Peter Bannas1,2, Harald Kramer1,3, Diego Hernando1, Rashmi Agni4, Ashley M Cunningham4, Rakesh Mandal4, Utaroh Motosugi1, Samir D Sharma1, Alejandro Munoz del Rio1, Luis Fernandez5, Scott B Reeder1,6,7,8,9. 1. Department of Radiology, University of Wisconsin-Madison, Madison, WI. 2. Department of Radiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany. 3. Department of Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany. 4. Department of Pathology, University of Wisconsin-Madison, Madison, WI. 5. Department of Surgery, University of Wisconsin-Madison, Madison, WI. 6. Department of Medical Physics, University of Wisconsin-Madison, Madison, WI. 7. Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI. 8. Department of Medicine, University of Wisconsin-Madison, Madison, WI. 9. Department of Emergency Medicine, University of Wisconsin-Madison, Madison, WI.
Abstract
UNLABELLED: Emerging magnetic resonance imaging (MRI) biomarkers of hepatic steatosis have demonstrated tremendous promise for accurate quantification of hepatic triglyceride concentration. These methods quantify the proton density fat-fraction (PDFF), which reflects the concentration of triglycerides in tissue. Previous in vivo studies have compared MRI-PDFF with histologic steatosis grading for assessment of hepatic steatosis. However, the correlation of MRI-PDFF with the underlying hepatic triglyceride content remained unknown. The aim of this ex vivo study was to validate the accuracy of MRI-PDFF as an imaging biomarker of hepatic steatosis. Using ex vivo human livers, we compared MRI-PDFF with magnetic resonance spectroscopy-PDFF (MRS-PDFF), biochemical triglyceride extraction, and histology as three independent reference standards. A secondary aim was to compare the precision of MRI-PDFF relative to biopsy for the quantification of hepatic steatosis. MRI-PDFF was prospectively performed at 1.5 Tesla in 13 explanted human livers. We performed colocalized paired evaluation of liver fat content in all nine Couinaud segments using single-voxel MRS-PDFF (n=117) and tissue wedges for biochemical triglyceride extraction (n=117), and five core biopsies performed in each segment for histologic grading (n=585). Accuracy of MRI-PDFF was assessed through linear regression with MRS-PDFF, triglyceride extraction, and histology. Intraobserver agreement, interobserver agreement, and repeatability of MRI-PDFF and histologic grading were assessed through Bland-Altman analyses. MRI-PDFF showed an excellent correlation with MRS-PDFF (r=0.984, confidence interval 0.978-0.989) and strong correlation with histology (r=0.850, confidence interval 0.791-0.894) and triglyceride extraction (r=0.871, confidence interval 0.818-0.909). Intraobserver agreement, interobserver agreement, and repeatability showed a significantly smaller variance for MRI-PDFF than for histologic steatosis grading (all P<0.001). CONCLUSION: MRI-PDFF is an accurate, precise, and reader-independent noninvasive imaging biomarker of liver triglyceride content, capable of steatosis quantification over the entire liver.
UNLABELLED: Emerging magnetic resonance imaging (MRI) biomarkers of hepatic steatosis have demonstrated tremendous promise for accurate quantification of hepatic triglyceride concentration. These methods quantify the proton density fat-fraction (PDFF), which reflects the concentration of triglycerides in tissue. Previous in vivo studies have compared MRI-PDFF with histologic steatosis grading for assessment of hepatic steatosis. However, the correlation of MRI-PDFF with the underlying hepatic triglyceride content remained unknown. The aim of this ex vivo study was to validate the accuracy of MRI-PDFF as an imaging biomarker of hepatic steatosis. Using ex vivo human livers, we compared MRI-PDFF with magnetic resonance spectroscopy-PDFF (MRS-PDFF), biochemical triglyceride extraction, and histology as three independent reference standards. A secondary aim was to compare the precision of MRI-PDFF relative to biopsy for the quantification of hepatic steatosis. MRI-PDFF was prospectively performed at 1.5 Tesla in 13 explanted human livers. We performed colocalized paired evaluation of liver fat content in all nine Couinaud segments using single-voxel MRS-PDFF (n=117) and tissue wedges for biochemical triglyceride extraction (n=117), and five core biopsies performed in each segment for histologic grading (n=585). Accuracy of MRI-PDFF was assessed through linear regression with MRS-PDFF, triglyceride extraction, and histology. Intraobserver agreement, interobserver agreement, and repeatability of MRI-PDFF and histologic grading were assessed through Bland-Altman analyses. MRI-PDFF showed an excellent correlation with MRS-PDFF (r=0.984, confidence interval 0.978-0.989) and strong correlation with histology (r=0.850, confidence interval 0.791-0.894) and triglyceride extraction (r=0.871, confidence interval 0.818-0.909). Intraobserver agreement, interobserver agreement, and repeatability showed a significantly smaller variance for MRI-PDFF than for histologic steatosis grading (all P<0.001). CONCLUSION: MRI-PDFF is an accurate, precise, and reader-independent noninvasive imaging biomarker of liver triglyceride content, capable of steatosis quantification over the entire liver.
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