Radiomics: Images Are More than Pictures, They Are Data

被引:6439
作者
Gillies, Robert J. [1 ]
Kinahan, Paul E. [2 ]
Hricak, Hedvig [3 ]
机构
[1] Univ S Florida, Coll Med, H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Imaging, 12902 Magnolia Dr, Tampa, FL 33612 USA
[2] Univ Washington, Dept Radiol, Seattle, WA 98195 USA
[3] Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY 10065 USA
基金
美国国家卫生研究院;
关键词
CONCORDANCE CORRELATION-COEFFICIENT; COMPUTER-AIDED DIAGNOSIS; GENE-EXPRESSION PROGRAMS; INTRATUMOR HETEROGENEITY; RADIOGENOMIC ANALYSIS; DISTANT METASTASIS; CLINICAL-OUTCOMES; TEXTURE ANALYSIS; PROSTATE-CANCER; BREAST-CANCER;
D O I
10.1148/radiol.2015151169
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
引用
收藏
页码:563 / 577
页数:15
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