Multi-vendor, multi-field strength validation of MRI-Proton density fat fraction for fat quantification: A standardized phantom study

BACKGROUND/PURPOSE: This study aimed to validate the accuracy and consistency of Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF) across systems from three major vendors at two field strengths. METHODS: A PDFF phantom with five calibrated values (0%, 10%, 20%, 30%, and 40%) was scanned at six hospitals. The platforms included GE, Siemens, and Philips systems at both 1.5T and 3.0T, utilizing corresponding commercial PDFF sequences. Correlation with reference values was assessed using Pearson's correlation coefficient (r). Overall agreement and systematic bias were evaluated using the Concordance Correlation Coefficient (CCC) and Bland-Altman analysis, respectively. Finally, linearly weighted Kappa (κ) statistics were used to evaluate agreement for clinical steatosis grading. RESULTS: All evaluated systems exhibited an excellent correlation with reference values, yielding a Pearson correlation coefficient (r) > 0.99 (p < 0.0001). The overall agreement measured by CCC was also excellent, ranging from 0.9797 to 0.9964. Bland-Altman analysis revealed no statistically significant bias for Siemens platforms (p > 0.05). However, a small but statistically significant systematic underestimation was observed for GE (mean bias: 1.7 to -1.9%) and Philips (mean bias: 2.1 to -2.7%) platforms (p < 0.0001). Weighted Kappa analysis showed excellent to perfect agreement for steatosis grading (κ = 0.83 to 1.00). CONCLUSION: MRI-PDFF is an accurate, precise, and consistent biomarker for liver fat quantification across different vendors and field strengths. The minor, systematic inter-vendor biases observed are likely due to proprietary algorithmic differences and, while quantitatively small, highlight the need for harmonization in multi-center clinical trials.

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Journal
Journal of the Formosan Medical Association
Published
2026-04-01
DOI
https://doi.org/10.1016/j.jfma.2026.04.011
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Multi-vendor, multi-field strength validation of MRI-Proton density fat fraction for fat quantification: A standardized phantom study

Yueh‐Hsun Lu, Li-pin CHEN, Kuang-Chen Yen, Chih-Horng Wu et al.
Journal of the Formosan Medical Association
Advanced MRI Techniques and Applications
article

Multi-vendor, multi-field strength validation of MRI-Proton density fat fraction for fat quantification: A standardized phantom study

Yueh‐Hsun Lu, Li-pin CHEN, Kuang-Chen Yen, Chih-Horng Wu, Chia-Hsun Lu, Cheng-Fu Ni
article en

Abstract

BACKGROUND/PURPOSE: This study aimed to validate the accuracy and consistency of Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF) across systems from three major vendors at two field strengths. METHODS: A PDFF phantom with five calibrated values (0%, 10%, 20%, 30%, and 40%) was scanned at six hospitals. The platforms included GE, Siemens, and Philips systems at both 1.5T and 3.0T, utilizing corresponding commercial PDFF sequences. Correlation with reference values was assessed using Pearson's correlation coefficient (r). Overall agreement and systematic bias were evaluated using the Concordance Correlation Coefficient (CCC) and Bland-Altman analysis, respectively. Finally, linearly weighted Kappa (κ) statistics were used to evaluate agreement for clinical steatosis grading. RESULTS: All evaluated systems exhibited an excellent correlation with reference values, yielding a Pearson correlation coefficient (r) > 0.99 (p < 0.0001). The overall agreement measured by CCC was also excellent, ranging from 0.9797 to 0.9964. Bland-Altman analysis revealed no statistically significant bias for Siemens platforms (p > 0.05). However, a small but statistically significant systematic underestimation was observed for GE (mean bias: 1.7 to -1.9%) and Philips (mean bias: 2.1 to -2.7%) platforms (p < 0.0001). Weighted Kappa analysis showed excellent to perfect agreement for steatosis grading (κ = 0.83 to 1.00). CONCLUSION: MRI-PDFF is an accurate, precise, and consistent biomarker for liver fat quantification across different vendors and field strengths. The minor, systematic inter-vendor biases observed are likely due to proprietary algorithmic differences and, while quantitatively small, highlight the need for harmonization in multi-center clinical trials.

Journal of the Formosan Medical Association
National Taiwan University (TW), Taipei Medical University Hospital (TW), National Taiwan University Hospital (TW), Wan Fang Hospital (TW), Taipei Medical University-Shuang Ho Hospital (TW), Taipei Medical University (TW)
National Taiwan University Hospital
Openalex Percentile: Top 21%
Advanced MRI Techniques and Applications
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