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Updated: Jan 13, 2026
Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI
Published on: October 20, 2023
Impact of hepatic vessels on whole liver proton density fat fraction and R2* quantification
Ana Jimenez-Pastor1, David Marti-Aguado2,3, Bernardo Pereira4
1Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain. anajimenez@quibim.com.
Objectives:
This study investigated the influence of hepatic vessels on the quantification of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and R2* using automated whole-liver segmentation.
Materials And Methods:
This prospective multicenter study included patients with chronic liver disease having paired liver biopsy and MR exams with a standardized multiecho chemical-shift gradient echo sequence. Automated whole-liver segmentation was performed, generating two masks per patient, one including and the other excluding the major hepatic vessels. PDFF and R2* were quantified and graded for both masks. Histological grading of hepatic steatosis and iron overload severity was used as a reference standard.
Results:
A total of 377 patients were evaluated, of whom 54% had hepatic steatosis and 20% had iron overload on biopsy readings. Stratified by histological grades, there were no statistically significant differences in the distribution of PDFF or R2* between the two segmentation masks. Overall, PDFF and R2* values were minimally lower when vessels were included, with a bias of -0.06% for PDFF and -0.25 s-1 for R2*. A lower coefficient of variation was obtained for both imaging parameters after excluding vessels. Patients were classified in the same PDFF grades despite the segmentation approach, and only 7 cases (1.9% of the study population) were reclassified for R2* grading, all being upgraded after vessel exclusion.
Conclusion:
Excluding hepatic vessels entails nonsignificant differences in PDFF and R2* quantification. Although with limited impact, vessel exclusion improves biomarker precision in research settings demanding high accuracy and increases clinicians' confidence when using automatic tools in clinical practice.
Relevance Statement:
Fat and iron quantification on MRI are key imaging biomarkers for the accurate non-invasive assessment of patients with chronic liver disease. Proton density, fat fraction, and R2* quantification show minimal differences if hepatic vessels are included or excluded from the liver segmentation mask.
Key Points:
The effect of hepatic vessels on proton density, fat fraction, and R2* quantification was evaluated. No significant differences were found, excluding hepatic vessels, although their inclusion showed a small negative bias. Vessel exclusion may improve clinicians' confidence and precision in high-sensitivity applications.
