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Delta-radiomics increases multicentre reproducibility: a phantom study.

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Summary
This summary is machine-generated.

Delta-texture analysis (D-TA) shows more robust radiomics features than standard texture analysis (TA) across different CT scanners and acquisition parameters. This improved reliability suggests D-TA

Keywords:
ImagingLung cancerRadiomicsTexture analysis

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Area of Science:

  • Medical Imaging
  • Radiomics
  • Quantitative Imaging

Background:

  • Texture analysis (TA) provides quantitative imaging features correlated with clinical outcomes.
  • Robustness of radiomics features is a challenge due to variations in acquisition and reconstruction protocols.
  • Delta-texture analysis (D-TA) assesses TA feature changes over time, typically before and after therapy.

Purpose of the Study:

  • To investigate the influence of different CT scanners and acquisition parameters on the robustness of TA and D-TA.
  • To compare the reliability of TA and D-TA features.

Main Methods:

  • A commercial phantom was scanned using three different CT scanners with varied plug configurations.
  • Texture analysis (TA) features were extracted using LifeX software.
  • D-TA features were calculated as the variation of TA parameters between scans: (Y-X)/X.
  • Robustness was assessed using intraclass coefficient correlation (ICC).

Main Results:

  • Standard TA features demonstrated poor to moderate reliability across different scans and parameters (0/37 good reliability).
  • D-TA features exhibited significantly better reliability, with 17/37 parameters showing good reliability.
  • A significant difference in ICC was observed between TA and D-TA for the overall group and GLCM parameters.

Conclusions:

  • D-TA features are more robust than TA features when evaluated across different CT scanners and acquisition settings.
  • D-TA holds potential for early assessment of treatment response and development of personalized therapies.
  • Further clinical validation is necessary to confirm these findings.