[Three Dimensional Volumetric Analysis of Solid Pulmonary Nodules on Chest CT: Cancer Risk Assessment]

Zhongguo Fei Ai Za Zhi. 2016 May 20;19(5):279-85. doi: 10.3779/j.issn.1009-3419.2016.05.05.
[Article in Chinese]

Abstract

Background: The management of pulmonary nodules relies on cancer risk assessment, in which the only widely accepted criterion is diameter. The development of volumetric computed tomography (CT) and three-dimensional (3D) software enhances the clarity in displaying the nodules' characteristics. This study evaluated the values of the nodules' volume and 3D morphological characteristics (edge, shape and location) in cancer risk assessment.

Methods: The CT data of 200 pulmonary nodules were retrospectively evaluated using 3D volumetric software. The malignancy or benignity of all the nodules was confirmed by pathology, histology or follow up (>2 years). Logistic regression analysis was performed to calculate the odds ratios (ORs) of the 3D margin (smooth, lobulated or spiculated/irregular), shape (spherical or non-spherical), location (purely intraparenchymal, juxtavascular or pleural-attached), and nodule volume in cancer risk assessment for total and sub-centimeter nodules. The receiver operating characteristic (ROC) curve was employed to determine the optimal threshold for the nodule volume.

Results: Out of 200 pulmonary nodules, 78 were malignant, whereas 122 were benign. The Logistic regression analysis showed that the volume (OR=3.3; P<0.001) and the 3D margin (OR=13.4, 9.8; both P=0.001) were independent predictive factors of malignancy, whereas the location and 3D shape exhibited no total predictive value (P>0.05). ROC analysis showed that the optimal threshold for malignancy was 666 mm³. For sub-centimeter nodules, the 3D margin was the only valuable predictive factor of malignancy (OR=60.5, 75.0; P=0.003, 0.007).

Conclusions: The volume and 3D margin are important factors considered to assess the cancer risk of pulmonary nodules. Volumes larger than 666 mm³ can be determined as high risk for pulmonary nodules; by contrast, nodules with lobulated, spiculated, or irregular margin present a high malignancy probability.

背景与目的 肺结节临床处理策略主要基于其恶性风险度评估,目前公认的计算机断层扫描(computed tomography, CT)影像学标准为结节直径。容积CT及三维分析软件的应用使肺结节形态学特征显示更加清晰。本研究的目的是评估肺结节的容积及三维形态特征(边缘、形状、位置)在结节恶性风险度评估中的价值。方法 应用三维分析软件对200例直径小于3 cm实性结节的CT影像资料进行回顾性分析,恶性结节经病理或组织学确认,良性结节经病理或两年随访无增大确认。对全部结节及亚厘米结节(直径小于10 mm)分别采用Logistic回归分析计算结节三维边缘(光滑、分叶、毛刺或不规则)、形状(球体、非球体)、位置(肺实质内、血管相贴、胸膜相贴)、结节容积的似然比(odds ratios, ORs),并通过受试者工作特征(receiver operating characteristic, ROC)曲线确定结节容积评估恶性风险度的最佳阈值。结果 纳入研究的200例中恶性78例,良性122例。对全部结节的Logistic回归分析结果显示结节容积(OR=3.3, P<0.001)、边缘形态(分叶、毛刺或不规则的OR值分别为13.4、9.8,P均=0.001)具有预测价值,而结节的位置及三维形状不具备预测价值(P>0.05)。ROC分析显示结节容积对恶性风险度评估有价值(曲线下面积为0.928;P<0.01,最佳阈值为666 mm3)。对亚厘米结节的分析显示仅边缘分叶、毛刺或不规则的结节恶性风险度高(OR=60.5, 75.0; P=0.003, 0.007)。结论 结节的三维容积及边缘形态有助于判定结节的恶性风险度,容积大于666 mm3可作为恶性高危结节的阈值;边缘分叶、毛刺或不规则是亚厘米结节的唯一高危因素。.

MeSH terms

  • Aged
  • Humans
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / diagnostic imaging
  • Lung Neoplasms / mortality
  • Male
  • Middle Aged
  • ROC Curve
  • Retrospective Studies
  • Risk Assessment
  • Solitary Pulmonary Nodule / diagnosis*
  • Solitary Pulmonary Nodule / diagnostic imaging
  • Solitary Pulmonary Nodule / mortality
  • Tomography, X-Ray Computed

Grants and funding

本研究受国家自然科学基金面上项目(No.81171345)、中央补助地方公共卫生专项资金肺癌早诊早治项目和2012年高等学校博士学科点专项科研基金(No.20121202110005)资助