期刊
AMERICAN JOURNAL OF ROENTGENOLOGY
卷 207, 期 3, 页码 534-543出版社
AMER ROENTGEN RAY SOC
DOI: 10.2214/AJR.15.15864
关键词
heterogeneity; informatics; lung cancer; radiogenomics; radiomics; texture analysis
资金
- Department of Health via the National Institute for Health Research (NIHR) Biomedical Research Centre awards
- Cancer Research UK
- Engineering and Physical Sciences Research Council in association
- Medical Research Council
- Department of Health (England)
- Cancer Research UK [16463] Funding Source: researchfish
OBJECTIVE. Texture analysis involves the mathematic processing of medical images to derive sets of numeric quantities that measure heterogeneity. Studies on lung cancer have shown that texture analysis may have a role in characterizing tumors and predicting patient outcome. This article outlines the mathematic basis of and the most recent literature on texture analysis in lung cancer imaging. We also describe the challenges facing the clinical implementation of texture analysis. CONCLUSION. Texture analysis of lung cancer images has been applied successfully to FDG PET and CT scans. Different texture parameters have been shown to be predictive of the nature of disease and of patient outcome. In general, it appears that more heterogeneous tumors on imaging tend to be more aggressive and to be associated with poorer outcomes and that tumor heterogeneity on imaging decreases with treatment. Despite these promising results, there is a large variation in the reported data and strengths of association.
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