• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Contrast media & molecular imaging >Radiomic Profiling of Head and Neck Cancer: 18F-FDG PET Texture Analysis as Predictor of Patient Survival
【24h】

Radiomic Profiling of Head and Neck Cancer: 18F-FDG PET Texture Analysis as Predictor of Patient Survival

机译：头颈癌的放射学特征分析：18F-FDG PET纹理分析可预测患者生存率

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background and Purpose. The accurate prediction of prognosis and pattern of failure is crucial for optimizing treatment strategies for patients with cancer, and early evidence suggests that image texture analysis has great potential in predicting outcome both in terms of local control and treatment toxicity. The aim of this study was to assess the value of pretreatment 18F-FDG PET texture analysis for the prediction of treatment failure in primary head and neck squamous cell carcinoma (HNSCC) treated with concurrent chemoradiation therapy. Methods. We performed a retrospective analysis of 90 patients diagnosed with primary HNSCC treated between January 2010 and June 2017 with concurrent chemo-radiotherapy. All patients underwent 18F-FDG PET/CT before treatment. 18F-FDG PET/CT texture features of the whole primary tumor were measured using an open-source texture analysis package. Least absolute shrinkage and selection operator (LASSO) was employed to select the features that are associated the most with clinical outcome, as progression-free survival and overall survival. We performed a univariate and multivariate analysis between all the relevant texture parameters and local failure, adjusting for age, sex, smoking, primary tumor site, and primary tumor stage. Harrell c-index was employed to score the predictive power of the multivariate cox regression models. Results. Twenty patients (22.2%) developed local failure, whereas the remaining 70 (77.8%) achieved durable local control. Multivariate analysis revealed that one feature, defined as low-intensity long-run emphasis (LILRE), was a significant predictor of outcome regardless of clinical variables (hazard ratio??0.001, ).The multivariate model based on imaging biomarkers resulted superior in predicting local failure with a c-index of 0.76 against 0.65 of the model based on clinical variables alone. Conclusion. LILRE, evaluated on pretreatment 18F-FDG PET/CT, is associated with higher local failure in patients with HNSCC treated with chemoradiotherapy. Using texture analysis in addition to clinical variables may be useful in predicting local control.
机译：背景和目的。准确预测预后和失败模式对于优化癌症患者的治疗策略至关重要，早期证据表明，图像纹理分析在预测局部控制和治疗毒性方面都具有巨大潜力。这项研究的目的是评估预处理18F-FDG PET质地分析对于同时进行化学放射治疗的原发性头颈部鳞状细胞癌（HNSCC）的治疗失败预测的价值。方法。我们对2010年1月至2017年6月间同时进行化学放疗的90例诊断为原发性HNSCC的患者进行了回顾性分析。所有患者在治疗前均接受了18F-FDG PET / CT。使用开源纹理分析工具包测量整个原发肿瘤的18F-FDG PET / CT纹理特征。采用最小绝对收缩和选择算子（LASSO）来选择与临床结局最相关的特征，如无进展生存期和总生存期。我们在所有相关的纹理参数和局部衰竭之间进行了单因素和多因素分析，并针对年龄，性别，吸烟，原发肿瘤部位和原发肿瘤阶段进行了调整。使用Harrell c指数对多元Cox回归模型的预测能力进行评分。结果。 20例患者（22.2％）发生局部衰竭，而其余70例（77.8％）实现了持久的局部控制。多元分析显示，无论临床变量如何，低强度长期强调（LILRE）都是预测结局的重要指标（危险比≤0.001）。仅根据临床变量预测模型的c指数为0.76而不是0.65的局部失败。结论。经预处理的18F-FDG PET / CT评估的LILRE与接受放化疗的HNSCC患者较高的局部衰竭率相关。除临床变量外，还使用纹理分析可能有助于预测局部控制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号