CONTRIBUTIONWhat are the novel findings of this work? Subjective assessment of ultrasound images is the best method of predicting deep myometrial invasion and cervical stromal invasion of endometrial cancer, especially in patients with a Grade-1 or -2 tumor. To predict high-risk disease, mathematical models may be useful, but the best strategy is to combine subjective assessment with biopsy grade or to use the subjective two-step strategy.
What are the clinical implications of this work?Ultrasound imaging has a central role in the preoperative evaluation of patients with endometrial cancer. In the hands of experienced ultrasound examiners, subjective assessment of extension of endometrial cancer performs better than does any ultrasound measurement or published risk-prediction model.
ABSTRACTObjectives 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 .
MethodsThe 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 116 Verbakel et al.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.
ResultsIn 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 ...