Application of radiomics information captured from PET/CT and CT to predict therapeutic effect of stereotactic ablative radiotherapy in stage Ⅰ non-small cell lung cancer

陈佳艳; 王佳舟; 张军华

doi:10.19401/j.cnki.1007-3639.2017.02.008

您当前的位置：

首页 >

文章列表页 >

Application of radiomics information captured from PET/CT and CT to predict therapeutic effect of stereotactic ablative radiotherapy in stage Ⅰ non-small cell lung cancer

更新时间：2025-12-31

- Application of radiomics information captured from PET/CT and CT to predict therapeutic effect of stereotactic ablative radiotherapy in stage Ⅰ non-small cell lung cancer
- China Oncology Vol. 27, Issue 2, Pages: 128-134(2017)
- 作者机构：
  
  复旦大学附属肿瘤医院放疗科，复旦大学上海医学院肿瘤学系,上海,200032
- 作者简介：
- 基金信息：
- DOI：10.19401/j.cnki.1007-3639.2017.02.008
  CLC：
- Published Online：22 March 2017，
  
  Published：22 March 2017
- 稿件说明：
移动端阅览
陈佳艳,王佳舟,张军华,等. 基于CT或PET/CT的影像组学信息预测Ⅰ期非小细胞肺癌立体定向消融放疗疗效的初步研究[J]. 中国癌症杂志, 2017, 27(2): 128-134.

陈佳艳, 王佳舟, 张军华. Application of radiomics information captured from PET/CT and CT to predict therapeutic effect of stereotactic ablative radiotherapy in stage Ⅰ non-small cell lung cancer[J]. China Oncology, 2017, 27(2): 128-134.
陈佳艳,王佳舟,张军华,等. 基于CT或PET/CT的影像组学信息预测Ⅰ期非小细胞肺癌立体定向消融放疗疗效的初步研究[J]. 中国癌症杂志, 2017, 27(2): 128-134. DOI： 10.19401/j.cnki.1007-3639.2017.02.008.

陈佳艳, 王佳舟, 张军华. Application of radiomics information captured from PET/CT and CT to predict therapeutic effect of stereotactic ablative radiotherapy in stage Ⅰ non-small cell lung cancer[J]. China Oncology, 2017, 27(2): 128-134. DOI： 10.19401/j.cnki.1007-3639.2017.02.008.

摘要

背景与目的：影像组学作为极具潜力的新领域，是指从影像图像中提取有价值的图像特征，并将这些特征数据定量化并转换成可挖掘的数据矿用以指导临床。该回顾性研究应用影像组学的方法初步探索PET/CT对比常规CT在Ⅰ期非小细胞肺癌(non-small cell lung cancer，NSCLC)患者接受立体定向消融放疗(stereotactic ablative radiotherapy，SABR)后疗效预测方面的可行性。方法：回顾性收集经病理证实并在复旦大学附属肿瘤医院行SABR治疗的Ⅰ期NSCLC患者，提取治疗前PET/CT和定位CT图像，由放疗科医师勾画病灶，运用影像组学的方法进行特征值的提取、分析和总结，采用NMF聚类法(non-negative matrix factorization)分析这些特征值是否能够对有无局部进展的患者进行区分，所有统计学算法都在R平台(RDevelopment Core Team)上实现。结果：16例患者纳入最终分析，在PET/CT的影像组学PET特征中发现两个差异有统计学意义的特征值(灰度共生矩阵最大相关系数和灰度游程共生矩阵长行程加重)，可以用以区分患者是否出现局部进展，而在所有定位CT图像提取的特征值中并没有类似发现。结论：在经过SABR治疗后的Ⅰ期NSCLC患者中应用基线PET/CT及胸部定位CT提供的信息进行影像组学分析后，PET/CT似乎能够提供更具统计效能的PET特征值用以预测疗效，对比胸部定位CT提供的信息，PET/CT所提取的特征值可能更敏感、更全面甚至更具特征性。

Abstract

Background and purpose: Radiomics is an emerging field that generates large amounts of valuable clinical information through extracting quantitative imaging features. The purpose of this study was to use the radiomics approach to assess the value of features captured from PET and CT in predicting the therapeutic effect in stage Ⅰ non-small cell lung cancer (NSCLC) after stereotactic ablative radiotherapy (SABR). Methods: Patients with stage Ⅰ NSCLC confirmed by pathology and treated with SABR were included retrospectively. The gross tumor volume (GTV) was defined by two radiologists. PET and CT scan images were collected

and radiomic features were further extracted and analyzed. Non-negative matrix factorization was used to distinguish patients with or without local control. Results: Sixteen patients were eligible for analysis. This study identified two PET features (LL_GLCM_Maximal_Correlation_Coefficient and HL_GLRMS_LRE) captured from PET/CT as having significance in classifying patients with or without disease development. This study not find similar results in CT scans. Conclusion: It seems feasible to use radiomics information effects from PET/CT to predict therapeutic effects of SABR in stage Ⅰ NSCLC. Further investigation is needed.

关键词

Keywords

references

Views

2421

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research progress and prospects of MRI in predicting lymph node status in breast cancer

MRI-based radiomics and deep learning model construction: non-invasive differentiation of molecular subtypes in primary intracranial diffuse large B-cell lymphoma

A cohort study of prognostic value of ¹⁸F-FDG PET/CT metabolic parameters in patients with diffuse large B-cell lymphoma treated with CAR-T

A CT-based radiomics nomogram for predicting local tumor progression of colorectal cancer lung metastases treated with radiofrequency ablation

Important progress in surgical treatment of lung cancer in 2023

Related Author

Zihan ZHAI

Sheng CHEN

Yanwei ZENG

Zhijian XU

Xin CAO

Kun LÜ

Huiming LI

Min GAO

Related Institution

Department of Breast Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University

Department of Radiology, Huashan Hospital, Fudan University

Shanghai Engineering Research Center of Intelligent Imaging for Critical Brain Diseases

Institute of Functional and Molecular Medical Imaging, Fudan University

Academy for Engineering and Technology, Fudan University

AI问答

⁰