人工智能在肺癌脑转移瘤EGFR突变状态研究中的应用与进展  

Artificial intelligence-based research progress related to EGFR mutation status in non-small cell lung cancer brain metastases

作　　者：迪拉热·司马义 丁秋分 王俭[1] Dilare·Simayi;Ding Qiufen;Wang Jian(The First Affiliated Hospital of Xinjiang Medical University,Urumqi,Xinjiang 830054,China)

机构地区：[1]新疆医科大学第一附属医院,新疆乌鲁木齐830054

出　　处：《首都食品与医药》2025年第9期11-13,共3页Capital Food Medicine

摘　　要：非小细胞肺癌(Non-small cell lung cancer,NSCLC)是发病率和死亡率均很高的恶性肿瘤,脑转移(Brain metastasis,BM)是肺癌远处转移中最常见的。表皮生长因子受体(Epidermal growth factor receptor,EGFR)突变与脑转移相关,并且近年来随着表皮生长因子受体酪氨酸激酶抑制剂(Epidermal growth factor receptor-tyrosine kinase inhibitors,EGFR-TKI)疗法改变了EGFR突变NSCLC患者的预后,检测其突变状态至关重要。本文介绍了影像组学和深度学习在预测NSCLC合并BM患者的EGFR突变状态、临床预后及耐药性中的应用。Non-small cell lung cancer(NSCLC)is a malignant tumor with high incidence and mortality.Brain metastasis(BM)is the most common type of distant metastasis in lung cancer.Epidermal growth factor receptor(EGFR)mutations are associated with brain metastasis.In recent years,with the epidermal growth factor receptor-tyrosine kinase inhibitors(EGFR-TKI)therapy changing the prognosis of NSCLC patients with EGFR mutations,it is of crucial importance to detect the mutation status.This paper expounds on the applications of radiomics and deep learning in predicting the EGFR mutation status,clinical prognosis,and drug resistance in NSCLC patients with BM.

关 键 词：非小细胞肺癌 脑转移瘤 EGFR 影像组学 深度学习 

分 类 号：R734.2[医药卫生—肿瘤]