PDF(Pubmed)
Abstract：
UNASSIGNED: The Node Reporting and Data System (Node-RADS) is a recently proposed classification system for the categorization of lymph nodes in radiological images. This study was conducted to retrospectively evaluate the diagnostic accuracy of the Node-RADS score for metastatic cervical lymph nodes on magnetic resonance imaging (MRI) of patients with nasopharyngeal carcinoma (NPC).
UNASSIGNED: We retrospectively analyzed cervical lymph nodes of NPC cases. Two radiologists independently evaluated each lymph node on the MRI scans using Node-RADS. Interobserver agreement between 2 radiologists for Node-RADS score assessment was evaluated by linear weighted kappa statistics. The correlation between metastasis and the Node-RADS score of each lymph node was analyzed using multivariate regression analysis. To investigate the diagnostic performance of the Node-RADS score, we further conducted receiver operating characteristic curve analysis. Correspondently, the sensitivity, specificity, positive predictive value, and negative predictive value of each different cutoff (>1, >2, >3, and >4) were computed.
UNASSIGNED: In all, 119 patients with NPC were assessed, including 203 cervical lymph nodes consisting of 140 (69%) of 203 metastatic and 63 (31%) of 203 benign. The kappa agreement between the 2 readers for the Node-RADS score was 0.863 (95% CI = 0.830-0.897, P < .001). Node-RADS score on MRI scan was shown to be an independent predictive factor of lymph node metastasis after multivariate regression analysis (odds ratio [OR] = 6.745, 95% CI = 3.964-11.474, P < .001). Node-RADS achieved an area under the curve (AUC) of 0.950 (95% CI = 0.921-0.979) in diagnosing metastatic lymph nodes. When Node-RADS >2 was identified as the best cutoff based on balanced values, the sensitivity and positive predictive value were 0.92 and 0.94, respectively.
UNASSIGNED: Our study suggests that the Node-RADS score has high accuracy in predicting NPC cervical lymph node metastasis. Nevertheless, this conclusion requires confirmation in a larger cohort of patients with NPC.
UNASSIGNED: We retrospectively analyzed cervical lymph nodes of NPC cases. Two radiologists independently evaluated each lymph node on the MRI scans using Node-RADS. Interobserver agreement between 2 radiologists for Node-RADS score assessment was evaluated by linear weighted kappa statistics. The correlation between metastasis and the Node-RADS score of each lymph node was analyzed using multivariate regression analysis. To investigate the diagnostic performance of the Node-RADS score, we further conducted receiver operating characteristic curve analysis. Correspondently, the sensitivity, specificity, positive predictive value, and negative predictive value of each different cutoff (>1, >2, >3, and >4) were computed.
UNASSIGNED: In all, 119 patients with NPC were assessed, including 203 cervical lymph nodes consisting of 140 (69%) of 203 metastatic and 63 (31%) of 203 benign. The kappa agreement between the 2 readers for the Node-RADS score was 0.863 (95% CI = 0.830-0.897, P < .001). Node-RADS score on MRI scan was shown to be an independent predictive factor of lymph node metastasis after multivariate regression analysis (odds ratio [OR] = 6.745, 95% CI = 3.964-11.474, P < .001). Node-RADS achieved an area under the curve (AUC) of 0.950 (95% CI = 0.921-0.979) in diagnosing metastatic lymph nodes. When Node-RADS >2 was identified as the best cutoff based on balanced values, the sensitivity and positive predictive value were 0.92 and 0.94, respectively.
UNASSIGNED: Our study suggests that the Node-RADS score has high accuracy in predicting NPC cervical lymph node metastasis. Nevertheless, this conclusion requires confirmation in a larger cohort of patients with NPC.
摘要：
■节点报告和数据系统（Node-RADS）是最近提出的用于对放射学图像中的淋巴结进行分类的分类系统。这项研究旨在回顾性评估Node-RADS评分对鼻咽癌（NPC）患者磁共振成像（MRI）转移性颈淋巴结的诊断准确性。
■我们回顾性分析了鼻咽癌的颈部淋巴结。两名放射科医生使用Node-RADS独立评估MRI扫描中的每个淋巴结。通过线性加权kappa统计量评估了2位放射科医师对Node-RADS评分评估的观察者之间的一致性。采用多因素回归分析淋巴结转移与各淋巴结的Node-RADS评分的相关性。要调查Node-RADS评分的诊断性能，我们进一步进行了接收器工作特性曲线分析。相应地,灵敏度,特异性，正预测值，并计算每个不同截止值(>1、>2、>3和>4)的阴性预测值。
■总之，对119例鼻咽癌患者进行了评估，包括203个颈部淋巴结，包括203个转移性淋巴结中的140个（69％）和203个良性淋巴结中的63个（31％）。2位读者对Node-RADS评分的kappa一致性为0.863（95%CI=0.830-0.897，P<.001）。多因素回归分析显示MRI扫描的Node-RADS评分是淋巴结转移的独立预测因素(比值比[OR]=6.745,95%CI=3.964-11.474,P<.001)。在诊断转移性淋巴结时，Node-RADS的曲线下面积（AUC）为0.950（95％CI=0.921-0.979）。当Node-RADS>2被确定为基于平衡值的最佳截止值时，敏感性和阳性预测值分别为0.92和0.94.
■我们的研究表明，Node-RADS评分在预测NPC颈淋巴结转移方面具有很高的准确性。然而，这一结论需要在更大的NPC患者队列中得到证实.
■我们回顾性分析了鼻咽癌的颈部淋巴结。两名放射科医生使用Node-RADS独立评估MRI扫描中的每个淋巴结。通过线性加权kappa统计量评估了2位放射科医师对Node-RADS评分评估的观察者之间的一致性。采用多因素回归分析淋巴结转移与各淋巴结的Node-RADS评分的相关性。要调查Node-RADS评分的诊断性能，我们进一步进行了接收器工作特性曲线分析。相应地,灵敏度,特异性，正预测值，并计算每个不同截止值(>1、>2、>3和>4)的阴性预测值。
■总之，对119例鼻咽癌患者进行了评估，包括203个颈部淋巴结，包括203个转移性淋巴结中的140个（69％）和203个良性淋巴结中的63个（31％）。2位读者对Node-RADS评分的kappa一致性为0.863（95%CI=0.830-0.897，P<.001）。多因素回归分析显示MRI扫描的Node-RADS评分是淋巴结转移的独立预测因素(比值比[OR]=6.745,95%CI=3.964-11.474,P<.001)。在诊断转移性淋巴结时，Node-RADS的曲线下面积（AUC）为0.950（95％CI=0.921-0.979）。当Node-RADS>2被确定为基于平衡值的最佳截止值时，敏感性和阳性预测值分别为0.92和0.94.
■我们的研究表明，Node-RADS评分在预测NPC颈淋巴结转移方面具有很高的准确性。然而，这一结论需要在更大的NPC患者队列中得到证实.
