Radiomics/Radiogenomics in Lung Cancer: Basic Principles and Initial Clinical Results

Lung cancer is the leading cause of cancer-related deaths worldwide, and elucidation of its complicated pathobiology has been traditionally targeted by studies incorporating genomic as well other high-throughput approaches. Recently, a collection of methods used for cancer imaging, supplemented by q...

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Published inCancers Vol. 14; no. 7; p. 1657
Main Authors Anagnostopoulos, Athanasios K, Gaitanis, Anastasios, Gkiozos, Ioannis, Athanasiadis, Emmanouil I, Chatziioannou, Sofia N, Syrigos, Konstantinos N, Thanos, Dimitris, Chatziioannou, Achilles N, Papanikolaou, Nikolaos
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 25.03.2022
MDPI
Subjects
Algorithms
Artificial intelligence
Biomarkers
Feature selection
Genomes
Genomics
Lung cancer
Machine learning
Magnetic resonance imaging
Medicin och hälsovetenskap
Patients
Phenotypes
Pipelines
Proteomics
Radiomics
Review
Tomography
Transcriptomics
lung cancer
image science
radiomics
radiogenomics
learning algorithms
review
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Summary:Lung cancer is the leading cause of cancer-related deaths worldwide, and elucidation of its complicated pathobiology has been traditionally targeted by studies incorporating genomic as well other high-throughput approaches. Recently, a collection of methods used for cancer imaging, supplemented by quantitative aspects leading towards imaging biomarker assessment termed "radiomics", has introduced a novel dimension in cancer research. Integration of genomics and radiomics approaches, where identifying the biological basis of imaging phenotypes is feasible due to the establishment of associations between molecular features at the genomic-transcriptomic-proteomic level and radiological features, has recently emerged termed radiogenomics. This review article aims to briefly describe the main aspects of radiogenomics, while discussing its basic limitations related to lung cancer clinical applications for clinicians, researchers and patients.
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These authors contributed equally to this work.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers14071657