borderline disease. Combining nucleosome scores with chromosomal instability scores assessed in the same cfDNA improved prediction of malignancy. Nucleosome scores were, however, more reliable to predict non-high-grade serous ovarian tumors, which are characterized by low chromosomal instability. These data highlight that compared to chromosomal instability, nucleosome footprinting provides a complementary and more generic read-out for pre-surgical diagnosis of invasive disease in women with adnexal masses.

Imaging fetal anatomy.

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.