Journal
JOURNAL OF NUCLEAR MEDICINE
Volume 61, Issue 4, Pages 488-495Publisher
SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.118.222893
Keywords
radiomics; artificial intelligence; machine learning; PET; single-photon emission tomography
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Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving. The goal of this continuing education article is to provide an introduction to the field, covering the basic radiomics workflow: feature calculation and selection, dimensionality reduction, and data processing. Potential clinical applications in nuclear medicine that include PET radiomics-based prediction of treatment response and survival will be discussed. Current limitations of radiomics, such as sensitivity to acquisition parameter variations, and common pitfalls will also be covered.
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