Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding.

OBJECTIVE: To describe the ultrasound features of different endometrial and other intracavitary pathologies inpre- and postmenopausal women presenting with abnormal uterine bleeding, using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: This was a prospective observational multicenter study of consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler and fluid-instillation sonography were performed. Endometrial sampling was performed according to each center's local protocol. The histological endpoints were cancer, atypical endometrial hyperplasia/endometrioid intraepithelial neoplasia (EIN), endometrial atrophy, proliferative or secretory endometrium, endometrial hyperplasia without atypia, endometrial polyp, intracavitary leiomyoma and other. For fluid-instillation sonography, the histological endpoints were endometrial polyp, intracavitary leiomyoma and cancer. For each histological endpoint, we report typical ultrasound features using the IETA terminology. RESULTS: The database consisted of 2856 consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler was performed in all cases and fluid-instillation sonography in 1857. In 2216 women, endometrial histology was available, and these comprised the study population. Median age was 49 years (range, 19-92 years), median parity was 2 (range, 0-10) and median body mass index was 24.9 kg/m2 (range, 16.0-72.1 kg/m2 ). Of the study population, 843 (38.0%) women were postmenopausal. Endometrial polyps were diagnosed in 751 (33.9%) women, intracavitary leiomyomas in 223 (10.1%) and endometrial cancer in 137 (6.2%). None (0% (95% CI, 0.0-5.5%)) of the 66 women with endometrial thickness < 3 mm had endometrial cancer or atypical hyperplasia/EIN. Endometrial cancer or atypical hyperplasia/EIN was found in three of 283 (1.1% (95% CI, 0.4-3.1%)) endometria with a three-layer pattern, in three of 459 (0.7% (95% CI, 0.2-1.9%)) endometria with a linear endometrial midline and in five of 337 (1.5% (95% CI, 0.6-3.4%)) cases with a single vessel without branching on unenhanced ultrasound. CONCLUSIONS: The typical ultrasound features of endometrial cancer, polyps, hyperplasia and atrophy and intracavitary leiomyomas, are described using the IETA terminology. The detection of some easy-to-assess IETA features (i.e. endometrial thickness < 3 mm, three-layer pattern, linear midline and single vessel without branching) makes endometrial cancer unlikely. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.

Validation of ultrasound strategies to assess tumor extension and to predict high-risk endometrial cancer in women from the prospective IETA (International Endometrial Tumor Analysis)-4 cohort.

OBJECTIVES: To compare the performance of ultrasound measurements and subjective ultrasound assessment (SA) in detecting deep myometrial invasion (MI) and cervical stromal invasion (CSI) in women with endometrial cancer, overall and according to whether they had low- or high-grade disease separately, and to validate published measurement cut-offs and prediction models to identify MI, CSI and high-risk disease (Grade-3 endometrioid or non-endometrioid cancer and/or deep MI and/or CSI). METHODS: The study comprised 1538 patients with endometrial cancer from the International Endometrial Tumor Analysis (IETA)-4 prospective multicenter study, who underwent standardized expert transvaginal ultrasound examination. SA and ultrasound measurements were used to predict deep MI and CSI. We assessed the diagnostic accuracy of the tumor/uterine anteroposterior (AP) diameter ratio for detecting deep MI and that of the distance from the lower margin of the tumor to the outer cervical os (Dist-OCO) for detecting CSI. We also validated two two-step strategies for the prediction of high-risk cancer; in the first step, biopsy-confirmed Grade-3 endometrioid or mucinous or non-endometrioid cancers were classified as high-risk cancer, while the second step encompassed the application of a mathematical model to classify the remaining tumors. The 'subjective prediction model' included biopsy grade (Grade 1 vs Grade 2) and subjective assessment of deep MI or CSI (presence or absence) as variables, while the 'objective prediction model' included biopsy grade (Grade 1 vs Grade 2) and minimal tumor-free margin. The predictive performance of the two two-step strategies was compared with that of simply classifying patients as high risk if either deep MI or CSI was suspected based on SA or if biopsy showed Grade-3 endometrioid or mucinous or non-endometrioid histotype (i.e. combining SA with biopsy grade). Histological assessment from hysterectomy was considered the reference standard. RESULTS: In 1275 patients with measurable lesions, the sensitivity and specificity of SA for detecting deep MI was 70% and 80%, respectively, in patients with a Grade-1 or -2 endometrioid or mucinous tumor vs 76% and 64% in patients with a Grade-3 endometrioid or mucinous or a non-endometrioid tumor. The corresponding values for the detection of CSI were 51% and 94% vs 50% and 91%. Tumor AP diameter and tumor/uterine AP diameter ratio showed the best performance for predicting deep MI (area under the receiver-operating characteristics curve (AUC) of 0.76 and 0.77, respectively), and Dist-OCO had the best performance for predicting CSI (AUC, 0.72). The proportion of patients classified correctly as having high-risk cancer was 80% when simply combining SA with biopsy grade vs 80% and 74% when using the subjective and objective two-step strategies, respectively. The subjective and objective models had an AUC of 0.76 and 0.75, respectively, when applied to Grade-1 and -2 endometrioid tumors. CONCLUSIONS: In the hands of experienced ultrasound examiners, SA was superior to ultrasound measurements for the prediction of deep MI and CSI of endometrial cancer, especially in patients with a Grade-1 or -2 tumor. The mathematical models for the prediction of high-risk cancer performed as expected. The best strategies for predicting high-risk endometrial cancer were combining SA with biopsy grade and the subjective two-step strategy, both having an accuracy of 80%. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Ultrasound-based risk model for preoperative prediction of lymph-node metastases in women with endometrial cancer: model-development study.

OBJECTIVE: To develop a preoperative risk model, using endometrial biopsy results and clinical and ultrasound variables, to predict the individual risk of lymph-node metastases in women with endometrial cancer. METHODS: A mixed-effects logistic regression model for prediction of lymph-node metastases was developed in 1501 prospectively included women with endometrial cancer undergoing transvaginal ultrasound examination before surgery, from 16 European centers. Missing data, including missing lymph-node status, were imputed. Discrimination, calibration and clinical utility of the model were evaluated using leave-center-out cross validation. The predictive performance of the model was compared with that of risk classification from endometrial biopsy alone (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). RESULTS: Lymphadenectomy was performed in 691 women, of whom 127 had lymph-node metastases. The model for prediction of lymph-node metastases included the predictors age, duration of abnormal bleeding, endometrial biopsy result, tumor extension and tumor size according to ultrasound and undefined tumor with an unmeasurable endometrium. The model's area under the curve was 0.73 (95% CI, 0.68-0.78), the calibration slope was 1.06 (95% CI, 0.79-1.34) and the calibration intercept was 0.06 (95% CI, -0.15 to 0.27). Using a risk threshold for lymph-node metastases of 5% compared with 20%, the model had, respectively, a sensitivity of 98% vs 48% and specificity of 11% vs 80%. The model had higher sensitivity and specificity than did classification as high-risk, according to endometrial biopsy alone (50% vs 35% and 80% vs 77%, respectively) or combined endometrial biopsy and ultrasound (80% vs 75% and 53% vs 52%, respectively). The model's clinical utility was higher than that of endometrial biopsy alone or combined endometrial biopsy and ultrasound at any given risk threshold. CONCLUSIONS: Based on endometrial biopsy results and clinical and ultrasound characteristics, the individual risk of lymph-node metastases in women with endometrial cancer can be estimated reliably before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Clinical Reliability of point-of-care tests to support community based acute ambulatory care.

OBJECTIVE: To ensure clinicians can rely on point-of-care testing results, we assessed agreement between point-of-care tests for creatinine, urea, sodium, potassium, calcium, Hb, INR, CRP and subsequent corresponding laboratory tests. PARTICIPANTS: Community-dwelling adults referred to a community-based acute ambulatory care unit. INTERVENTIONS: The Abbott i-STATTM (Hb, clinical chemistry, INR) and the AfinionTM Analyser (CRP) and corresponding laboratory analyses. OUTCOMES: Agreement (Bland-Altman) and bias (Passing-Bablok regression). RESULTS: Among 462 adults we found an absolute mean difference between point-of-care and central laboratory analyses of 6.4g/L (95%LOA -7.9 to +20.6) for haemoglobin, -0.5mmol/L (95%LOA -4.5 to +3.5) for sodium, 0.2mmol/L (95%LOA -0.6 to +0.9) for potassium, 0.0mmol/L (95%LOA -0.3 to +0.3) for calcium, 9.0 µmol/L (95%LOA -18.5 to +36.4) for creatinine, 0.0mmol/L (95%LOA -2.7 to +2.6) for urea, -0.2 (95%LOA -2.4 to +2.0) for INR, -5.0 mg/L (95%LOA -24.4 to +14.4) for CRP. CONCLUSIONS: There was acceptable agreement and bias for these analytes, except for haemoglobin and creatinine.

Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta-analysis.

BACKGROUND: There is no international consensus on how to manage women with a pregnancy of unknown location (PUL). OBJECTIVES: To present a systematic quantitative review summarising the evidence related to management protocols for PUL. SEARCH STRATEGY: MEDLINE, COCHRANE and DARE databases were searched from 1 January 1984 to 31 January 2017. The primary outcome was accurate risk prediction of women initially diagnosed with a PUL having an ectopic pregnancy (high risk) as opposed to either a failed PUL or intrauterine pregnancy (low risk). SELECTION CRITERIA: All studies written in the English language, which were not case reports or series that assessed women classified as having a PUL at initial ultrasound. DATA COLLECTION AND ANALYSIS: Forty-three studies were included. QUADAS-2 criteria were used to assess the risk of bias. We used a novel, linear mixed-effects model and constructed summary receiver operating characteristic curves for the thresholds of interest. MAIN RESULTS: There was a high risk of differential verification bias in most studies. Meta-analyses of accuracy were performed on (i) single human chorionic gonadotrophin (hCG) cut-off levels, (ii) hCG ratio (hCG at 48 hours/initial hCG), (iii) single progesterone cut-off levels and (iv) the 'M4 model' (a logistic regression model based on the initial hCG and hCG ratio). For predicting an ectopic pregnancy, the areas under the curves (95% CI) for these four management protocols were as follows: (i) 0.42 (0.00-0.99), (ii) 0.69 (0.57-0.78), (iii) 0.69 (0.54-0.81) and (iv) 0.87 (0.83-0.91), respectively. CONCLUSIONS: The M4 model was the best available method for predicting a final outcome of ectopic pregnancy. Developing and validating risk prediction models may optimise the management of PUL. TWEETABLE ABSTRACT: Pregnancy of unknown location meta-analysis: M4 model has best test performance to predict ectopic pregnancy.

Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study.

OBJECTIVE: To describe the sonographic features of endometrial cancer in relation to tumor stage, grade and histological type, using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: This was a prospective multicenter study of 1714 women with biopsy-confirmed endometrial cancer undergoing standardized transvaginal grayscale and Doppler ultrasound examination according to the IETA study protocol, by experienced ultrasound examiners using high-end ultrasound equipment. Clinical and sonographic data were entered into a web-based database. We assessed how strongly sonographic characteristics, according to IETA, were associated with outcome at hysterectomy, i.e. tumor stage, grade and histological type, using univariable logistic regression and the c-statistic. RESULTS: In total, 1538 women were included in the final analysis. Median age was 65 (range, 27-98) years, median body mass index was 28.4 (range 16-67) kg/m2 , 1377 (89.5%) women were postmenopausal and 1296 (84.3%) reported abnormal vaginal bleeding. Grayscale and color Doppler features varied according to grade and stage of tumor. High-risk tumors, compared with low-risk tumors, were less likely to have regular endometrial-myometrial junction (difference of -23%; 95% CI, -27 to -18%), were larger (mean endometrial thickness; difference of +9%; 95% CI, +8 to +11%), and were more likely to have non-uniform echogenicity (difference of +7%; 95% CI, +1 to +13%), a multiple, multifocal vessel pattern (difference of +21%; 95% CI, +16 to +26%) and a moderate or high color score (difference of +22%; 95% CI, +18 to +27%). CONCLUSION: Grayscale and color Doppler sonographic features are associated with grade and stage of tumor, and differ between high- and low-risk endometrial cancer. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Subjective assessment versus ultrasound models to diagnose ovarian cancer: A systematic review and meta-analysis.

INTRODUCTION: Many national guidelines concerning the management of ovarian cancer currently advocate the risk of malignancy index (RMI) to characterise ovarian pathology. However, other methods, such as subjective assessment, International Ovarian Tumour Analysis (IOTA) simple ultrasound-based rules (simple rules) and IOTA logistic regression model 2 (LR2) seem to be superior to the RMI. Our objective was to compare the diagnostic accuracy of subjective assessment, simple rules, LR2 and RMI for differentiating benign from malignant adnexal masses prior to surgery. MATERIALS AND METHODS: MEDLINE, EMBASE and CENTRAL were searched (January 1990-August 2015). Eligibility criteria were prospective diagnostic studies designed to preoperatively predict ovarian cancer in women with an adnexal mass. RESULTS: We analysed 47 articles, enrolling 19,674 adnexal tumours; 13,953 (70.9%) benign and 5721 (29.1%) malignant. Subjective assessment by experts performed best with a pooled sensitivity of 0.93 (95% confidence interval [CI] 0.92-0.95) and specificity of 0.89 (95% CI 0.86-0.92). Simple rules (classifying inconclusives as malignant) (sensitivity 0.93 [95% CI 0.91-0.95] and specificity 0.80 [95% CI 0.77-0.82]) and LR2 (sensitivity 0.93 [95% CI 0.89-0.95] and specificity 0.84 [95% CI 0.78-0.89]) outperformed RMI (sensitivity 0.75 [95% CI 0.72-0.79], specificity 0.92 [95% CI 0.88-0.94]). A two-step strategy using simple rules, when inconclusive added by subjective assessment, matched test performance of subjective assessment by expert examiners (sensitivity 0.91 [95% CI 0.89-0.93] and specificity 0.91 [95% CI 0.87-0.94]). CONCLUSIONS: A two-step strategy of simple rules with subjective assessment for inconclusive tumours yielded best results and matched test performance of expert ultrasound examiners. The LR2 model can be used as an alternative if an expert is not available.