Diagnostics (May 2024)

Comparison of Vendor-Independent Software Tools for Liver Proton Density Fat Fraction Estimation at 1.5 T

  • Zita Zsombor,
  • Boglárka Zsély,
  • Aladár D. Rónaszéki,
  • Róbert Stollmayer,
  • Bettina K. Budai,
  • Lőrinc Palotás,
  • Viktor Bérczi,
  • Ildikó Kalina,
  • Pál Maurovich Horvat,
  • Pál Novák Kaposi

DOI
https://doi.org/10.3390/diagnostics14111138
Journal volume & issue
Vol. 14, no. 11
p. 1138

Abstract

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(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise modeling (MAG-R), and multi-scale quadratic pseudo-Boolean optimization with graph cut (QPBO). The accuracy and reliability of the methods were evaluated in phantoms with known fat/water ratios and a patient cohort with various grades (S0–S3) of steatosis. Image acquisitions were performed at 1.5 Tesla (T). (3) Results: The PDFF estimates showed a nearly perfect correlation (Pearson r = 0.999, p p p p = 0.005) were lower than MAG-R. The field inhomogeneity artifacts were most frequent in MAG-R (70%) and GC (39%) and absent in QPBO images. (4) Conclusions: The tested algorithms all accurately estimate PDFF in vitro. Meanwhile, QPBO is the least affected by field inhomogeneity artifacts in vivo.

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