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

OBJECTIVES: To describe the sonographic features of endometrial cancer in relation to stage, grade, and histological type using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: Prospective multicenter study on 1714 women with endometrial cancer undergoing a standardized transvaginal grayscale and Doppler ultrasound examination by an experienced ultrasound examiner using a high-end ultrasound system. Clinical and sonographic data were entered into a web-based protocol. We assessed how strongly sonographic characteristics, according to IETA, were associated to outcome at hysterectomy, i.e. tumor stage, grade, and histological type. RESULTS: After excluding 176 women (no or delayed hysterectomy, final diagnosis other than endometrial cancer, or incomplete data), 1538 women were included in our statistical analysis. Median age was 65 years (range 27-98), and median BMI 28.4 (range 16-67), 1378 (89.7%) women were postmenopausal, and 1296 (84.2%) reported abnormal vaginal bleeding. Grayscale and color Doppler features varied according to grade and stage. High-risk tumors (stage 1A, grade 3 or non-endometrioid or ≥ stage 1B) were less likely to have regular endometrial myometrial border (difference of -23%, 95% CI -27 to -18%), whilst they were larger (mean endometrial thickness; difference of +9 mm, 95% CI +8 to +11 mm), more frequently had non-uniform echogenicity (difference of +10%, 95% CI +5 to +15%), 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%), than low-risk tumors. CONCLUSION: Grayscale and color Doppler ultrasound features are associated with grade and stage, and differ between high and low risk endometrial cancer

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

Objectives: To validate prospectively five mathematical models published in 2007 for calculating the risk of endometrial malignancy in a defined high-risk group of patients with postmenopausal bleeding and sonographic endometrial thickness≥4.5mm. Methods: Of 1012 consecutive patients, 379 fulfilled our inclusion criteria, which were the same as those of the original study in which the models were created (endometrial thickness≥4.5mm, no fluid in the uterine cavity, detectable Doppler signals in the endometrium). A standardized history was taken, and clinical and transvaginal grayscale and power Doppler ultrasound examinations were performed following the study protocol. All data were collected prospectively and the five models were applied prospectively to the study patients' data to assess their risk of endometrial malignancy. Using the histological diagnosis of the endometrium as gold standard, we calculated the area under the receiver-operating characteristics curve (AUC), and sensitivity, specificity and likelihood ratios when using the same cut-offs as in the original study, for each of the five models. Results: Ninety-three (25%) patients had malignant endometrium. The performance of the models was similar to that in the original study, with AUCs ranging from 0.86 to 0.90. The model with the best diagnostic performance included endometrial thickness, heterogeneous endometrial echogenicity and areas of densely packed vessels on power Doppler (AUC, 0.90; sensitivity, 81%; specificity, 84% at preselected cut-off). The models were well calibrated. Conclusions: On temporal validation, the five models for calculating the risk of endometrial malignancy in a defined high-risk group of patients retained their good diagnostic performance and were well calibrated. The models make it possible to reclassify high-risk patients as having a low or relatively low risk, moderately high risk or very high risk of endometrial cancer, and so can be used for individualized patient management

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.status: publishe

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.status: publishe

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

An ultrasound-based risk model to predict lymph node metastases before surgery in women with endometrial cancer: a model development study.

OBJECTIVES: To develop a pre-operative risk model using endometrial biopsy results, 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 was developed on 1501 prospectively included women with endometrial cancer subjected to transvaginal ultrasound examination before surgery. Missing data, including missing lymph node status, was imputed. Discrimination, calibration and clinical utility were evaluated using leave-center-out cross-validation. The predictive performance was compared with risk classification from endometrial biopsy alone (high-risk = endometrioid cancer grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk = endometrioid cancer grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). RESULTS: Lymphadenectomy was performed in 691 women, of which 127 had lymph node metastases. The model 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 AUC was 0.73 (95% CI 0.68 to 0.78), calibration slope 1.06 (95% CI 0.79 to 1.34) and calibration intercept 0.06 (95% CI 0.15 to 0.27). Using risk thresholds for lymph node metastases 5% vs. 20% the model had sensitivity 98% vs. 48% and specificity 11% vs. 80%. The model had higher sensitivity and specificity than high-risk according to endometrial biopsy alone (50% vs. 35% and 80% vs. 77%) or combined endometrial biopsy and ultrasound (80% vs. 75% and 53% vs. 52%). 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, clinical and ultrasound characteristics, the individual risk of lymph node metastases in women with endometrial cancer can be reliably estimated before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound. This article is protected by copyright. All rights reserved