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Tumor margin contains prognostic information: Radiomic margin characteristics analysis in lung adenocarcinoma patients

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Title
Tumor margin contains prognostic information: Radiomic margin characteristics analysis in lung adenocarcinoma patients
Author(s)
Lee, Geewon; Hyunjin Park; Lee, Ho Yun; Ahn, Joong Hyun; Sohn, Insuk; Lee, Seung-Hak; Kim, Jhingook
Publication Date
2021-04
Journal
Cancers, v.13, no.7
Publisher
MDPI AG
Abstract
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.We aimed to investigate the relationship between tumor radiomic margin characteristics and prognosis in patients with lung cancer. We enrolled 334 patients who underwent complete resection for lung adenocarcinoma. A quantitative computed tomography analysis was performed, and 76 radiomic margin characteristics were extracted. The radiomic margin characteristics were correlated with overall survival. The selected clinical variables and radiomic margin characteristics were used to calculate a prognostic model with subsequent internal and external validation. Nearly all of the radiomic margin characteristics showed excellent reproducibility. The least absolute shrinkage and selection operator (LASSO) method was used to select eight radiomic margin characteristics. When compared to the model with clinical variables only (C-index = 0.738), the model incorporating clinical variables and radiomic margin characteristics (C-index = 0.753) demonstrated a higher C-index for predicting overall survival. In the model integrating both clinical variables and radiomic margin characteristics, convexity, a Laplace of Gaussian (LoG) kurtosis of 3, and the roundness factor were each independently predictive of overall survival. In addition, radiomic margin characteristics were also correlated with the micropapillary subtype, and the sphericity value was able to predict the presence of the micropapillary subtype. In conclusion, our study showed that radiomic margin characteristics helped predict overall survival in patients with lung adenocarcinomas, thus implying that the tumor margin contains prognostic information.
URI
https://pr.ibs.re.kr/handle/8788114/9525
DOI
10.3390/cancers13071676
ISSN
2072-6694
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
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