Context: Endometrial cancer is the third most common malignancy of the female genital tract in the Philippines, following cervical and ovarian cancer. Ultrasound as the first line in imaging has a major role in preoperative treatment and planning. Aims: To compare the diagnostic accuracy of subjective versus objective ultrasound measurement techniques in detecting cervical stromal invasion (CSI) and deep myometrial invasion (MI). Materials and Methods: Fifty‑seven patients were enrolled in this cross‑sectional study. Deep MI and CSI were evaluated both subjectively and objectively by measuring tumor‑free distance (TFD), distance from the outer cervical os to lowest edge of the tumor border (Dist‑OCO), and distance from the internal cervical os to caudal tumor border (Dist‑ICO). Histopathological result used as the gold standard. Results: Subjective assessment for deep (MI) had 79.3% sensitivity, 82.1% specificity, 82.1% positive predictive value (PPV), 82.1% negative predictive value (NPV), and 80.7%. Subjective assessment for CSI had a sensitivity, specificity, PPV, NPV, and overall accuracy of 80%, 90.4%, 44.4%, 97.9%, and 89.5%. Objective measurement (TFD ≤0.8 cm) to detect deep MI had 86.2% sensitivity, 57.1% specificity, 67.4% PPV, 80% NPV, and 71.9% overall accuracy. Adjusting TFD cutoff to 0.65 increased to 71.4% specificity, making it comparable with subjective assessment. Dist‑OCO (≤2.1 cm) yielded 100% sensitivity, 86.3% specificity, 30% PPV, 100% NPV, and 87% overall accuracy. Dist‑ICO was first used in this study, hence no cutoff yet. By using receiver operating characteristics, cutoff was 0.45 cm, which yielded a 60% sensitivity and 92% specificity (area under the curve 0.731, P = 0.09). Conclusions Subjective assessment of CSI and deep MI performs better than objective measurement techniques. TFD and Dist‑OCO as the objective measurements showed clinically comparable accuracy to subjective assessment by an expert. Dist‑ICO needs to be validated to a larger population to determine its clinical value in predicting CSI.
Endometrial Neoplasms