CT Radiomics in Thoracic Oncology: Technique and Clinical Applications
10.1007/s13139-017-0506-5
- Author:
Geewon LEE
1
;
So Hyeon BAK
;
Ho Yun LEE
Author Information
1. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. hoyunlee96@gmail.com
- Publication Type:Review
- Keywords:
Computed tomography;
Lung cancer;
Image processing;
Biomarkers
- MeSH:
Biology;
Biomarkers;
Humans;
Lung Neoplasms;
Phenotype;
Population Characteristics;
Precision Medicine
- From:Nuclear Medicine and Molecular Imaging
2018;52(2):91-98
- CountryRepublic of Korea
- Language:English
-
Abstract:
Precision medicine offers better treatment options and improved survival for cancer patients based on individual variability. As the success of precision medicine depends on robust biomarkers, the requirement for improved imaging biomarkers that reflect tumor biology has grown exponentially. Radiomics, the field of study in which high-throughput data are generated and large amounts of advanced quantitative features are extracted from medical images, has shown great potential as a source of quantitative biomarkers in the field of oncology. Radiomics provides quantitative information about the morphology, texture, and intratumoral heterogeneity of the tumor itself as well as features related to pulmonary function. Hence, radiomics data can be used to build descriptive and predictive clinical models that relate imaging characteristics to tumor biology phenotypes. In this review, we describe the workflow of CT radiomics, types of CT radiomics, and its clinical application in thoracic oncology.
