Agreement between region-of-interest- and parametric map-based hepatic proton density fat fraction estimation in adults with chronic liver disease

• Published in: Abdominal imaging Vol. 42; no. 3; pp. 833 - 841
• Main Authors: Manning, Paul M., Hamilton, Gavin, Wang, Kang, Park, Chulhyun, Hooker, Jonathan C., Wolfson, Tanya, Gamst, Anthony, Haufe, William M., Schlein, Alex N., Middleton, Michael S., Sirlin, Claude B.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2017; Springer Nature B.V
• Subjects: Adult; Aged; Algorithms; Chronic Disease; Contrast Media; Cross-Sectional Studies; Fatty Liver - diagnostic imaging; Female; Gadolinium DTPA; Gastroenterology; Hepatology; Humans; Image Interpretation, Computer-Assisted; Imaging; Magnetic Resonance Imaging - methods; Male; Medicine; Medicine & Public Health; Middle Aged; Prospective Studies; Radiology; PDFF; MRI; Proton density fat fraction; Quantitative imaging biomarker; Analysis methods; Hepatic steatosis; QIB; Fat quantification
• ISSN: 2366-004X; 2366-0058
• DOI: 10.1007/s00261-016-0925-2

Purpose To compare agreement between region-of-interest (ROI)- and parametric map-based methods of hepatic proton density fat fraction (PDFF) estimation in adults with known or suspected hepatic steatosis secondary to chronic liver disease over a range of imaging and analysis conditions. Materials and methods In this IRB approved HIPAA compliant prospective single-site study, 31 adults with chronic liver disease undergoing clinical gadoxetic acid-enhanced liver magnetic resonance imaging at 3 T were recruited. Multi-echo gradient-echo imaging at flip angles of 10° and 50° was performed before and after administration of gadoxetic acid. Six echoes were acquired at successive nominally out-of-phase and in-phase echo times. PDFF was estimated with a nonlinear fitting algorithm using the first two, three, four, five, and (all) six echoes. Hence, 20 different imaging and analysis conditions were used (pre/post contrast x low/high flip angle x 2/3/4/5/6 echoes). For each condition, PDFF estimation was done in corresponding liver locations using two methods: a region-of-interest (ROI)-based method in which mean signal intensity values within ROIs were run through the fitting algorithm, and a parametric map-based method in which individual signal intensities were run through the fitting algorithm pixel by pixel. Agreement between ROI- and map-based PDFF estimation was assessed by Bland–Altman and intraclass correlation (ICC) analysis. Results Depending on the condition and method, PDFF ranged from −2.52% to 45.57%. Over all conditions, mean differences between ROI- and map-based PDFF estimates ranged from 0.04% to 0.24%, with all ICCs ≥0.999. Conclusion Agreement between ROI- and parametric map-based PDFF estimation is excellent over a wide range of imaging and analysis conditions.