Accuracy of Automated Liver Contouring, Fat Fraction, and R2* Measurement on Gradient Multiecho Magnetic Resonance Images. Issue 5 (September 2018)

• Record Type: Journal Article
• Authors: Stocker, Daniel; Bashir, Mustafa R.; Kannengiesser, Stephan A.R.; Reiner, Cäcilia S.
• Is Part Of: Journal of computer assisted tomography. Volume 42:Issue 5(2018)
• Publication Date: 2018-09
• Subjects: liver fat -- liver iron -- dixon technique; Tomography -- Periodicals; Tomography -- Periodicals; Tomography; Periodicals; 616.0757
• DOI: 10.1097/RCT.0000000000000759
• Languages: English
• ISSNs: 0363-8715

Abstract

Abstract : Objective: This study aimed to evaluate the performance of an automated workflow of volumetric liver proton density fat fraction (PDFFvol ) and R2* quantification with automated inline liver volume (LV) segmentation. Methods: Dual-echo and multiecho Dixon magnetic resonance images were evaluated in 74 consecutive patients (group A, PDFF < 10%; B, PDFF ≥ 10%; C, R2* ≥ 100 s −1 ; D, post-hemihepatectomy). The values of PDFFvol and R2*vol measurements across the LV were generated on multiecho images in an automated fashion based on inline liver segmentation on dual-echo images. Similar measurements were performed manually. Results: Using the inline algorithm, the mis-segmented LV was highest in group D (80%). There were no significant differences between automated and manual measurements of PDFFvol . Automated R2*vol was significantly lower than manual R2*vol in group A ( P = 0.004). Conclusions: Inline LV segmentation performed well in patients without and with hepatic steatosis. In cases with iron overload and post-hemihepatectomy, extrahepatic areas were erroneously included to a greater extent, with a tendency toward overestimation of PDFFvol .