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

doi:10.1038/s41467-020-19116-x

	Non-invasive decision support for NSCLC treatment using PET/CT radiomics
	Mu, Wei1 ; Jiang, Lei2 ; Zhang, JianYuan 3,4; Shi, Yu 1; Gray, Jhanelle E.5; Tunali, Ilke 1; Gao, Chao 6,7; Sun, Yingying 6,7; Tian, Jie8,9 ; Zhao, Xinming 3; Sun, Xilin 6,7; Gillies, Robert J.1; Schabath, Matthew B.5,10
Source Publication	NATURE COMMUNICATIONS
ISSN	2041-1723
	2020-10-16
Volume	11 Issue:1 Pages:11
Corresponding Author	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)
Abstract	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.
DOI	10.1038/s41467-020-19116-x
WOS Keyword	EGFR MUTATION STATUS ; CELL LUNG-CANCER ; GROWTH ; CHEMOTHERAPY ; DOCETAXEL ; BLOCKADE ; FEATURES
Indexed By	SCI
Language	英语
Funding Project	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)
Funding Organization	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)
WOS Research Area	Science & Technology - Other Topics
WOS Subject	Multidisciplinary Sciences
WOS ID	WOS:000582054700007
Publisher	NATURE RESEARCH
Citation statistics	Cited Times:9[WOS] [WOS Record] [Related Records in WOS]
Document Type	期刊论文
Identifier	http://ir.ia.ac.cn/handle/173211/42183
Collection	中国科学院分子影像重点实验室
Corresponding Author	Zhao, Xinming; Sun, Xilin; Gillies, Robert J.; Schabath, Matthew B.
Affiliation	1.H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Physiol, Tampa, FL 33612 USA 2.Tongji Univ, Shanghai Pulm Hosp, Dept Nucl Med, Sch Med, Shanghai, Peoples R China 3.Hebei Med Univ, Hosp 4, Dept Nucl Med, Shijiazhuang, Hebei, Peoples R China 4.Baoding 1 Cent Hosp, Dept Nucl Med, Baoding, Hebei, Peoples R China 5.H Lee Moffitt Canc Ctr & Res Inst, Dept Thorac Oncol, Tampa, FL 33612 USA 6.Harbin Med Univ, Mol Imaging Res Ctr MIRC, NHC & CAMS Key Lab Mol Probe & Targeted Theranost, Harbin, Heilongjiang, Peoples R China 7.Harbin Med Univ, Hosp 4, TOF PET CT MR Ctr, Harbin, Heilongjiang, Peoples R China 8.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 9.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 10.H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Epidemiol, Tampa, FL 33612 USA
Recommended Citation 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.

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