【摘要】 目的基于高分辨率CT影像,建立列线图模型,用于预测直径≤1cm肺纯磨玻璃结节中浸润性肺腺癌的风险。方法回顾性分析2015年11月至2017年7月在宁波市医疗中心李惠利东部医院胸外科行手术切除的直径≤1cm肺纯磨玻璃结节患者的临床病理资料,采用二元logistic回归模型对患者的临床信息及高分辨率CT影像学特征进行单因素及多因素分析,基于独立危险因素建立列线图用于预测浸润性肺腺癌的风险,同时绘制校准曲线,对预测概率与实际概率进行比较。结果共250例患者纳入分析,男63例(25.2%),女187例(74.8%),年龄18～79岁,平均(52.5±11.9)岁,其中良性病灶13例,不典型腺瘤样增生8例,原位腺癌64例,微浸润性腺癌137例,浸润性腺癌28例。单因素及多因素logistic回归分析显示,病灶大小、毛刺征、分叶征、支气管充气征、血管集束征、胸膜凹陷征及CT窗宽是浸润性肺腺癌的独立危险因素。进一步建立列线图发现,病灶直径较大和CT窗宽值较小的患者列线图模型评分较高,而列线图总分越高,相对应的浸润性肺腺癌风险越大。该列线图具有良好的鉴别能力,内部验证及外部验证的ROC曲线下面积分别为0.916和0.970。通过校准曲线进行一致性测试发现,该列线图对浸润性肺腺癌的预测概率与实际观察概率相关性良好。结论建立了一个用于预测直径≤1cm肺纯磨玻璃结节中浸润性肺腺癌风险的列线图模型,该模型具有较高的准确性及鉴别能力,有助于临床医师为每例患者制定较为精确的个性化治疗方案。更多还原

【Abstract】 Objective The pure ground-glass nodule is a common clinical concern. The purpose of this study was to develop a nomogram to predict the risk of invasive pulmonary adenocarcinoma with pure ground-glass nodules≤1 cm in diameter based on the HRCT imaging features. Method We reviewed a total of 250 patients who had undergone resection of pure ground-glass nodules≤1 cm in diameter in our hospital from December 2015 to July 2017, including the data of histopathologic examinations after surgical resection. Clinical information and HRCT imaging features were analyzed by the use of univariable and multivariable binary logistic regression analysis. A nomogram model to predict the risk of invasive pulmonary adenocarcinoma was developed and the calibration curves for the probability were drew. Result Two hundred fifty patients were enrolled for analysis,included 63(25.2%) men and 187(74.8%) women, with age ranging from 18 to 79 years(mean 52.5±11.9 years); 13 as benign lesions, 8 as atypical adenomatous hyperplasia, 64 as adenocarcinoma in situ, 137 as minimally invasive adenocarcinoma, and 28 as invasive adenocarcinoma. On the basis of the final logistic regression analysis, the lesion size, spiculation, lobulation, air bronchogram, vascular convergence, pleural tag and the computed tomography window width were identified for predicting the risk of invasive pulmonary adenocarcinoma and were entered into the nomogram. High scores were added to lesion size and computed tomography window width. A total score could be calculated by adding score of each factor. Higher total score was associated with greater risk of IPA. The nomogram showed an excellent discrimination, with an area under the receiver operating characteristic curve of 0.916 for internal validation and 0.970 for external validation. The calibration curves for the probability of invasive pulmonary adenocarcinoma showed optimal agreement between the predicted probability by the nomogram and the actual probability. Conclusion We constructed a novel nomogram that can predict the risk of invasive pulmonary adenocarcinoma for patients with pure ground-glass nodules≤1 cm in diameter. With highly accurate, excellent calibration and discrimination of the model, clinicians could more precisely make a specific pretreatment strategy for each patient.更多还原