肿瘤自身抗体及CT人工智能在NSCLC早期诊断中的应用研究进展OA北大核心CSTPCD
Research progress of tumor autoantibodies and CT artificial intelligence in early diagnosis of NSCLC
非小细胞肺癌(NSCLC)是全球发病和死亡原因排位居前的恶性肿瘤.近年来,CT人工智能利用大数据自动提取与学习影像学特征,可帮助影像科医师减少肺结节诊断的工作量与漏诊率.肺癌7种自身抗体(p53、SOX2、PGP9.5、CAGE、MAGE-A1、GAGE7、GBU4-5)试剂盒投入中国临床使用,在NSCLC的早期筛查中表现出高特异度.此外,ctDNA甲基化等其他液体活检技术也在不断探索中.然而,现有的各种方法用于肺癌早期诊断均有不足,将其优化组合或建立诊断模型已成为一种趋势.本文综述肺癌7种自身抗体与CT人工智能在NSCLC早期诊断中的相关研究进展及其价值,以期为其联合用于中国人群肺癌的早期诊断提供参考.
Non-small cell lung cancer(NSCLC)is one of the most prevalent and deadly malignant tumors in the world.In recent years,artificial intelligence(AI)in computed tomography(CT)has harnessed the power of big data to automatically extract and learn imaging features,thereby assisting radiologists in reducing the workload and missed diagnosis rate of pulmonary nodules.An ELISA kit for detecting seven lung cancer autoantibodies(p53,SOX2,PGP9.5,CAGE,MAGE-A1,GAGE7,and GBU4-5)has been clinically implemented in China,showing high specificity in the early screening of NSCLC.Additionally,other liquid biopsy techniques such as circulating tumor DNA(ctDNA)methylation markers are also continually being explored.However,existing methods for the early diagnosis of lung cancer all have their limitations,and optimizing their combination or establishing diagnostic models has become a trend.This review summarizes the research progress and value of the seven lung cancer autoantibodies and CT AI in the early diagnosis of NSCLC,with the aim of providing a reference for their combined use in the early diagnosis of lung cancer in Chinese population.
王晶;翟成凯
新乡医学院第五临床学院/新乡市第一人民医院呼吸与危重症医学科,河南新乡 453000
临床医学
非小细胞肺癌自身抗体人工智能肺结节早期诊断
non-small-cell lung carcinomaautoantibodiesartificial intelligencepulmonary nodulesearly diagnosis
《解放军医学杂志》 2024 (007)
848-854 / 7
This work was supported by the Scientific and Technological Project of Xinxiang City(GG2019033) 新乡市科技攻关计划项目(GG2019033)
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