Related Experiment Video
Updated: Oct 9, 2026
Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
Published on: August 19, 2021
Diagnostic value of Node-RADS in predicting lymph node metastasis in endometrial cancer
Fatemeh Shakki Katouli1, Fahimeh Zeinalkhani2, Mohammad Hossein Hashemi3
1Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran; Department of Radiology, Arash Women Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Purpose:
Accurate assessment of lymph node (LN) status is essential for staging of endometrial cancer (EC). This study evaluated the diagnostic performance of the Node Reporting and Data System (Node-RADS) in predicting pelvic LN metastasis in EC using preoperative MRI.
Methods:
In this retrospective study, patients with pathologically confirmed EC who underwent preoperative pelvic MRI between June 2020 and September 2025 were included. Node-RADS scores were assigned independently by two gynecologic radiologists in consensus and were correlated with surgical pathology. Diagnostic performance was assessed using receiver operating characteristic analysis. Area under the curve (AUC) values were compared using the DeLong test. Logistic regression was applied to identify independent predictors of LN metastasis.
Results:
Among 169 lymph nodes in 72 patients, 21 (12.4%) were metastatic. Metastatic nodes demonstrated significantly higher Node-RADS scores and larger short-axis diameters (p < 0.05). Node-RADS was the strongest predictor of metastatic involvement (OR = 264, 95% CI: 16-41,330; p < 0.0001). Tumor ADC values independently correlated with nodal metastasis (OR = 0.984, 95% CI: 0.966-0.996; p = 0.005). Node-RADS demonstrated excellent diagnostic accuracy (AUC = 0.963; 95% CI: 0.910-1.000), significantly outperforming size-based assessment (AUC = 0.851; p = 0.0029). Using a cutoff of Node-RADS ≥ 3 yielded optimal performance, with a sensitivity of 85.7% and specificity of 98.0%. Increasing the cutoff to ≥ 4 achieved perfect specificity (100%) at the cost of reduced sensitivity (47.6%).
Conclusion:
MRI-based Node-RADS is a robust and highly accurate tool for predicting pelvic LN metastasis in EC, outperforming conventional size criteria and providing strong independent diagnostic value.
