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

感兴趣区域和基于参数图的肝脏质子密度脂肪分数估计在慢性肝病成人中的一致性

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Abstract

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.

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