Cheng William Hong1, Adrija Mamidipalli1, Jonathan C Hooker1, Gavin Hamilton1, Tanya Wolfson2, Dennis H Chen1, Soudabeh Fazeli Dehkordy1, Michael S Middleton1, Scott B Reeder3, Rohit Loomba4, Claude B Sirlin1. 1. Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA. 2. Computational and Applied Statistics Laboratory, University of California San Diego, San Diego, California, USA. 3. Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin Madison, Madison, Wisconsin. 4. NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California San Diego, San Diego, California, USA.
Abstract
BACKGROUND: Proton 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. PURPOSE: To investigate the effects of varying six-peak TG spectral models on PDFF estimation bias. STUDY TYPE: Retrospective secondary analysis of prospectively acquired clinical research data. POPULATION: Forty-four adults with biopsy-confirmed nonalcoholic steatohepatitis. FIELD STRENGTH/SEQUENCE: Confounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy. ASSESSMENT: In 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 TESTS: MRS-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. RESULTS: Using 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 CONCLUSION: Over 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 EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002.
BACKGROUND: Proton 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. PURPOSE: To investigate the effects of varying six-peak TG spectral models on PDFF estimation bias. STUDY TYPE: Retrospective secondary analysis of prospectively acquired clinical research data. POPULATION: Forty-four adults with biopsy-confirmed nonalcoholic steatohepatitis. FIELD STRENGTH/SEQUENCE: Confounder-corrected chemical-shift-encoded 3T MRI (using a 2D multiecho gradient-recalled echo technique with magnitude reconstruction) and MR spectroscopy. ASSESSMENT: In 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 TESTS: MRS-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. RESULTS: Using 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 CONCLUSION: Over 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 EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:995-1002.
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