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Diagnostic and prognostic value of MRI-based Node-RADS for the assessment of regional lymph node metastasis in renal cell carcinoma - 28/03/25

Doi : 10.1016/j.diii.2024.10.005 
Xu Bai a, b, Cheng Peng c, Baichuan Liu a, Shaopeng Zhou a, Haili Liu d, Yijian Chen a, Huiping Guo a, Yuwei Hao a, Xin Liu e, Jian Zhao f, Xiaohui Ding g, Lin Li h, Xu Zhang c, Huiyi Ye a, Xin Ma c, Haiyi Wang a,
a Department of Radiology, First Medical Center, Chinese PLA General Hospital, Haidian District, Beijing 100853, China 
b Department of Radiology, Fifth Medical Center, Chinese PLA General Hospital, Beijing 100039, China 
c Department of Urology, First Medical Center, Chinese PLA General Hospital, Haidian District, Beijing 100853, China 
d Department of Radiology, Fourth Medical Center, Chinese PLA General Hospital, Haidian District, Beijing 100048, China 
e Department of Radiology, Chinese PLA 920 Hospital, Xishan District, Kunming 650118, China 
f Department of Radiology, Armed Police Force Hospital of Sichuan, Leshan, Sichuan 614000, China 
g Department of Pathology, First Medical Center, Chinese PLA General Hospital, Haidian District, Beijing 100853, China 
h Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Haidian District, Beijing 100853, China 

Corresponding author.

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Highlight

MRI-based Node-RADS outperforms size criteria for lymph node involvement in renal cell carcinoma.
MRI-based Node-RADS shows substantial interobserver agreement among three readers.
MRI-based Node-RADS shows potential prognostic capabilities for renal cell carcinoma.

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Abstract

Purpose

The purpose of this study was to assess the capabilities of MRI-based Node Reporting and Data System (Node-RADS) in diagnosing regional lymph node metastasis (RLNM) and to estimate its prognostic significance in patients with renal cell carcinomas (RCCs).

Materials and methods

Patients with RCC who underwent nephrectomy and regional lymph node dissection between January 2010 and August 2023 were retrospectively included. Two senior radiologists scored lymph nodes in consensus using MRI-based Node-RADS. The performance of MRI-based Node-RADS for the diagnosis of RLNM was estimated using area under receiver operating characteristic (AUC) curves and compared against size criteria. Three additional readers scored all lesions to assess interobserver agreement. Progression-free survival and overall survival were estimated and compared between patients with low (1–3) and high (4–5) scores.

Results

Overall, 216 patients with RCC were enrolled, including 58 with RLNM. There were 157 men and 59 women with a median age of 54 years (range: 8–83 years). Node-RADS showed larger AUC (0.93 [95 % confidence interval (CI): 0.87–0.97]) and higher specificity (96.8 % [95 % CI: 92.8–99.0]) compared to size criteria (0.88 [95 % CI: 0.83–0.94] and 87.3 % [95 % CI: 81.1–92.1], respectively) for the diagnosis of RLNM ( P = 0.039 and P < 0.001, respectively). Substantial interobserver agreement in Node-RADS scoring was obtained between the three readers (weighted κ, 0.75 [95 % CI: 0.69–0.80]). During a median follow-up of 56 months, patients with high Node-RADS score experienced poorer progression-free survival ( P < 0.001) and overall survival ( P < 0.001) than those with low Node-RADS score. At multivariable Cox regression analysis, Node-RADS was an independent variable associated with RCC prognosis after adjustment for confounders.

Conclusions

The MRI-based Node-RADS demonstrates notable performance in detecting RLNM and showed potential prognostic significance for RCCs.

El texto completo de este artículo está disponible en PDF.

Keywords : Lymphatic metastasis, Magnetic resonance imaging, Node Reporting and Data System (Node-RADS), Prognosis, Renal cell carcinoma

Abbreviations : AUC, CI, CT, HR, MRI, Node-RADS, OS, PFS, RCC, RLN, RLNM, ROC, SI


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