Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation

Author:

Cheng BoORCID,Deng Hongsheng,Zhao Yi,Xiong Junfeng,Liang Peng,Li Caichen,Liang Hengrui,Shi Jiang,Li Jianfu,Xiong Shan,Lai Ting,Chen Zhuxing,Wu Jianrong,Qian Tianyi,Huan Wenjing,Alexander Ng Man Tat,Wang Guotai,He JianxingORCID,Liang WenhuaORCID

Abstract

AbstractObjectivesThis study aimed to establish a noninvasive radiomics model based on computed tomography (CT), with favorable sensitivity and specificity to predict EGFR mutation status in GGO-featured lung adenocarcinoma that subsequently guiding the administration of targeted therapy.MethodClinical-pathological information and preoperative CT-images of 636 lung adenocarcinoma patients (464, 100, and 72 in the training, internal, and external validation sets, respectively) that underwent GGO lesions resection were included. A total of 1476 radiomic features were extracted with gradient boosting decision tree (GBDT).ResultsThe established radiomics model containing 252 selected features showed an encouraging discrimination performance of EGFR mutation status (mutant or wild-type), and the predictive ability was superior to that of the clinical model (AUC: 0.901 vs. 0.674, 0.813 vs. 0.730, and 0.801 vs. 0.746 the training, internal, and external validation sets, respectively). The combined radiomics plus clinical model showed no additional benefit over the radiomics model in predicting EGFR status (AUC: 0.909 vs. 0.901, 0.803 vs. 0.813, 0.808 vs. 0.801, respectively, in three cohorts). Uniquely, this model was validated in a cohort of lung adenocarcinoma patients who undertaken adjuvant EGFR-TKIs and harbored unresected GGOs, leading to a significantly improved potency of EGFR-TKIs (response rate: 33.9% vs. 62.5%, P =0.04; before- and after-prediction, respectively).ConclusionThis presented radiomics model can be served as a noninvasive and time-saving approach for predicting the EGFR mutation status in lung adenocarcinoma presenting as GGO.Key pointsWe developed a GGO-specific radiomics model containing 252 radiomics features for EGFR mutation status differentiation.An AUC of 0.813 and 0.801 in the internal and external validation cohort, respectively, were achieved.The radiomics model was utilized in clinical translation in an adjuvant EGFR-TKIs cohort with unresected GGOs. A significant improvement in the potency of EGFR-TKIs was achieved (response rate: 33.9% vs. 62.5%, P =0.04; before- and after-prediction).

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3