RESUMO
Objectives: The microcystic, elongated and fragmented pattern of invasion can be associated with an underestimation of the depth of myometrial invasion by imaging techniques. We aimed to evaluate the influence of microcystic, elongated and fragmented pattern of invasion in the diagnostic performance of transvaginal ultrasound scan and magnetic resonance imaging for the prediction of the depth of myometrial invasion in low-grade endometrioid endometrial carcinomas. Methods: Prospective and consecutive study including all low-grade (G1-G2) endometrioid endometrial carcinomas diagnosed between October 2013 and July 2018 in a tertiary hospital. Preoperative staging was performed with transvaginal ultrasound scan and/or magnetic resonance imaging followed by surgical staging. Final histology was considered as the reference standard. Sensitivity, specificity and diagnostic accuracy for the prediction of depth of myometrial invasion was calculated for both imaging techniques. The STARD 2015 guidelines were used. Results: A total of 136 patients were consecutively included. Transvaginal ultrasound scan was performed in 132 patients and magnetic resonance imaging in 119 patients. The diagnostic accuracy of transvaginal ultrasound scan for the prediction of depth of myometrial invasion in the microcystic, elongated and fragmented negative group (82% (95% confidence interval = 73-88)) was higher compared to the microcystic, elongated and fragmented positive group (61% (95% confidence interval = 36-83)). The diagnostic accuracy of magnetic resonance imaging was also higher in the microcystic, elongated and fragmented negative group (80% (95% confidence interval = 71-87)) compared to the microcystic, elongated and fragmented positive (47% (95% confidence interval = 21-73)). Conclusions: In low-grade endometrioid endometrial carcinomas with a positive microcystic, elongated and fragmented pattern of invasion, the evaluation of the depth of myometrial invasion using transvaginal ultrasound scan and magnetic resonance imaging may be underestimated.