From the Department of Radiology (M.S.C.), Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea.
Departments of Radiology and Research Institute of Radiology (Y.J.C., J.H.L., J.H.B.)
AJNR Am J Neuroradiol. 2019 Jun;40(6):1049-1054. doi: 10.3174/ajnr.A6066. Epub 2019 May 9.
An accurate and comprehensive assessment of lymph node metastasis in patients with head and neck squamous cell cancer is crucial in daily practice. This study constructed a predictive model with a risk scoring system based on CT characteristics of lymph nodes and tumors for patients with head and neck squamous cell carcinoma to stratify the risk of lymph node metastasis.
Data included 476 cervical lymph nodes from 191 patients with head and neck squamous cell carcinoma from a historical cohort. We analyzed preoperative CT images of lymph nodes, including diameter, ratio of long-to-short axis diameter, necrosis, conglomeration, infiltration to adjacent soft tissue, laterality and T-stage of the primary tumor. The reference standard comprised pathologic results. Multivariable logistic regression analysis was performed to develop the risk scoring system. Internal validation was performed with 1000-iteration bootstrapping.
Shortest axial diameter, ratio of long-to-short axis diameter, necrosis, and T-stage were used to develop a 9-point risk scoring system. The risk of malignancy ranged from 7.3% to 99.8%, which was positively associated with increased scores. Areas under the curve of the risk scoring systems were 0.886 (95% CI, 0.881-0.920) and 0.879 (95% CI, 0.845-0.914) in internal validation. The Hosmer-Lemeshow goodness-of-fit test indicated that the risk scoring system was well-calibrated ( = .160).
We developed a comprehensive and simple risk scoring system using CT characteristics in patients with head and neck squamous cell carcinoma to stratify the risk of lymph node metastasis. It could facilitate decision-making in daily practice.
对头颈鳞状细胞癌患者进行准确全面的淋巴结转移评估在日常实践中至关重要。本研究基于头颈部鳞状细胞癌患者淋巴结和肿瘤的 CT 特征构建了一个预测模型和风险评分系统,以对淋巴结转移风险进行分层。
纳入了来自历史队列的 191 例头颈部鳞状细胞癌患者的 476 个颈部淋巴结数据。分析了淋巴结的术前 CT 图像,包括直径、长径与短径的比值、坏死、融合、浸润相邻软组织、偏侧性和原发肿瘤的 T 分期。参考标准为病理结果。采用多变量逻辑回归分析建立风险评分系统。通过 1000 次迭代的自举法进行内部验证。
最短轴向直径、长径与短径的比值、坏死和 T 分期用于开发 9 分风险评分系统。恶性风险从 7.3%到 99.8%不等,与评分的增加呈正相关。风险评分系统在内部验证中的曲线下面积分别为 0.886(95%CI,0.881-0.920)和 0.879(95%CI,0.845-0.914)。Hosmer-Lemeshow 拟合优度检验表明风险评分系统具有良好的校准度( =.160)。
我们使用头颈部鳞状细胞癌患者的 CT 特征开发了一种全面而简单的风险评分系统,以对淋巴结转移风险进行分层。它可以为日常实践中的决策提供便利。