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Evaluation of response to immune checkpoint inhibitors using a radiomics, lesion-level approach

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Title
Evaluation of response to immune checkpoint inhibitors using a radiomics, lesion-level approach
Author(s)
Song, Chorog; Hyunjin Park; Lee, Ho Yun; Lee, Seunghak; Ahn, Joong Hyun; Lee, Se-Hoon
Publication Date
2021-12
Journal
Cancers, v.13, no.23
Publisher
MDPI
Abstract
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.Conventional methods to determine the response to immune checkpoint inhibitors (ICIs) are limited by the unique responses to an ICI. We performed a radiomics approach for all measurable lesions to identify radiomic variables that could distinguish hyperprogressive disease (HPD) on baseline CT scans and classify a dissociated response (DR). One hundred and ninety-six patients with advanced lung cancer, treated with ICI monotherapy, who underwent at least three CT scans, were retrospectively enrolled. For all 621 measurable lesions, HPDv was determined from baseline CT scans using the tumor growth kinetics (TGK) ratio, and radiomics features were extracted. Multivariable logistic regression analysis of radiomics features was performed to discriminate DR. Radiomics features that significantly discriminated HPDv on baseline CT differed according to organ. Of the 196 patients, 54 (27.6%) had a DR and 142 (72.4%) did not have a DR. Overall survival in the group with a DR was significantly inferior to that in the group without a DR (log rank test, p = 0.04). Our study shows that lesion-level analysis using radiomics features has great potential for discriminating HPDv and understanding heterogeneous tumor progression, including a DR, after ICI treatment.
URI
https://pr.ibs.re.kr/handle/8788114/10866
DOI
10.3390/cancers13236050
ISSN
2072-6694
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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