Radiographic Image Radiomics Feature Reproducibility: A Preliminary Study on the Impact of Field Size

J Med Imaging Radiat Sci. 2020 Mar;51(1):128-136. doi: 10.1016/j.jmir.2019.11.006. Epub 2020 Feb 21.

Abstract

Rationale and objectives: Radiomics is an approach to quantifying diseases. Recently, several studies have indicated that radiomics features are vulnerable against imaging parameters. The aim of this study is to assess how radiomics features change with radiographic field sizes, positions in the field size, and mAs.

Materials and methods: A large and small wood phantom and a cotton phantom were prepared and imaged in different field sizes, mAs, and placement in the radiographic field size. A region of interest was drawn on the image features, and twenty two features were extracted. Radiomics feature reproducibility was obtained based on coefficient of variation, Bland-Altman analysis, and intraclass correlation coefficient. Features with coefficient of variation ≤ 5%, intraclass correlation coefficient ≤ 90%, and 1% ≤ U/LRL ≤30% were introduced as robust features. U/LRL is upper/lower reproducibility limits in Bland-Altman.

Results: For all field sizes and all phantoms, features including Difference Variance, Inverse Different Moment, Fraction, Long Run Emphasis, Run Length Non Uniformity, and Short Run Emphasis were found as highly reproducible features. For change in the position of field size, Fraction was the most reproducible in all field sizes and all phantoms. On the mAs change, we found that feature, Short Run Emphasis field 15 × 15 for small wood phantom, and Correlation in all field sizes for Cotton are the most reproducible features.

Conclusion: We demonstrated that radiomics features are strongly vulnerable against radiographic field size, positions in the radiation field, mAs, and phantom materials, and reproducibility analyses should be performed before each radiomics study. Moreover, these changing parameters should be considered, and their effects should be minimized in future radiomics studies.

Keywords: Radiomics; field size; mAs; positions; radiography; reproducibility.

MeSH terms

  • Data Mining
  • Decision Support Techniques*
  • Diagnostic Imaging*
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Phantoms, Imaging
  • Reproducibility of Results