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T2w-MRI signal normalization affects radiomics features reproducibility.

Elisa Scalco1,2, Antonella Belfatto2, Alfonso Mastropietro1,2

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Radiomic feature reproducibility in prostate cancer MRI is significantly impacted by intensity normalization methods. Mean normalization and histogram matching offer better reliability than region-based normalization, crucial for consistent radiomics analysis.

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Area of Science:

  • Medical Imaging
  • Radiomics
  • Oncology

Background:

  • Radiomics is increasingly used in clinical practice but faces challenges in reproducibility, particularly with MRI data lacking standardized units.
  • Intensity normalization is a critical preprocessing step for radiomic feature extraction, with various methods available.
  • The impact of different normalization techniques on the reliability of radiomic features from pelvic T2w-MRI remains to be fully elucidated.

Purpose of the Study:

  • To evaluate the effect of three distinct intensity normalization techniques on the reproducibility of radiomic features extracted from T2w-MRI.
  • To compare the performance of mean normalization, region-of-interest (ROI) normalization, and histogram matching in enhancing radiomic feature reliability.

Main Methods:

  • T2w-MRI data from 14 prostate cancer patients before and 12 months after radiotherapy were analyzed.
  • Four conditions were tested: original MRI (No_Norm), mean normalization (Norm_Mean), ROI normalization (Norm_ROI), and histogram matching (Norm_HM).
  • Ninety-one radiomic features were extracted from the prostate, obturator muscles, and bulb, and their reproducibility was assessed using the Intraclass Correlation Coefficient (ICC).

Main Results:

  • Approximately 60% of radiomic features exhibited poor reproducibility (ICC < 0.5), with Norm_ROI showing the lowest average ICC (0.45).
  • Norm_HM demonstrated superior performance for first-order features compared to Norm_Mean (average ICC 0.76 vs. 0.33).
  • Feature reproducibility varied across organs, being higher in the prostate. Analysis of feature differences (Δfeature) indicated Norm_Mean and Norm_HM were more consistent.

Conclusions:

  • The choice of intensity normalization significantly impacts radiomic feature reproducibility and information content in T2w-MRI.
  • Norm_Mean and Norm_HM methods generally yield more reproducible radiomic features compared to Norm_ROI.
  • A small subset of features, including skewness, kurtosis, and certain GLCM-derived features, demonstrated consistent reproducibility across tested conditions.