Non-invasive decision support for NSCLC treatment using PET/CT radiomics

doi:10.1038/s41467-020-19116-x

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Non-invasive decision support for NSCLC treatment using PET/CT radiomics
	Mu, Wei 10; Jiang, Lei 4; Zhang, JianYuan 5,9; Shi, Yu 10; Gray, Jhanelle E.7; Tunali, Ilke 10; Gao, Chao 6,8; Sun, Yingying 6,8; Tian, Jie 2,3; Zhao, Xinming 5
刊名	NATURE COMMUNICATIONS
	2020-10-16
卷号	11 期号:1 页码:11
ISSN号	2041-1723
DOI	10.1038/s41467-020-19116-x
通讯作者	Zhao, Xinming(xinm_zhao@163.com) ; Sun, Xilin(sunxl@ems.hrbmu.edu.cn) ; Gillies, Robert J.(Robert.Gillies@Moffitt.org) ; Schabath, Matthew B.(matthew.schabath@moffitt.org)
英文摘要	Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during therapy. Thus, there is a compelling need to identify comprehensive biomarkers that can be used longitudinally to help guide therapy choice. Herein, we report a F-18-FDG-PET/CT-based deep learning model, which demonstrates high accuracy in EGFR mutation status prediction across patient cohorts from different institutions. A deep learning score (EGFR-DLS) was significantly and positively associated with longer progression free survival (PFS) in patients treated with EGFR-TKIs, while EGFR-DLS is significantly and negatively associated with higher durable clinical benefit, reduced hyperprogression, and longer PFS among patients treated with ICIs. Thus, the EGFR-DLS provides a non-invasive method for precise quantification of EGFR mutation status in NSCLC patients, which is promising to identify NSCLC patients sensitive to EGFR-TKI or ICI-treatments.EGFR mutations are common in non-small cell lung cancer and patients with these mutations are treated with tyrosine kinase inhibitors. Here, the authors show that EGFR mutation status can be predicted from F-18-FDG-PET/CT images, which may enable the stratification of patients for treatment.
资助项目	U.S. Public Health Service[U01 CA143062] ; U.S. Public Health Service[R01 CA190105] ; National Natural Science Foundation of China[81971645] ; National Natural Science Foundation of China[81627901] ; National Natural Science Foundation of China[81471724] ; Tou-Yan Innovation Team Program of the Heilongjiang Province[2019-15] ; Natural Science Foundation of Heilongjiang Province[JQ2020H002] ; National Basic Research Program of China[2015CB931800] ; Key Laboratory of Molecular Imaging Foundation (College of Heilongjiang Province)
WOS关键词	EGFR MUTATION STATUS ; CELL LUNG-CANCER ; GROWTH ; CHEMOTHERAPY ; DOCETAXEL ; BLOCKADE ; FEATURES
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	NATURE RESEARCH
WOS记录号	WOS:000582054700007
资助机构	U.S. Public Health Service ; National Natural Science Foundation of China ; Tou-Yan Innovation Team Program of the Heilongjiang Province ; Natural Science Foundation of Heilongjiang Province ; National Basic Research Program of China ; Key Laboratory of Molecular Imaging Foundation (College of Heilongjiang Province)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42182]
专题	自动化研究所_中国科学院分子影像重点实验室
通讯作者	Zhao, Xinming; Sun, Xilin; Gillies, Robert J.; Schabath, Matthew B.
作者单位	1.H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Epidemiol, Tampa, FL 33612 USA 2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 4.Tongji Univ, Shanghai Pulm Hosp, Dept Nucl Med, Sch Med, Shanghai, Peoples R China 5.Hebei Med Univ, Hosp 4, Dept Nucl Med, Shijiazhuang, Hebei, Peoples R China 6.Harbin Med Univ, Hosp 4, TOF PET CT MR Ctr, Harbin, Heilongjiang, Peoples R China 7.H Lee Moffitt Canc Ctr & Res Inst, Dept Thorac Oncol, Tampa, FL 33612 USA 8.Harbin Med Univ, Mol Imaging Res Ctr MIRC, NHC & CAMS Key Lab Mol Probe & Targeted Theranost, Harbin, Heilongjiang, Peoples R China 9.Baoding 1 Cent Hosp, Dept Nucl Med, Baoding, Hebei, Peoples R China 10.H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Physiol, Tampa, FL 33612 USA
推荐引用方式 GB/T 7714	Mu, Wei,Jiang, Lei,Zhang, JianYuan,et al. Non-invasive decision support for NSCLC treatment using PET/CT radiomics[J]. NATURE COMMUNICATIONS,2020,11(1):11.
APA	Mu, Wei.,Jiang, Lei.,Zhang, JianYuan.,Shi, Yu.,Gray, Jhanelle E..,...&Schabath, Matthew B..(2020).Non-invasive decision support for NSCLC treatment using PET/CT radiomics.NATURE COMMUNICATIONS,11(1),11.
MLA	Mu, Wei,et al."Non-invasive decision support for NSCLC treatment using PET/CT radiomics".NATURE COMMUNICATIONS 11.1(2020):11.