Accuracy of automated liver contouring, fat fraction, and R2* measurement on gradient multiecho magnetic resonance images

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; 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.