Parillo Marco, Quattrocchi Carlo Cosimo
Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, 38123 Trento, Italy.
Centre for Medical Sciences-CISMed, University of Trento, 38122 Trento, Italy.
J Clin Med. 2025 Jan 5;14(1):263. doi: 10.3390/jcm14010263.
The assessment of lymph node (LN) involvement with clinical imaging is a key factor in cancer staging. Node Reporting and Data System 1.0 (Node-RADS) was introduced in 2021 as a new system specifically tailored for classifying and reporting LNs on computed tomography (CT) and magnetic resonance imaging scans. The aim of this review is to compile the scientific evidence that has emerged since the introduction of Node-RADS, with a specific focus on its diagnostic performance and reliability. Node-RADS's performance has been evaluated in various cancer types and anatomical sites, revealing a trend where higher Node-RADS scores correspond to a greater probability of metastatic LN with better diagnostic performances compared to using short axis diameter alone. Moreover, Node-RADS exhibits encouraging diagnostic value for both Node-RADS ≥ 3 and Node-RADS ≥ 4 cutoffs in predicting metastatic LN. In terms of Node-RADS scoring reliability, preliminary studies show promising but partially conflicting results, with agreement levels, mostly between two readers, ranging from fair to almost perfect. This review highlights a wide variation in methodologies across different studies. Thus, to fully realize the potential of Node-RADS in clinical practice, future studies should comprehensively evaluate its diagnostic accuracy, category-specific malignancy rates, and inter-observer agreement. Finally, although limited, promising evidence has suggested the following: a potential prognostic role for Node-RADS; the possible value of diffusion-weighted imaging for LNs classified as Node-RADS ≥ 3; a correlation between Node-RADS and certain texture features in CT; and improved diagnostic performance when Node-RADS is integrated into radiomics or clinical models.
通过临床影像评估淋巴结（LN）受累情况是癌症分期的关键因素。淋巴结报告与数据系统1.0（Node-RADS）于2021年推出，是专门为在计算机断层扫描（CT）和磁共振成像扫描中对淋巴结进行分类和报告而量身定制的新系统。本综述的目的是汇集自Node-RADS推出以来出现的科学证据，特别关注其诊断性能和可靠性。Node-RADS的性能已在各种癌症类型和解剖部位进行了评估，结果显示与仅使用短轴直径相比，更高的Node-RADS评分对应着转移淋巴结的可能性更大，诊断性能更好。此外，在预测转移淋巴结方面，Node-RADS对Node-RADS≥3和Node-RADS≥4的截断值均具有令人鼓舞的诊断价值。在Node-RADS评分可靠性方面，初步研究显示出有前景但部分相互矛盾的结果，读者间的一致性水平大多在两位读者之间，从一般到几乎完美不等。本综述强调了不同研究之间方法学的广泛差异。因此，为了在临床实践中充分发挥Node-RADS的潜力，未来的研究应全面评估其诊断准确性、特定类别恶性率和观察者间一致性。最后，尽管证据有限，但有前景的证据表明了以下几点：Node-RADS的潜在预后作用；扩散加权成像对分类为Node-RADS≥3的淋巴结的可能价值；Node-RADS与CT中某些纹理特征之间的相关性；以及将Node-RADS整合到放射组学或临床模型中时诊断性能的改善。
