Node-RADS 1.0 for lymph node involvement detection in renal cell carcinoma: A study on 2D and 3D CT imaging

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Renal cell carcinoma (RCC) is a common malignancy.
• Accurate assessment of lymph node involvement (LNI) is crucial for RCC staging and treatment planning.
• The Node-RADS (Node, Reporting and Data System) score is a standardized system for evaluating lymph nodes on imaging.

Purpose of the Study:

• To evaluate the diagnostic accuracy of the Node-RADS 1.0 score in predicting LNI in RCC patients.
• To compare the diagnostic performance of the Node-RADS score using two-dimensional (2D) and three-dimensional (3D) imaging modalities.

Main Methods:

• Retrospective analysis of 375 RCC patients with confirmed lymph node status.
• Preoperative abdomen CT imaging was assessed by three independent readers using the Node-RADS score (2D and 3D).
• Sensitivity, specificity, AUC, and inter-reader agreement were calculated, with histology serving as the gold standard.

Main Results:

• Node-RADS score ≥ 3 demonstrated high diagnostic accuracy with an AUC of 0.901 on 2D imaging.
• The diagnostic performance of Node-RADS on 2D and 3D modalities was comparable (p=0.651).
• Excellent inter-reader agreement was observed for both 2D and 3D Node-RADS assessments (Kendall's W 0.889 and 0.869).

Conclusions:

• The Node-RADS score is a reliable tool for identifying LNI in RCC patients.
• Node-RADS assessment using 2D and 3D imaging offers similar diagnostic performance.
• This standardized scoring system can aid in the accurate staging of RCC.