CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer
CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer
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DOI：
10.1016/j.radonc.2016.05.024
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发表时间：
2016-08-01
影响因子：
5.7
通讯作者：
Aerts, Hugo J. W. L.
中科院分区：
文献类型：
--
作者：
Huynh, Elizabeth;Coroller, Thibaud P.;Aerts, Hugo J. W. L.
背景：放射组学使用大量描述肿瘤表型的定量成像特征来开发临床结果的成像生物标记物。为探讨立体定向全身放射治疗(SBRT)治疗早期非小细胞肺癌(NSCLC)患者临床预后的影像指标，对治疗前CT扫描进行放射学分析。材料与方法：对113例接受SBRT治疗的I-II期非小细胞肺癌患者的CT影像进行分析。根据稳定性和方差性选择了12个放射学特征。评估这些特征与临床结果及其预后价值的相关性(使用一致性指数(CI))。结果：总生存率与两个常规影像特征(体积和直径)和两个放射学特征(LOG 3D RUN、低灰度级、短程重点和STATS中位数)相关。有一个放射学特征(小波L1H统计范围)对远处转移有显著的预测作用(CI=0.67，Q值0.1)，而常规和临床参数均不能预测远处转移。3个常规影像特征和4个放射学特征对总体生存有预测作用。结论：本探索性分析表明，对于常规影像指标无法预测SBRT患者预后的某些结果，放射学特征具有潜在的预测作用。(C)2016爱思唯尔爱尔兰有限公司。保留所有权利。
Background: Radiomics uses a large number of quantitative imaging features that describe the tumor phenotype to develop imaging biomarkers for clinical outcomes. Radiomic analysis of pre-treatment computed-tomography (CT) scans was investigated to identify imaging predictors of clinical outcomes in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT).Materials and methods: CT images of 113 stage I-II NSCLC patients treated with SBRT were analyzed. Twelve radiomic features were selected based on stability and variance. The association of features with clinical outcomes and their prognostic value (using the concordance index (CI)) was evaluated. Radiomic features were compared with conventional imaging metrics (tumor volume and diameter) and clinical parameters.Results: Overall survival was associated with two conventional features (volume and diameter) and two radiomic features (LoG 3D run low gray level short run emphasis and stats median). One radiomic feature (Wavelet LLH stats range) was significantly prognostic for distant metastasis (CI = 0.67, q-value < 0.1), while none of the conventional and clinical parameters were. Three conventional and four radiomic features were prognostic for overall survival.Conclusion: This exploratory analysis demonstrates that radiomic features have potential to be prognostic for some outcomes that conventional imaging metrics cannot predict in SBRT patients. (C) 2016 Elsevier Ireland Ltd. All rights reserved.