• Cheng William Hong, Adrija Mamidipalli, Jonathan C Hooker, Gavin Hamilton, Tanya Wolfson, Dennis H Chen, Soudabeh Fazeli Dehkordy, Michael S Middleton, Scott B Reeder, Rohit Loomba, and Claude B Sirlin.
• Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA.
• J Magn Reson Imaging. 2018 Apr 1; 47 (4): 995-1002.

BackgroundProton density fat fraction (PDFF) estimation requires spectral modeling of the hepatic triglyceride (TG) signal. Deviations in the TG spectrum may occur, leading to bias in PDFF quantification.PurposeTo investigate the effects of varying six-peak TG spectral models on PDFF estimation bias.Study TypeRetrospective secondary analysis of prospectively acquired clinical research data.PopulationForty-four adults with biopsy-confirmed nonalcoholic steatohepatitis.Field Strength/SequenceConfounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy.AssessmentIn each patient, 61 pairs of colocalized MRI-PDFF and MRS-PDFF values were estimated: one pair used the standard six-peak spectral model, the other 60 were six-peak variants calculated by adjusting spectral model parameters over their biologically plausible ranges. MRI-PDFF values calculated using each variant model and the standard model were compared, and the agreement between MRI-PDFF and MRS-PDFF was assessed.Statistical TestsMRS-PDFF and MRI-PDFF were summarized descriptively. Bland-Altman (BA) analyses were performed between PDFF values calculated using each variant model and the standard model. Linear regressions were performed between BA biases and mean PDFF values for each variant model, and between MRI-PDFF and MRS-PDFF.ResultsUsing the standard model, mean MRS-PDFF of the study population was 17.9 ± 8.0% (range: 4.1-34.3%). The difference between the highest and lowest mean variant MRI-PDFF values was 1.5%. Relative to the standard model, the model with the greatest absolute BA bias overestimated PDFF by 1.2%. Bias increased with increasing PDFF (P < 0.0001 for 59 of the 60 variant models). MRI-PDFF and MRS-PDFF agreed closely for all variant models (R2  = 0.980, P < 0.0001).Data ConclusionOver a wide range of hepatic fat content, PDFF estimation is robust across the biologically plausible range of TG spectra. Although absolute estimation bias increased with higher PDFF, its magnitude was small and unlikely to be clinically meaningful.Level Of Evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002.© 2017 International Society for Magnetic Resonance in Medicine.

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