Purpose: To investigate the feasibility of estimating the proton-density fat fraction (PDFF) using a 7.1T magnetic resonance imaging (MRI) system and to compare the accuracy of liver fat quantification using different fitting approaches. Materials and Methods: Fourteen leptin-deficient ob/ob mice and eight intact controls were examined in a 7.1T animal scanner using a 3D six-echo chemical shift-encoded pulse sequence. Confounder-corrected PDFF was calculated using magnitude (magnitude data alone) and combined fitting (complex and magnitude data). Differences between fitting techniques were compared using Bland–Altman analysis. In addition, PDFFs derived with both reconstructions were correlated with histopathological fat content and triglyceride mass fraction using linear regression analysis. Results: The PDFFs determined with the use of both reconstructions correlated very strongly (r = 0.91). However, small mean bias between reconstructions demonstrated divergent results (3.9%; confidence interval [CI] 2.7–5.1%). For both reconstructions, there was linear correlation with histopathology (combined fitting: r = 0.61; magnitude fitting: r = 0.64) and triglyceride content (combined fitting: r = 0.79; magnitude fitting: r = 0.70). Conclusion: Liver fat quantification using the PDFF derived from MRI performed at 7.1T is feasible. PDFF has strong correlations with histopathologically determined fat and with triglyceride content. However, small differences between PDFF reconstruction techniques may impair the robustness and reliability of the biomarker at 7.1T. J. Magn. Reson. Imaging 2016;44:1425–1431.

Quantification of liver proton-density fat fraction in 7.1T preclinical MR systems: Impact of the fitting technique

Cigliano A.;
2016-01-01

Abstract

Purpose: To investigate the feasibility of estimating the proton-density fat fraction (PDFF) using a 7.1T magnetic resonance imaging (MRI) system and to compare the accuracy of liver fat quantification using different fitting approaches. Materials and Methods: Fourteen leptin-deficient ob/ob mice and eight intact controls were examined in a 7.1T animal scanner using a 3D six-echo chemical shift-encoded pulse sequence. Confounder-corrected PDFF was calculated using magnitude (magnitude data alone) and combined fitting (complex and magnitude data). Differences between fitting techniques were compared using Bland–Altman analysis. In addition, PDFFs derived with both reconstructions were correlated with histopathological fat content and triglyceride mass fraction using linear regression analysis. Results: The PDFFs determined with the use of both reconstructions correlated very strongly (r = 0.91). However, small mean bias between reconstructions demonstrated divergent results (3.9%; confidence interval [CI] 2.7–5.1%). For both reconstructions, there was linear correlation with histopathology (combined fitting: r = 0.61; magnitude fitting: r = 0.64) and triglyceride content (combined fitting: r = 0.79; magnitude fitting: r = 0.70). Conclusion: Liver fat quantification using the PDFF derived from MRI performed at 7.1T is feasible. PDFF has strong correlations with histopathologically determined fat and with triglyceride content. However, small differences between PDFF reconstruction techniques may impair the robustness and reliability of the biomarker at 7.1T. J. Magn. Reson. Imaging 2016;44:1425–1431.
2016
chemical shift imaging
liver fat
proton-density fat fraction
ultra-high-field MRI
Algorithms
Animals
Biomarkers
Densitometry
Fats
Feasibility Studies
Image Interpretation
Computer-Assisted
Liver
Magnetic Resonance Imaging
Male
Mice
Mice
Inbred C57BL
Mice
Knockout
Molecular Imaging
Numerical Analysis
Computer-Assisted
Protons
Reproducibility of Results
Sensitivity and Specificity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14245/16163
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