CASIA OpenIR
Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule
Fan, Li1; Fang, MengJie2,3; Li, ZhaoBin4; Tu, WenTing1; Wang, ShengPing5; Chen, WuFei6; Tian, Jie2,3; Dong, Di2,3; Liu, ShiYuan1
Source PublicationEUROPEAN RADIOLOGY
ISSN0938-7994
2019-02-01
Volume29Issue:2Pages:889-897
Corresponding AuthorDong, Di(di.dong@ia.ac.cn) ; Liu, ShiYuan(lsy0930@163.com)
AbstractObjectivesTo identify the radiomics signature allowing preoperative discrimination of lung invasive adenocarcinomas from non-invasive lesions manifesting as ground-glass nodules.MethodsThis retrospective primary cohort study included 160 pathologically confirmed lung adenocarcinomas. Radiomics features were extracted from preoperative non-contrast CT images to build a radiomics signature. The predictive performance and calibration of the radiomics signature were evaluated using intra-cross (n=76), external non-contrast-enhanced CT (n=75) and contrast-enhanced CT (n=84) validation cohorts. The performance of radiomics signature and CT morphological and quantitative indices were compared.Results355 three-dimensional radiomics features were extracted, and two features were identified as the best discriminators to build a radiomics signature. The radiomics signature showed a good ability to discriminate between invasive adenocarcinomas and non-invasive lesions with an accuracy of 86.3%, 90.8%, 84.0% and 88.1%, respectively, in the primary and validation cohorts. It remained an independent predictor after adjusting for traditional preoperative factors (odds ratio 1.87, p < 0.001) and demonstrated good calibration in all cohorts. It was a better independent predictor than CT morphology or mean CT value.ConclusionsThe radiomics signature showed good predictive performance in discriminating between invasive adenocarcinomas and non-invasive lesions. Being a non-invasive biomarker, it could assist in determining therapeutic strategies for lung adenocarcinoma.Key Points center dot The radiomics signature was a non-invasive biomarker of lung invasive adenocarcinoma.center dot The radiomics signature outweighed CT morphological and quantitative indices.center dot A three-centre study showed that radiomics signature had good predictive performance.
KeywordLung Adenocarcinoma Tomography x-ray computed Computational biology Solitary pulmonary nodule
DOI10.1007/s00330-018-5530-z
WOS KeywordCOMPUTED-TOMOGRAPHY ; IASLC/ATS/ERS CLASSIFICATION ; INTERNATIONAL-ASSOCIATION ; MULTIDETECTOR CT ; OPACITY NODULES ; PREDICT ; LESIONS ; CHEST ; SIZE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[81370035] ; National Natural Science Foundation of China[81230030] ; National Natural Science Foundation of China[81771924] ; National Key R&D Program of China[2016YFE0103000] ; National Key R&D Program of China[2017YFC1308703] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFC1308700] ; Shanghai Pujiang Talent Program[15PJD002]
Funding OrganizationNational Natural Science Foundation of China ; National Key R&D Program of China ; Shanghai Pujiang Talent Program
WOS Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000454706500043
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25646
Collection中国科学院自动化研究所
Corresponding AuthorDong, Di; Liu, ShiYuan
Affiliation1.Second Mil Med Univ, Changzheng Hosp, Dept Radiol, 415 Fengyang Rd, Shanghai 200003, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
4.Shanghai Jiao Tong Univ, Peoples Hosp 6, Dept Radiat Oncol, Shanghai 200233, Peoples R China
5.Fudan Univ, Dept Radiol, Shanghai Canc Ctr, Shanghai 200032, Peoples R China
6.Fudan Univ, Dept Radiol, Huadong Hosp, Shanghai 200040, Peoples R China
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Fan, Li,Fang, MengJie,Li, ZhaoBin,et al. Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule[J]. EUROPEAN RADIOLOGY,2019,29(2):889-897.
APA Fan, Li.,Fang, MengJie.,Li, ZhaoBin.,Tu, WenTing.,Wang, ShengPing.,...&Liu, ShiYuan.(2019).Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule.EUROPEAN RADIOLOGY,29(2),889-897.
MLA Fan, Li,et al."Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule".EUROPEAN RADIOLOGY 29.2(2019):889-897.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Fan, Li]'s Articles
[Fang, MengJie]'s Articles
[Li, ZhaoBin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Fan, Li]'s Articles
[Fang, MengJie]'s Articles
[Li, ZhaoBin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Fan, Li]'s Articles
[Fang, MengJie]'s Articles
[Li, ZhaoBin]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.