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Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer Improvements Using Radiomics

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Title
Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer Improvements Using Radiomics
Author(s)
Geewon Lee; So Hyeon Bak; Ho Yun Lee; Joon Young Choi; Hyunjin Park; Seung-Hak Lee; Yoshiharu Ohno; Mizuki Nishino; Edwin J.R. van Beek; Kyung Soo Lee
Publication Date
2019-03
Journal
JOURNAL OF THORACIC IMAGING, v.34, no.2, pp.103 - 115
Publisher
LIPPINCOTT WILLIAMS & WILKINS
Abstract
Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics. © 2019 Wolters Kluwer Health, Inc. All rights reserved.
URI
https://pr.ibs.re.kr/handle/8788114/5878
ISSN
0883-5993
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
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