Özet:

Aim: There are no studies that have evaluated the accuracy of the finding of myometrial invasion in each modality in predicting adverse prognostic factors and survival. We compared the association of myometrial invasion on MRI and frozen section with presence of adverse prognostic factors and decreased disease-specific survival (DSS) in endometrioid endometrial cance. Material and Methods: A total of 149 patients diagnosed and treated surgically for endometrioid endometrial cancer at a single institution between 2010 and 2017 were included in the study. Accuracies of radiological myometrial invasion and frozen section myometrial invasion in predicting the histopathological myometrial invasion, other adverse prognostic factors and DSS were compared. Results: Frozen section had an accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 89.2%, 100.0%, 84.7%, 72.8% and 100.0%, respectively in diagnosing histopathological deep (≥50%) myometrial invasion with a kappa value of 0.876 (p<0.001). MRI had an accuracy, sensitivity, specificity, PPV and NPV of 71.3%, 55.8%, 80.6%, 63.2%, 75.3%, respectively with a kappa value of 0.392 (p<0.001) in predicting deep myometrial invasion. The accuracy of the finding of deep myometrial invasion on frozen section was higher than the finding of deep myometrial invasion on MRI in predicting the presence of adverse prognostic factors. However, the specificities and NPV’s were higher than their respective sensitivity and PPV values overall for both modalitiesd. Conclusion: Although MRI is frequently used in the preoperative evaluation of patients with endometrial cancer, the finding of deep myometrial invasion on MRI was not as accurate as that of frozen section in predicting the presence of adverse prognostic factors and poor survival. However, both test modalities demonstrated high specificity and NPV. As such both tests may provide higher efficacy in identifying patients without advanced disease who may not require complete lymph node dissection.

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