Radiomics in Oncological PET/CT: a Methodological Overview

Seunggyun Ha, Hongyoon Choi, Jin Chul Paeng, Gi Jeong Cheon

Research output: Contribution to journalReview articlepeer-review

88 Scopus citations

Abstract

Radiomics is a medical imaging analysis approach based on computer-vision. Metabolic radiomics in particular analyses the spatial distribution patterns of molecular metabolism on PET images. Measuring intratumoral heterogeneity via image is one of the main targets of radiomics research, and it aims to build a image-based model for better patient management. The workflow of radiomics using texture analysis follows these steps: 1) imaging (image acquisition and reconstruction); 2) preprocessing (segmentation & quantization); 3) quantification (texture matrix design & texture feature extraction); and 4) analysis (statistics and/or machine learning). The parameters or conditions at each of these steps are effect on the results. In statistical testing or modeling, problems such as multiple comparisons, dependence on other variables, and high dimensionality of small sample size data should be considered. Standardization of methodology and harmonization of image quality are one of the most important challenges with radiomics methodology. Even though there are current issues in radiomics methodology, it is expected that radiomics will be clinically useful in personalized medicine for oncology.

Original languageEnglish
Pages (from-to)14-29
Number of pages16
JournalNuclear Medicine and Molecular Imaging
Volume53
Issue number1
DOIs
StatePublished - 1 Feb 2019

Bibliographical note

Publisher Copyright:
© 2019, Korean Society of Nuclear Medicine.

Keywords

  • FDG PET/CT
  • Intratumoral heterogeneity
  • Oncology
  • Radiomics
  • Texture analysis

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