Clinical applications of radiomics in non-small cell lung cancer patients with immune checkpoint inhibitor-related pneumonitis

Frontiers in Immunology

Immunology

Rui Su¹  Zhen Chao¹  Jing Zhao²  Lei Liu²  Zhizhao Zhang²  Wei Xu³  Yang Shu⁴  Pancen Ran⁴  Guobin Fu⁵ 

[1] College of Artificial Intelligence and Big Data for Medical Sciences, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China;The Second Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China;The Second Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China;Department of Oncology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China;Department of Oncology, The Third Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China;

关键词: radiomics;    non-small cell lung cancer;    immune checkpoint inhibitor-related pneumonitis;    deep learning;    immunotherapy;   

DOI  :  10.3389/fimmu.2023.1251645

 received in 2023-07-02, accepted in 2023-08-24,  发布年份 2023

来源: Frontiers

【 摘 要 】

Immune checkpoint inhibitors (ICIs) modulate the body’s immune function to treat tumors but may also induce pneumonitis. Immune checkpoint inhibitor-related pneumonitis (ICIP) is a serious immune-related adverse event (irAE). Immunotherapy is currently approved as a first-line treatment for non-small cell lung cancer (NSCLC), and the incidence of ICIP in NSCLC patients can be as high as 5%-19% in clinical practice. ICIP can be severe enough to lead to the death of NSCLC patients, but there is a lack of a gold standard for the diagnosis of ICIP. Radiomics is a method that uses computational techniques to analyze medical images (e.g., CT, MRI, PET) and extract important features from them, which can be used to solve classification and regression problems in the clinic. Radiomics has been applied to predict and identify ICIP in NSCLC patients in the hope of transforming clinical qualitative problems into quantitative ones, thus improving the diagnosis and treatment of ICIP. In this review, we summarize the pathogenesis of ICIP and the process of radiomics feature extraction, review the clinical application of radiomics in ICIP of NSCLC patients, and discuss its future application prospects.

【 授权许可】

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Copyright © 2023 Shu, Xu, Su, Ran, Liu, Zhang, Zhao, Chao and Fu