title: Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art.
abstract: With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Department of Radiology and Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea.
authors.forename: Geewon
authors.initials: G
authors.lastname: Lee
authors.affiliation: Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. Electronic address: hoyunlee96@gmail.com.
authors.forename: Ho Yun
authors.initials: HY
authors.lastname: Lee
authors.affiliation: School of Electronic and Electrical Engineering and Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, Republic of Korea.
authors.forename: Hyunjin
authors.initials: H
authors.lastname: Park
authors.affiliation: Department of Radiology, UW-Madison School of Medicine and Public Health, Madison, WI, United States.
authors.forename: Mark L
authors.initials: ML
authors.lastname: Schiebler
authors.affiliation: Clinical Research Imaging Centre, Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.
authors.forename: Edwin J R
authors.initials: EJR
authors.lastname: van Beek
authors.affiliation: Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe-shi 650-0017, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe-shi 650-0017, Japan.
authors.forename: Yoshiharu
authors.initials: Y
authors.lastname: Ohno
authors.affiliation: Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
authors.forename: Joon Beom
authors.initials: JB
authors.lastname: Seo
authors.affiliation: Department of Radiology, Stanford University, Palo Alto, CA, United States.
authors.forename: Ann
authors.initials: A
authors.lastname: Leung
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism; D023281:Genomics; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D000072078:Positron Emission Tomography Computed Tomography / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods
chemical_list: D014408:Biomarkers, Tumor
keywords: Biomarkers; Computed tomography; Image processing; Lung cancer; Outcomes assessment; Positron emission tomography