Computer-aided Volumetry of Part-Solid Lung Cancers by Using CT: Solid Component Size Predicts Prognosis
Computer-aided Volumetry of Part-Solid Lung Cancers by Using CT: Solid Component Size Predicts Prognosis
复制标题
DOI：
10.1148/radiol.2018172319
复制
发表时间：
2018-06-01
期刊：
影响因子：
19.7
通讯作者：
Naganawa, Shinji
中科院分区：
文献类型：
--
作者：
Kamiya, Shinichiro;Iwano, Shingo;Naganawa, Shinji
目的：探讨部分实性非小细胞肺癌患者的术后预后与使用三维（3D）容积软件在多探测器计算机断层扫描（CT）图像上获得的实体成分大小之间的关系。材料与方法：回顾性研究，使用术前多层螺旋CT数据与0.5毫米层厚，临床记录和病理报告的96例原发性亚固体非小细胞肺癌（47名男性和49名女性，平均年龄6标准差，66岁6 8）进行了审查。两名放射科医师测量每个结节在轴向图像上的二维（2D）最大实体尺寸（以下称为2D MSSA）、在多平面重建图像上的3D最大实体尺寸（以下称为3D MSSMPR）以及每个结节内大于0 HU的3D实体体积（以下称为3D SV 0 HU）。采用考克斯比例风险模型分析术后复发与临床病理特征、2D MSSA、3D MSSMPR和3D SV（OHU）的相关性（95%置信区间：0.692，0.900），3D MSSMPR为0.776（95%置信区间：0.667，0.886），3D SV（OHU）为0.835（95%置信区间：0.749，0.922）。3D SV（OHU）预测肿瘤复发的最佳截止值为0.54 cm（3），复发的敏感性为0.933（95%置信区间：0.679，0.998），特异性为0.716（95%置信区间：0.605，0.811）。无病生存的重要预测因素是3D SV（OHU）大于或等于0.54 cm（3）（风险比，6.61; P =.001）和淋巴和/或血管浸润来自组织病理学分析（风险比，2.96; P =.040）。3D SV（OHU）测量预测部分实性肺癌患者术后预后的准确性高于2D MSSA和3D MSSMPR。(C)RSNA，2018
Purpose: To investigate the relationship between the postoperative prognosis of patients with part-solid non-small cell lung cancer and the solid component size acquired by using three-dimensional (3D) volumetry software on multidetector computed tomographic (CT) images. Materials andMethods: A retrospective study by using preoperative multidetector CT data with 0.5-mm section thickness, clinical records, and pathologic reports of 96 patients with primary subsolid non-small cell lung cancer (47 men and 49 women; mean age 6 standard deviation, 66 years 6 8) were reviewed. Two radiologists measured the two-dimensional (2D) maximal solid size of each nodule on an axial image (hereafter, 2D MSSA), the 3D maximal solid size on multiplanar reconstructed images (hereafter, 3D MSSMPR), and the 3D solid volume of greater than 0 HU (hereafter, 3D SV 0HU) within each nodule. The correlations between the postoperative recurrence and the effects of clinical and pathologic characteristics, 2D MSSA, 3D MSSMPR, and 3D SV (OHU) as prognostic imaging biomarkers were assessed by using a Cox proportional hazards model.Results: For the prediction of postoperative recurrence, the area under the receiver operating characteristics curve was 0.796 (95% confidence interval: 0.692, 0.900) for 2D MSSA, 0.776 (95% confidence interval: 0.667, 0.886) for 3D MSSMPR, and 0.835 (95% confidence interval: 0.749, 0.922) for 3D SV (OHU). The optimal cutoff value for 3D SV (OHU) for predicting tumor recurrence was 0.54 cm(3), with a sensitivity of 0.933 (95% confidence interval: 0.679, 0.998) and a specificity of 0.716 (95% confidence interval: 0.605, 0.811) for the recurrence. Significant predictive factors for disease-free survival were 3D SV (OHU) greater than or equal to 0.54 cm(3) (hazard ratio, 6.61; P =.001) and lymphatic and/or vascular invasion derived from histopathologic analysis (hazard ratio, 2.96; P =.040).Conclusion: The measurement of 3D SV (OHU) predicted the postoperative prognosis of patients with part-solid lung cancer more accurately than did 2D MSSA and 3D MSSMPR. (C) RSNA, 2018