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Clinical Validation of Deep-learning Approach to Estimate Proton-Density Fat Fraction from In-phase and Out-of-phase T1-weighted MRI

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AI-IOP PDFF closely matched CSE-PDFF, suggesting high accuracy for liver fat quantification.
The deep-learning method outperformed conventional Dixon SFF in liver fat estimation accuracy.
External validation confirmed the reliability of AI-IOP across diverse settings, indicating robustness.
Findings may enhance diagnosis of metabolic-associated steatohepatitis where advanced methods are inaccessible.

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Analysis evaluates deep-learning estimation of proton-density fat fraction in MRI, suggesting improvements for liver fat quantification.

Yavuz et al. (2025) studied this question.

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