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Related Experiment Video

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Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics

Published on: January 8, 2018

A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample.

Riccardo Levi^1,2, Maximiliano Mollura³, Giovanni Savini²

¹Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, Pieve Emanuele, 20072, Milan, Italy.

Scientific Reports

|August 20, 2024

Summary

Radiomics features (RFs) from CT scans are sensitive to imaging parameters. Generalized Linear Models (GLM) effectively harmonize RFs across different CT settings, improving data consistency for research.

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Area of Science:

Medical Imaging
Radiology
Quantitative Imaging

Background:

Radiomics features (RFs) quantify imaging patterns but face reproducibility issues due to varying CT acquisition settings.
Standardization is crucial for clinical implementation of radiomics.

Purpose of the Study:

To investigate the impact of CT scanner and acquisition parameters on radiomics features of lumbar vertebrae.
To evaluate the effectiveness of a Generalized Linear Model (GLM) for harmonizing radiomics features.

Main Methods:

Extracted radiomics features from lumbar vertebrae across different CT scanners and protocols (kV, mA, FOV, kernel).
Utilized univariate and multivariate Generalized Linear Models (GLM) to assess parameter effects.
Compared GLM harmonization performance against the ComBat algorithm.

Main Results:

kV variations significantly altered radiomics features (First Order, GLCM, NGTDM), while mA had minimal impact.
The tailored GLM model outperformed ComBat in harmonizing CT images, achieving higher R2 values for more features.
GLM achieved R2 > 0.90 in 19.6% of RFs, compared to 0.9% for ComBat.

Conclusions:

CT acquisition parameters significantly influence bone radiomics features, necessitating harmonization strategies.
Generalized Linear Models offer a robust approach to mitigate variations and improve radiomics data consistency across diverse CT protocols and vendors.