摘要目的 应用影像组学技术分析发生放射性肺炎( RP)的肺癌患者定位及复位CT图像特征参数变化,筛选与RP发生密切相关的指标.方法 选取放疗后经过随访发生2级及以上RP的肺癌患者31例,获取其放疗前的定位CT图像和经过40 Gy放疗后的复位CT图像,将患侧肺和健侧肺设置为提取参数的ROI,在完成正常肺组织自动分割后,使用IBEX软件进行radiomics特征参数的提取,比较这些特征参数在定位和复位CT图像中的差异.结果 (1)每个时段的单侧肺分别提取了86个有效参数指标;(2)放疗前患侧肺和健侧肺差异有统计学意义的参数指标有22个;(3)复位CT中健侧肺和患侧肺差异有统计学意义的参数有12个;(4)患侧肺放疗前后差异有统计学意义的参数有28个;(5)健侧肺放疗前后差异有统计学意义的参数有28个.结论 在发生RP的肺癌患者中,部分CT影像组学特征在定位和复位CT间差异显著,对这些指标动态变化的追踪分析具有预测RP发生的潜在优势.

abstractsObjective To investigate the changes of the parameters related to planning and re-planning CT imaging features in lung cancer patients presenting with radiation pneumonitis ( RP) by using radiomics technique,and identify the parameters intimately related to the incidence of RP. Methods A total of 31 lung cancer patients who were diagnosed with grade ≥ 2 RP after receiving radiation therapy were selected in this study. For each patient, planning CT images before radiation therapy and re-planning CT images after 40 Gy radiation therapy were obtained. The affected and contralateral lungs were considered as the region of interest (ROI).After the automatic segmentation of normal lung tissues,the parameters related to radiomics features were extracted from ROI by using radiomics software. The differences of these parameters between planning and re-planning CT images were statistically compared. Results ( 1 ) For unilateral lung within each time interval,86 parameters related to radiomics features were extracted; ( 2) Twenty-two parameters significantly differed between the affected and contralateral lungs prior to radiotherapy;(3) Twelve parameters significantly differed between the affected and contralateral lungs on re-planning CT images;(4) Twenty-eight parameters significantly differed in the affected lung before and after radiation therapy;(5) Twenty-eight parameters significantly differed in the contralateral lung before and after radiation therapy. Conclusions The CT imaging radiomics features significantly differ between planning and re-planning CT scan in partial lung cancer patients presenting with RP.Monitoring the dynamic changes of these parameters plays a potential role in predicting the incidence of RP.