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FDG PET radiomics: a review of the methodological aspects

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Abstract

Purpose

To perform an updated review regarding the influence of methodological conditions on radiomics analyses of 18F-FDG PET imaging.

Methods

We performed a systematic review of the literature using PubMed/Medline and Google scholars, with multiple research keywords for each organ accompanying the terms “radiomics”, “texture”, “heterogeneity”, “FDG”, “PET” and “PET/CT”. The review considers methodological studies for shape, histogram and textural features extracted from FDG PET imaging. The references cited in the retrieved articles were also explored to find additional studies. The search was limited to English language. Preclinical and animal studies were not included in the review. A total of 44 original articles were considered for the review.

Results

In the same conditions, repeatability is very variable among the radiomics features in FDG PET. The vast majority of features are sensitive to acquisition and reconstruction settings independently of the category or order of features. Similar sensitivity and variability are observed with respect to respiratory motion, pre-processing, segmentation method, and specifically for textural features, discretisation of grey levels and implementation/parameterisation of texture matrices.

Conclusion

Radiomics features are sensitive to almost all factors involved in the PET/CT workflow, from the generation of the images, to the radiomics implementation choices. This strongly supports the need for standardization efforts of these conditions to enable implementation in clinical routine and multicentric studies. However, to date the repercussion of these features fluctuations on the clinical endpoints has been rarely studied. Similar standardization and consensus will also be needed for the statistical analysis and machine learning aspects involved in radiomics analyses of FDG PET images.

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Abbreviations

ASM:

Angular second moment

CCC:

Concordance correlation coefficient

CHAUC :

Area under the curve of the cumulative histogram

COV:

Coefficient of variation

FLAB:

Fuzzy locally adaptive bayesian algorithm

GLCM:

Grey-level co-occurrence matrix

GLRLM:

Grey-level run-length matrix

GLZSM:

Grey-level zone-size matrix

HILAE:

High-intensity large area emphasis

HGZE:

High grey-level zone emphasis

ICC:

Intra-class correlation coefficients

IV:

Intensity variability

LGZE:

Low grey-level zone emphasis

LRE:

Long-run emphasis

MTV:

Metabolic tumour volume

NGTDM:

Neighbourhood grey-tone difference matrix

NSCLC:

Non-small lung cancer

OSEM:

Ordered subset expectation maximisation

PSF:

Point spread function

SRE:

Short-run emphasis

SUV:

Standardised uptake value

SUVSD :

SUV standard deviation

SZV:

Size-zone variability

TOF:

Time of flight

VOI:

Volume of interest

ZP:

Zone percentage

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Authors and Affiliations

  1. Division of Nuclear Medicine and Oncological Imaging, University Hospital of Liege, Liege, Belgium

    Pierre Lovinfosse & Roland Hustinx

  2. LaTIM, INSERM, UMR 1101, IBSAM, UBO, UBL, Brest, France

    Dimitris Visvikis & Mathieu Hatt

Authors
  1. Pierre Lovinfosse
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  2. Dimitris Visvikis
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  3. Roland Hustinx
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  4. Mathieu Hatt
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Contributions

PL: Content planning, literature search and review, manuscript writing. DV: Content planning, manuscript editing. RH: Content planning, manuscript editing. MH: Content planning, manuscript writing and editing.

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Correspondence to Pierre Lovinfosse.

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All the authors declare no conflict of interest.

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Lovinfosse, P., Visvikis, D., Hustinx, R. et al. FDG PET radiomics: a review of the methodological aspects. Clin Transl Imaging 6, 379–391 (2018). https://doi.org/10.1007/s40336-018-0292-9

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