[Advancements in Radiomics for Immunotherapy of Non-small Cell Lung Cancer].

Q4 Medicine
Yue Hou, Tianming Zhang, Hong Wang
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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.
.

[非小细胞肺癌免疫疗法放射组学的进展]。
肺癌是癌症相关死亡的主要原因,其中非小细胞肺癌(NSCLC)是最主要的亚型。目前,以程序性细胞死亡受体 1 或其配体的免疫检查点抑制剂(ICIs)为代表的免疫疗法已广泛应用于 NSCLC 患者的临床诊断和治疗。然而,只有少数患者能从中获益,而免疫疗法也缺乏可靠的预测指标。放射组学是一种利用计算机软件和算法从生物医学图像中提取大量定量信息的工具。大量研究证实,预测NSCLC免疫疗效的放射组学模型可作为一种新型的免疫疗效预测标志物,有望指导肺癌患者的个体化诊疗决策,具有广阔的应用前景。本文综述了放射组学在预测NSCLC免疫治疗反应、识别假性进展和过度进展、ICI相关肺炎、恶病质风险以及与其他基因组学相结合等方面的研究进展。.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
中国肺癌杂志
中国肺癌杂志 Medicine-Pulmonary and Respiratory Medicine
CiteScore
1.40
自引率
0.00%
发文量
5131
审稿时长
14 weeks
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.
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