CASIA OpenIR  > 中国科学院分子影像重点实验室
Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images
Mu, Wei1,2; Chen, Zhe1,2; Liang, Ying3; Shen, Wei1,2; Yang, Feng4; Dai, Ruwei1,2; Wu, Ning3; Tian, Jie1,2
2015-07-07
发表期刊PHYSICS IN MEDICINE AND BIOLOGY
卷号60期号:13页码:5123-5139
文章类型Article
摘要The aim of the study is to assess the staging value of the tumor heterogeneity characterized by texture features and other commonly used semi-quantitative indices extracted from F-18-FDG PET images of cervical cancer (CC) patients. Forty-two patients suffering CC at different stages were enrolled in this study. Firstly, we proposed a new tumor segmentation method by combining the intensity and gradient field information in a level set framework. Secondly, fifty-four 3D texture features were studied besides of SUVs (SUVmax, SUVmean, SUVpeak) and metabolic tumor volume (MTV). Through correlation analysis, receiver-operating-characteristic (ROC) curves analysis, some independent indices showed statistically significant differences between the early stage (ES, stages I and II) and the advanced stage (AS, stages III and IV). Then the tumors represented by those independent indices could be automatically classified into ES and AS, and the most discriminative feature could be chosen. Finally, the robustness of the optimal index with respect to sampling schemes and the quality of the PET images were validated. Using the proposed segmentation method, the dice similarity coefficient and Hausdorff distance were 91.78 +/- 1.66% and 7.94 +/- 1.99 mm, respectively. According to the correlation analysis, all the fifty-eight indices could be divided into 20 groups. Six independent indices were selected for their highest areas under the ROC curves (AUROC), and showed significant differences between ES and AS P < 0.05). Through automatic classification with the support vector machine (SVM) Classifier, run percentage (RP) was the most discriminative index with the higher accuracy (88.10%) and larger AUROC (0.88). The Pearson correlation of RP under different sampling schemes is 0.9991 +/- 0.0011. RP is a highly stable feature and well correlated with tumor stage in CC, which suggests it could differentiate ES and AS with high accuracy.
关键词Cervical Cancer Pet/ct Images Tumor Segmentation Texture Analysis Cancer Staging
WOS标题词Science & Technology ; Technology ; Life Sciences & Biomedicine
关键词[WOS]SUPPORT VECTOR MACHINES ; ACTIVE CONTOURS ; LUNG-CANCER ; QUANTIFICATION ; SEGMENTATION ; RADIOTHERAPY ; ALGORITHM ; VOLUMES ; CT
收录类别SCI
语种英语
WOS研究方向Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000356872000013
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/7902
专题中国科学院分子影像重点实验室
作者单位1.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China
3.Chinese Acad Med Sci, Canc Inst & Hosp, Beijing 100021, Peoples R China
4.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
推荐引用方式
GB/T 7714
Mu, Wei,Chen, Zhe,Liang, Ying,et al. Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images[J]. PHYSICS IN MEDICINE AND BIOLOGY,2015,60(13):5123-5139.
APA Mu, Wei.,Chen, Zhe.,Liang, Ying.,Shen, Wei.,Yang, Feng.,...&Tian, Jie.(2015).Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images.PHYSICS IN MEDICINE AND BIOLOGY,60(13),5123-5139.
MLA Mu, Wei,et al."Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images".PHYSICS IN MEDICINE AND BIOLOGY 60.13(2015):5123-5139.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Staging of cervical (561KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Mu, Wei]的文章
[Chen, Zhe]的文章
[Liang, Ying]的文章
百度学术
百度学术中相似的文章
[Mu, Wei]的文章
[Chen, Zhe]的文章
[Liang, Ying]的文章
必应学术
必应学术中相似的文章
[Mu, Wei]的文章
[Chen, Zhe]的文章
[Liang, Ying]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Staging of cervical cancer based on tumor heterogeneity characterized by texture features on 18F-FDG PET images.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。