{"title":"[Advancements in Radiomics for Immunotherapy of Non-small Cell Lung Cancer].","authors":"Yue Hou, Tianming Zhang, Hong Wang","doi":"10.3779/j.issn.1009-3419.2024.102.29","DOIUrl":null,"url":null,"abstract":"<p><p>Lung cancer is the main cause of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the predominant subtype. At present, immunotherapy represented by immune checkpoint inhibitors (ICIs) of programmed cell death receptor 1 or its ligand has been widely used in the clinical diagnosis and treatment of patients with NSCLC. However, only a few patients can benefit from it, and reliable predictive markers for immunotherapy are lacking. Radiomics is a tool that uses computer software and algorithms to extract a large amount of quantitative information from biomedical images. A large number of studies have confirmed that the radiomic model that predicts the immune efficacy of NSCLC can be used as a new type of immune efficacy predictive marker, which is expected to guide the individualized diagnosis and treatment decisions for patients with lung cancer and has a bright application prospect. This article reviews the research progress of radiomics in predicting the immune therapy response of NSCLC, identifying pseudo-progression and hyperprogression, ICIs-related pneumonia, cachexia risk, and combining with other genomics.\u2029.</p>","PeriodicalId":39317,"journal":{"name":"中国肺癌杂志","volume":"27 8","pages":"637-644"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425675/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国肺癌杂志","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3779/j.issn.1009-3419.2024.102.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Lung cancer is the main cause of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the predominant subtype. At present, immunotherapy represented by immune checkpoint inhibitors (ICIs) of programmed cell death receptor 1 or its ligand has been widely used in the clinical diagnosis and treatment of patients with NSCLC. However, only a few patients can benefit from it, and reliable predictive markers for immunotherapy are lacking. Radiomics is a tool that uses computer software and algorithms to extract a large amount of quantitative information from biomedical images. A large number of studies have confirmed that the radiomic model that predicts the immune efficacy of NSCLC can be used as a new type of immune efficacy predictive marker, which is expected to guide the individualized diagnosis and treatment decisions for patients with lung cancer and has a bright application prospect. This article reviews the research progress of radiomics in predicting the immune therapy response of NSCLC, identifying pseudo-progression and hyperprogression, ICIs-related pneumonia, cachexia risk, and combining with other genomics. .
期刊介绍:
Chinese Journal of Lung Cancer(CJLC, pISSN 1009-3419, eISSN 1999-6187), a monthly Open Access journal, is hosted by Chinese Anti-Cancer Association, Chinese Antituberculosis Association, Tianjin Medical University General Hospital. CJLC was indexed in DOAJ, EMBASE/SCOPUS, Chemical Abstract(CA), CSA-Biological Science, HINARI, EBSCO-CINAHL,CABI Abstract, Global Health, CNKI, etc. Editor-in-Chief: Professor Qinghua ZHOU.