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Proceedings Paper

A preliminary study of visualizing texture components of stage IA lung adenocarcinoma in three-dimensional thoracic CT images with structure-texture image decomposition
Author(s): Y. Kawata; N. Niki; M. Kusumoto; H. Ohmatsu; K. Aokage; G. Ishii; Y. Matsumoto; T. Tsuchida; K. Eguchi; M. Kaneko
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Paper Abstract

Lung adenocarcinomas are the most prevalent subtype of non-small cell lung cancers which are found as the most common true-positive finding in a lung cancer screening population. The ability to preoperatively identify patients with a high rate of relapse becomes crucial to guide treatment decisions and to develop risk-adapted treatment strategies. Considerable research efforts have been performed to enable the stratification of adenocarcinoma aggressiveness based on preoperative CT image analyses for optimal therapeutic management to maximize patient survival and preserve lung function. It is currently a major focus to quantitatively evaluate adenocarcinoma aggressiveness according to computerextracted imaging features (radiomics) in three-dimensional (3D) thoracic CT images. Texture features are known to measure tumor heterogeneity and have been identified as the features having a potential correlation to outcomes in lung cancer. Nevertheless, a spatial configuration of texture caused by the tumor heterogeneity remains elusive. In this study, we present a visualization method to reveal a spatial configuration of the texture of pulmonary nodules in 3D thoracic CT images through a structure-texture image decomposition. Applying the method to an example of early-stage lung adenocarcinomas graded with texture features based on the popular algorithm such as gray-level co-occurrence matrix (GLCM), we present that the preliminary results reveal the presence of intensity structure caused by tumor heterogeneity.

Paper Details

Date Published: 28 February 2020
PDF: 7 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 113170G (28 February 2020); doi: 10.1117/12.2549824
Show Author Affiliations
Y. Kawata, Tokushima Univ. (Japan)
N. Niki, Tokushima Univ. (Japan)
M. Kusumoto, National Cancer Ctr. Hospital (Japan)
H. Ohmatsu, Medical Affairs Section (Japan)
K. Aokage, National Cancer Ctr. Hospital East (Japan)
G. Ishii, National Cancer Ctr. (Japan)
Y. Matsumoto, National Cancer Ctr. Hospital (Japan)
T. Tsuchida, National Cancer Ctr. Hospital (Japan)
K. Eguchi, Teikyo Univ. School of Medicine (Japan)
M. Kaneko, Tokyo Health Service Association (Japan)

Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

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