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Radiomics in Oncological PET/CT: a Methodological Overview

Nuclear Medicine and Molecular Imaging volume 53, pages 14–29 (2019)Cite this article

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.

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Abbreviations

AQ:

Absolute quantization

AUC-CSH:

Area under curve of cumulative SUV-volume histogram

CSH:

Cumulative SUV-volume histogram

CV:

Coefficient of variation

FBN:

Fixed bin number

FBS:

Fixed bin size

FCM:

Fuzzy C-means

FDR:

False-discovery rate

18F-FDG:

18F-fluorodeoxyglucose

FLAB:

Fuzzy locally adaptive Bayesian

GLCM:

Gray-level co-occurrence matrix

GLRLM:

Gray-level run-length matrix

GLSZM:

Gray-level size zone matrix

IFH:

Intensity frequency histogram

ITH:

Intratumoral heterogeneity

IVH:

Intensity volume histogram

MTV:

Metabolic tumor volume

NGTDM:

Neighborhood gray-tone difference matrix

PET/CT:

Positron emission tomography/computed tomography

PVC:

Partial volume correction

RQ:

Relative quantization

SAM:

Second angular moment

SGLDM:

Spatial gray-level dependence matrix

SUV:

Standardized uptake value

TLG:

Total lesion glycolysis

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Affiliations

  1. Radiation Medicine Research Institute, Seoul National University College of Medicine, Seoul, South Korea

    Seunggyun Ha & Gi Jeong Cheon

  2. Department of Nuclear Medicine, Seoul National University Hospital, Seoul, South Korea

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

  3. Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea

    Gi Jeong Cheon

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  1. Seunggyun Ha
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Correspondence to Gi Jeong Cheon.

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Seunggyun Ha, Hongyoon Choi, Jin Chul Paeng, and Gi Jeong Cheon declare no conflict of interest.

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Ha, S., Choi, H., Paeng, J.C. et al. Radiomics in Oncological PET/CT: a Methodological Overview. Nucl Med Mol Imaging 53, 14–29 (2019). https://doi.org/10.1007/s13139-019-00571-4

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  • DOI: https://doi.org/10.1007/s13139-019-00571-4

Keywords

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