M. A. Pascual

Prospective geographical and temporal validation of three published mathematical models to calculate risk of endometrial malignancy in patients with postmenopausal bleeding

The Risk of Endometrial Malignancy and Other Endometrial Pathology in Women with Abnormal Uterine Bleeding: An Ultrasound-Based Model Development Study by the IETA Group

<b><i>Objectives:</i></b> The aim of this study was to develop a model that can discriminate between different etiologies of abnormal uterine bleeding. <b><i>Design:</i></b> The International Endometrial Tumor Analysis 1 study is a multicenter observational diagnostic study in 18 bleeding clinics in 9 countries. Consecutive women with abnormal vaginal bleeding presenting for ultrasound examination (<i>n</i> = 2,417) were recruited. The histology was obtained from endometrial sampling, D&C, hysteroscopic resection, hysterectomy, or ultrasound follow-up for >1 year. <b><i>Methods:</i></b> A model was developed using multinomial regression based on age, body mass index, and ultrasound predictors to distinguish between: (1) endometrial atrophy, (2) endometrial polyp or intracavitary myoma, (3) endometrial malignancy or atypical hyperplasia, (4) proliferative/secretory changes, endometritis, or hyperplasia without atypia and validated using leave-center-out cross-validation and bootstrapping. The main outcomes are the model’s ability to discriminate between the four outcomes and the calibration of risk estimates. <b><i>Results:</i></b> The median age in 2,417 women was 50 (interquartile range 43–57). 414 (17%) women had endometrial atrophy; 996 (41%) had a polyp or myoma; 155 (6%) had an endometrial malignancy or atypical hyperplasia; and 852 (35%) had proliferative/secretory changes, endometritis, or hyperplasia without atypia. The model distinguished well between malignant and benign histology (<i>c</i>-statistic 0.88 95% CI: 0.85–0.91) and between all benign histologies. The probabilities for each of the four outcomes were over- or underestimated depending on the centers. <b><i>Limitations:</i></b> Not all patients had a diagnosis based on histology. The model over- or underestimated the risk for certain outcomes in some centers, indicating local recalibration is advisable. <b><i>Conclusions:</i></b> The proposed model reliably distinguishes between four histological outcomes. This is the first model to discriminate between several outcomes and is the only model applicable when menopausal status is uncertain. The model could be useful for patient management and counseling, and aid in the interpretation of ultrasound findings. Future research is needed to externally validate and locally recalibrate the model.

Preoperative Assessment of Cervical Involvement in Endometrial Cancer by Transvaginal Ultrasound and Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Abstract Objective To compare the diagnostic accuracy of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) for detecting cervical infiltration by endometrial carcinoma using meta-analysis assessment. Methods An extensive search of papers comparing TVS and MRI for assessing cervical infiltration in endometrial cancer in the same set of patients was performed in Medline (Pubmed), Web of Science, and the Cochrane Database. Quality was assessed using QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies-2). Quantitative meta-analysis was performed. Results Our extended search identified 12 articles that used both techniques in the same set of patients and were included in the meta-analysis. The risk of bias for most studies was high for patient selection and index tests in QUADAS-2. Overall, the pooled estimated sensitivity and specificity for diagnosing cervical infiltration in women with endometrial cancer were identical for both techniques [69 % (95 % CI, 51 %–82 %) and 93 % (95 % CI, 90 %–95 %) for TVS, and 69 % (95 % CI, 57 %–79 %) and 91 % (95 % CI, 90 %–95 %) for MRI, respectively]. No statistical differences were found when comparing both methods. Heterogeneity was high for sensitivity and moderate for specificity when analyzing TVS and moderate for both sensitivity and specificity in the case of MRI. Conclusion TVS and MRI showed very similar diagnostic performance for diagnosing cervical involvement in women with endometrial cancer.

Two‐dimensional transvaginal sonography vs saline contrast sonohysterography for diagnosing endometrial polyps: systematic review and meta‐analysis

ABSTRACTObjectiveTo compare the diagnostic performance of two‐dimensional transvaginal sonography (TVS) and saline contrast sonohysterography (SCSH) for the diagnosis of endometrial polyps in studies that used both tests in the same group of patients.MethodsThis was a systematic review and meta‐analysis. An extensive search was conducted of Medline (PubMed), Cochrane Library and Web of Science, for studies comparing the diagnostic performance of TVS and SCSH for identifying endometrial polyps, published between January 1990 and December 2019, that reported a definition of endometrial polyp on TVS and SCSH and used pathologic analysis as the reference standard. Quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool. A random‐effects model was used to determine pooled sensitivity, specificity and positive and negative likelihood ratios of TVS and SCSH in the detection of endometrial polyps. Subanalysis according to menopausal status was performed.ResultsIn total, 1278 citations were identified; after exclusions, 25 studies were included in the meta‐analysis. In the included studies, the risk of bias evaluated using QUADAS‐2 was low for most of the four domains, except for flow and timing, which had an unclear risk of bias in 13 studies. Pooled sensitivity, specificity and positive and negative likelihood ratios for TVS in the detection of endometrial polyps were 55.0% (95% CI, 46.0–64.0%), 91.0% (95% CI, 86.0–94.0%), 5.8 (95% CI, 3.9–8.7) and 0.5 (95% CI, 0.41–0.61), respectively. The corresponding values for SCSH were 92.0% (95% CI, 87.0–95.0%), 93.0% (95% CI, 91.0–95.0%), 13.9 (95% CI, 9.9–19.5) and 0.08 (95% CI, 0.05–0.14), respectively. Significant differences were found when comparing the methods in terms of sensitivity (P < 0.001), but not for specificity (P = 0.0918). Heterogeneity was high for TVS and moderate for SCSH. On subanalysis according to menopausal status, SCSH was found to have higher diagnostic accuracy in both pre‐ and postmenopausal women; sensitivity and specificity did not differ significantly between the groups for either TVS or SCSH.ConclusionGiven that SCSH has better diagnostic positive and negative likelihood ratios than does TVS in both pre‐ and postmenopausal women, those with clinical suspicion of endometrial polyps should undergo SCSH if TVS findings are inconclusive. © 2020 International Society of Ultrasound in Obstetrics and Gynecology

Validation of ADNEX and IOTA two‐step strategy and estimation of risk of complications during follow‐up of adnexal masses in low‐risk population

ABSTRACTObjectivesTo evaluate the ability of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and the International Ovarian Tumour Analysis (IOTA) two‐step strategy to predict malignancy in adnexal masses detected in an outpatient low‐risk setting, and to estimate the risk of complications in masses with benign ultrasound morphology managed using clinical and ultrasound follow‐up.MethodsThis single‐center study was performed at Hospital Universitari Dexeus, Barcelona, Spain, using interim data from the ongoing prospective observational IOTA Phase‐5 (IOTA5) study. The primary aim of the IOTA5 study is to describe the cumulative incidence of complications during follow‐up of adnexal masses classified as benign on ultrasound examination. Consecutive patients with an adnexal mass detected between June 2012 and September 2016 in a private center offering screening for gynecological cancer were included and followed up until February 2020. Tumors were classified as benign or malignant based on histology (if patients underwent surgery) or the outcome of clinical and ultrasound follow‐up at 12 (range, 10–14) months. Multiple imputation was used when outcomes were uncertain. The ability of the ADNEX model without CA125 and of the IOTA two‐step strategy to distinguish benign from malignant masses was evaluated retrospectively using the prospectively collected data. We assessed performance with regard to discrimination (area under the receiver‐operating‐characteristics curve (AUC)), calibration, classification (sensitivity and specificity) and clinical utility (Net Benefit). In the group of patients with a mass judged to be benign who were selected for conservative management, we evaluated the occurrence of spontaneous resolution or any mass complication during the first 5 years of follow‐up by assessing the cumulative incidence of malignancy, torsion, cyst rupture and minor mass complications (inflammation, infection or adhesions) and the time to occurrence of an event.ResultsA total of 2654 patients were recruited to the study. After application of exclusion criteria, 2039 patients with a newly detected mass were included for the model validation. Of those, 1684 (83%) masses were benign, 49 (2%) masses were malignant and, for 306 (15%) masses, the outcome was uncertain and therefore imputed. The AUC was 0.95 (95% CI, 0.89–0.98) for ADNEX without CA125 and 0.94 (95% CI, 0.88–0.97) for the two‐step strategy. Calibration performance could not be meaningfully interpreted because the small number of malignancies resulted in very wide confidence intervals. The two‐step strategy had better clinical utility than did the ADNEX model at malignancy risk thresholds < 3%. There were 1472 (72%) patients whose mass was judged to be benign based on pattern recognition by an experienced ultrasound examiner and were managed with clinical and ultrasound follow‐up. In this group, the 5‐year cumulative incidence was 66% (95% CI, 63–69%) for spontaneous resolution of the mass, 0% (95% CI, 0–0.2%) for torsion, 0.1% (95% CI, < 0.1–0.4%) for cyst rupture, 0.2% (95% CI, 0.1–0.6%) for a borderline tumor and 0.2% (95% CI, 0.1–0.6%) for invasive malignancy.ConclusionsThe ADNEX model and IOTA two‐step strategy performed well to distinguish benign from malignant adnexal masses detected in a low‐risk population. Conservative management is safe for masses with a benign ultrasound appearance in this population. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Vessel morphology depicted by three‐dimensional power Doppler ultrasound as second‐stage test in adnexal tumors that are difficult to classify: prospective diagnostic accuracy study

ABSTRACTObjectivesTo assess whether vessel morphology depicted by three‐dimensional (3D) power Doppler ultrasound improves discrimination between benignity and malignancy if used as a second‐stage test in adnexal masses that are difficult to classify.MethodsThis was a prospective observational international multicenter diagnostic accuracy study. Consecutive patients with an adnexal mass underwent standardized transvaginal two‐dimensional (2D) grayscale and color or power Doppler and 3D power Doppler ultrasound examination by an experienced examiner, and those with a ‘difficult’ tumor were included in the current analysis. A difficult tumor was defined as one in which the International Ovarian Tumor Analysis (IOTA) logistic regression model‐1 (LR‐1) yielded an ambiguous result (risk of malignancy, 8.3% to 25.5%), or as one in which the ultrasound examiner was uncertain regarding classification as benign or malignant when using subjective assessment. Even when the ultrasound examiner was uncertain, he/she was obliged to classify the tumor as most probably benign or most probably malignant. For each difficult tumor, one researcher created a 360° rotating 3D power Doppler image of the vessel tree in the whole tumor and another of the vessel tree in a 5‐cm3 spherical volume selected from the most vascularized part of the tumor. Two other researchers, blinded to the patient's history, 2D ultrasound findings and histological diagnosis, independently described the vessel tree using predetermined vessel features. Their agreed classification was used. The reference standard was the histological diagnosis of the mass. The sensitivity of each test for discriminating between benign and malignant difficult tumors was plotted against 1 – specificity on a receiver‐operating‐characteristics diagram, and the test with the point furthest from the reference line was considered to have the best diagnostic ability.ResultsOf 2403 women with an adnexal mass, 376 (16%) had a difficult mass. Ultrasound volumes were available for 138 of these cases. In 79/138 masses, the ultrasound examiner was uncertain about the diagnosis based on subjective assessment, in 87/138, IOTA LR‐1 yielded an ambiguous result and, in 28/138, both methods gave an uncertain result. Of the masses, 38/138 (28%) were malignant. Among tumors that were difficult to classify as benign or malignant by subjective assessment, the vessel feature ‘densely packed vessels’ had the best discriminative ability (sensitivity 67% (18/27), specificity 83% (43/52)) and was slightly superior to subjective assessment (sensitivity 74% (20/27), specificity 60% (31/52)). In tumors in which IOTA LR‐1 yielded an ambiguous result, subjective assessment (sensitivity 82% (14/17), specificity 79% (55/70)) was superior to the best vascular feature, i.e. changes in the diameter of vessels in the whole tumor volume (sensitivity 71% (12/17), specificity 69% (48/70)).ConclusionVessel morphology depicted by 3D power Doppler ultrasound may slightly improve discrimination between benign and malignant adnexal tumors that are difficult to classify by subjective ultrasound assessment. For tumors in which the IOTA LR‐1 model yields an ambiguous result, subjective assessment is superior to vessel morphology as a second‐stage test. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Imaging in gynecological disease (17): ultrasound features of malignant ovarian yolk sac tumors (endodermal sinus tumors)

ABSTRACTObjectiveTo describe the clinical and sonographic characteristics of malignant ovarian yolk sac tumors (YSTs).MethodsIn this retrospective multicenter study, we included 21 patients with a histological diagnosis of ovarian YST and available transvaginal ultrasound images and/or videoclips and/or a detailed ultrasound report. Ten patients identified from the International Ovarian Tumor Analysis (IOTA) studies had undergone a standardized preoperative ultrasound examination, by an experienced ultrasound examiner, between 1999 and 2016. A further 11 patients were identified through medical files, for whom ultrasound images were retrieved from local image workstations and picture archiving and communication systems. All tumors were described using IOTA terminology. The collected ultrasound images and videoclips were used by two observers for additional characterization of the tumors.ResultsAll cases were pure YSTs, except for one that was a mixed tumor (80% YST and 20% embryonal carcinoma). Median age at diagnosis was 25 (interquartile range (IQR), 19.5–30.5) years. Seventy‐six percent (16/21) of women had an International Federation of Gynecology and Obstetrics (FIGO) Stage I–II tumor at diagnosis. Fifty‐eight percent (11/19) of women felt pain during the ultrasound examination and one presented with ovarian torsion. Median serum α‐fetoprotein (S‐AFP) level was 4755 (IQR, 1071–25 303) µg/L and median serum CA 125 level was 126 (IQR, 35–227) kU/L. On ultrasound assessment, 95% (20/21) of tumors were unilateral. The median maximum tumor diameter was 157 (IQR, 107–181) mm and the largest solid component was 110 (IQR, 66–159) mm. Tumors were classified as either multilocular‐solid (10/21; 48%) or solid (11/21; 52%). Papillary projections were found in 10% (2/21) of cases. Most (20/21; 95%) tumors were well vascularized (color score, 3–4) and none had acoustic shadowing. Malignancy was suspected in all cases, except in the patient with ovarian torsion, who presented a tumor with a color score of 1, which was classified as probably benign. Image and videoclip quality was considered as adequate in 18/21 cases. On review of the images and videoclips, we found that all tumors contained both solid components and cystic spaces, and that 89% (16/18) had irregular, still fine‐textured and slightly hyperechoic solid tissue, giving them a characteristic appearance.ConclusionMalignant ovarian YSTs are often detected at an early stage, in young women usually in the second or third decade of life, presenting with pain and markedly elevated S‐AFP. On ultrasound, malignant ovarian YSTs are mostly unilateral, large and multilocular‐solid or solid, with fine‐textured slightly hyperechoic solid tissue and rich vascularization. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology..

International multicenter validation of AI-driven ultrasound detection of ovarian cancer

Abstract Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Deep learning has shown promising results in the detection of ovarian cancer in ultrasound images; however, external validation is lacking. In this international multicenter retrospective study, we developed and validated transformer-based neural network models using a comprehensive dataset of 17,119 ultrasound images from 3,652 patients across 20 centers in eight countries. Using a leave-one-center-out cross-validation scheme, for each center in turn, we trained a model using data from the remaining centers. The models demonstrated robust performance across centers, ultrasound systems, histological diagnoses and patient age groups, significantly outperforming both expert and non-expert examiners on all evaluated metrics, namely F1 score, sensitivity, specificity, accuracy, Cohen’s kappa, Matthew’s correlation coefficient, diagnostic odds ratio and Youden’s J statistic. Furthermore, in a retrospective triage simulation, artificial intelligence (AI)-driven diagnostic support reduced referrals to experts by 63% while significantly surpassing the diagnostic performance of the current practice. These results show that transformer-based models exhibit strong generalization and above human expert-level diagnostic accuracy, with the potential to alleviate the shortage of expert ultrasound examiners and improve patient outcomes.

Estimating risk of endometrial malignancy and other intracavitary uterine pathology in women without abnormal uterine bleeding using IETA‐1 multinomial regression model: validation study

ABSTRACTObjectivesTo assess the ability of the International Endometrial Tumor Analysis (IETA)‐1 polynomial regression model to estimate the risk of endometrial cancer (EC) and other intracavitary uterine pathology in women without abnormal uterine bleeding.MethodsThis was a retrospective study, in which we validated the IETA‐1 model on the IETA‐3 study cohort (n = 1745). The IETA‐3 study is a prospective observational multicenter study. It includes women without vaginal bleeding who underwent a standardized transvaginal ultrasound examination in one of seven ultrasound centers between January 2011 and December 2018. The ultrasonography was performed either as part of a routine gynecological examination, during follow‐up of non‐endometrial pathology, in the work‐up before fertility treatment or before treatment for uterine prolapse or ovarian pathology. Ultrasonographic findings were described using IETA terminology and were compared with histology, or with results of clinical and ultrasound follow‐up of at least 1 year if endometrial sampling was not performed. The IETA‐1 model, which was created using data from patients with abnormal uterine bleeding, predicts four histological outcomes: (1) EC or endometrial intraepithelial neoplasia (EIN); (2) endometrial polyp or intracavitary myoma; (3) proliferative or secretory endometrium, endometritis, or endometrial hyperplasia without atypia; and (4) endometrial atrophy. The predictors in the model are age, body mass index and seven ultrasound variables (visibility of the endometrium, endometrial thickness, color score, cysts in the endometrium, non‐uniform echogenicity of the endometrium, presence of a bright edge, presence of a single dominant vessel). We analyzed the discriminative ability of the model (area under the receiver‐operating‐characteristics curve (AUC); polytomous discrimination index (PDI)) and evaluated calibration of its risk estimates (observed/expected ratio).ResultsThe median age of the women in the IETA‐3 cohort was 51 (range, 20–85) years and 51% (887/1745) of the women were postmenopausal. Histology showed EC or EIN in 29 (2%) women, endometrial polyps or intracavitary myomas in 1094 (63%), proliferative or secretory endometrium, endometritis, or hyperplasia without atypia in 144 (8%) and endometrial atrophy in 265 (15%) women. The endometrial sample had insufficient material in five (0.3%) cases. In 208 (12%) women who did not undergo endometrial sampling but were followed up for at least 1 year without clinical or ultrasound signs of endometrial malignancy, the outcome was classified as benign. The IETA‐1 model had an AUC of 0.81 (95% CI, 0.73–0.89, n = 1745) for discrimination between malignant (EC or EIN) and benign endometrium, and the observed/expected ratio for EC or EIN was 0.51 (95% CI, 0.32–0.82). The model was able to categorize the four histological outcomes with considerable accuracy: the PDI of the model was 0.68 (95% CI, 0.62–0.73) (n = 1532). The IETA‐1 model discriminated very well between endometrial atrophy and all other intracavitary uterine conditions, with an AUC of 0.96 (95% CI, 0.95–0.98). Including only patients in whom the endometrium was measurable (n = 1689), the model's AUC was 0.83 (95% CI, 0.75–0.91), compared with 0.62 (95% CI, 0.52–0.73) when using endometrial thickness alone to predict malignancy (difference in AUC, 0.21; 95% CI, 0.08–0.32). In postmenopausal women with measurable endometrial thickness (n = 848), the IETA‐1 model gave an AUC of 0.81 (95% CI, 0.71–0.91), while endometrial thickness alone gave an AUC of 0.70 (95% CI, 0.60–0.81) (difference in AUC, 0.11; 95% CI, 0.01–0.20).ConclusionThe IETA‐1 model discriminates well between benign and malignant conditions in the uterine cavity in patients without abnormal bleeding, but it overestimates the risk of malignancy. It also discriminates well between the four histological outcome categories. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

International Ovarian Tumour Analysis (IOTA) Phase 5

The purpose of this study is to learn more about the appearance and behavior of benign-looking adnexal masses. * Benign-looking means that when viewed here by ultrasound it has the appearance of looking not harmful or not malignant. * Adnexal refers to the 'adnexa', the space in the female pelvis on either side of the uterus (or where the uterus used to be if you previously had a hysterectomy). The adnexa includes, but is not limited to, the ovaries and the fallopian tubes. * Masses refers to a variety of structures, including but not limited to: * ovarian cysts that are fluid filled sacs within or attached to an ovary * ovarian tumors that can be solid tissue or a combination of cysts and solid tissue * hydrosalpinges that are fluid collections in the fallopian tube Many women have what appear to be benign adnexal masses. Many times, removal of the masses with surgery is not necessary. Often surgery is performed unnecessarily, for fear that these masses could be cancer. There is not much information available for doctors to know how and when to follow these masses, or which ones will become cancer. This study will combine information from centers all around the world regarding the behavior of all types of benign adnexal masses. The aim of this study is to develop decision tools for doctors to know the best way to treat these masses in order to improve the detection of ovarian cancer while at the same time reduce the number of unnecessary operations.