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Noninvasive Grading of Liver Fibrosis Based on Texture Analysis From MRI-Derived Radiomics.

Jennifer Gotta1, Leon D Gruenewald1, Philipp Reschke1

  • 1Department of Radiology, Goethe University Hospital Frankfurt, Frankfurt am Main, Germany.

NMR in Biomedicine
|December 20, 2024
PubMed
Summary

This study shows magnetic resonance imaging (MRI) radiomics can noninvasively assess liver fibrosis. The developed radiomics model shows promise for staging liver fibrosis severity from MRI scans.

Keywords:
liver cirrhosisliver fibrosismagnetic resonance imagingradiomics

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Area of Science:

  • Radiology
  • Medical Imaging
  • Oncology

Background:

  • Metabolic syndrome and liver fibrosis are increasing globally.
  • Accurate, noninvasive fibrosis staging is crucial for patient management.
  • Current methods often require invasive procedures.

Purpose of the Study:

  • To evaluate MRI-derived radiomics for noninvasive liver fibrosis grading.
  • To develop and validate a radiomics model for fibrosis staging.
  • To assess the added value of apparent diffusion coefficient (ADC) values.

Main Methods:

  • Prospective enrollment of 79 participants undergoing MRI elastography (MRE).
  • Extraction of 107 radiomic features from MRI scans.
  • Development of a gradient-boosted tree model with stepwise feature reduction.
  • Validation in an independent test cohort.

Main Results:

  • The radiomics model achieved high AUC values (0.997-0.998) in the training cohort.
  • In the test cohort, AUC values ranged from 0.617 to 0.830, with AUC 0.830 for grade 2 fibrosis.
  • Inclusion of ADC values did not enhance model performance.

Conclusions:

  • MRI-based radiomics shows significant potential for noninvasive liver fibrosis staging.
  • This approach allows retrospective assessment of fibrosis severity from standard MRI scans.
  • Radiomics offers valuable insights into liver tissue characteristics for fibrosis evaluation.