## 3 Results  
### Performance of the Neural Networks to Estimate the Pancreatic PDFF  
The PDFF of six-echo pancreatic head estimated using NLV-Net showed a stronger correlation with the reference (slope: 1.02, rho: 0.95) when compared to U-Net (slope: 0.79, rho: 0.56) and MDWF-Net (slope: 0.79, rho: 0.55) (Figure 3). Bland-Altman analysis showed a similar outcome where NLV-Net had the lowest bias and the narrowest limits of agreement (bias: \(-\)0.0012; LoA: \(-\)0.013, 0.011) when compared to U-Net (bias: \(-\)0.0074; LoA: \(-\)0.035, 0.020) and MDWF-Net (bias: 0.0017; LoA: \(-\)0.028, 0.032) (Figure 4). The Friedman post hoc test indicated that none of the methods showed significant differences to the reference (NLV-Net: \(p\) > 0.99, U-Net: \(p\) = 0.055, MDWF-Net: \(p\) > 0.99).  
Figure 3: Linear regression test of (**a**) NLV-Net, (**b**) U-Net, and (**c**) MDWF-Net against the reference from six-echo pancreatic head.  
For the three-echo pancreatic head, U-Net had the strongest correlation to the six-echo reference in PDFF (slope: 0.99, rho: 0.66), followed by three-echo graph cut (slope: 0.38, rho: 0.51), NLV-Net (slope: 0.44, rho: 0.40), and MDWF-Net (slope: 0.23, rho: 0.30) (Figure 5). However, Bland-Altman analysis indicated that U-Net had the greatest bias and widest LoA (bias: \(-\)0.028; LoA: \(-\)0.051, \(-\)0.0048). MDWF-Net had a smaller bias and LoA (bias: \(-\)0.0026; LoA: \(-\)0.030, 0.024) than NLV-Net (bias: \(-\)0.012; LoA: \(-\)0.038, 0.014) and three-echo graph cut (bias: \(-\)0.012; LoA: \(-\)0.038, 0.015) (Figure 6). The [PERSON] post hoc test suggested that there was no statistical difference between the MDWF-Net and reference (\(p\) > 0.9999), whereas there were significant differences between the reference and NLV-Net (\(p\) = 0.0063), three-echo graph cut (\(p\) = 0.0089), and U-Net (\(p\) < 0.0001).  
In the six-echo pancreatic body, the PDFF from NLV-Net showed a stronger correlation to the reference (slope: 1.04, rho: 0.94) than U-Net (slope: 0.66, rho: 0.57) and MDWF-Net (slope: 0.67, rho: 0.66) (Figure A1). NLV-Net had a lower bias and a narrower LoA (bias: \(-\)0.0014; LoA: \(-\)0.016, 0.013) than U-Net (bias: \(-\)0.0038; LoA: \(-\)0.043, 0.036) and MDWF-Net (bias: 0.0030; LoA: \(-\)0.030, 0.036) (Figure A2). The Friedman test indicated that none of the methods was significantly different to the reference (\(p\) > 0.9999 for all methods).  
Similarly, the three-echo pancreatic body suggested that NLV-Net had the best PDFF agreement with the reference (slope: 0.49, rho: 0.34), followed by the three-echo graph cut (slope: 0.43, rho: 0.32), U-Net (slope: 0.13, rho: 0.050), and MDWF-Net (slope: \(-\)0.11, rho: \(-\)0.082) (Figure A3). NLV-Net had the smallest bias and narrowest LoA (bias: \(-\)0.0032; LoA: \(-\)0.040, 0.034) in comparison to the other methods, the three-echo graph-cut PDFF (bias: \(-\)0.0042; LoA: \(-\)0.043, 0.035), U-Net (bias: \(-\)0.0089; LoA: \(-\)0.056, 0.039), and MDWF-Net (bias: 0.012; LoA: \(-\)0.033, 0.058) (Figure A4). The Friedman test suggested that there were significant differences between the DL models and the reference (\(p\) = 0.0059). However, the Friedman post hoc test suggested that none of the methods was significantly different from the reference (three-echo graph cut: \(p\) = 0.62, NLV-Net: \(p\) > 0.9999, U-Net: \(p\) = 0.46, MDWF-Net: \(p\) = 0.33). There were significant differences between MDWF-Net and U-Net (\(p\) = 0.013) and between MDWF-Net and the three-echo graph cut (\(p\) = 0.039).  
Figure 4: [PERSON]–[PERSON] analysis of six-echo pancreatic head from graph cut against (a) NLV-Net, (b) U-Net, (c) MDWF-Net.