# Impact of hepatic vessels on whole liver proton density fat fraction and R2* quantification

## TL;DR

This study found that including or excluding hepatic vessels in MRI scans has minimal impact on measuring liver fat and iron levels, though excluding vessels slightly improves precision.

## Contribution

The study demonstrates that excluding hepatic vessels in liver MRI segmentation has minimal effect on PDFF and R2* quantification but improves precision in high-accuracy settings.

## Key findings

- Excluding hepatic vessels resulted in minimal bias for PDFF (-0.06%) and R2* (-0.25 s-1).
- Only 1.9% of patients were reclassified for R2* grading after excluding vessels.
- Vessel exclusion led to lower coefficient of variation for PDFF and R2* measurements.

## Abstract

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.

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.

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.

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.

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.

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.

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.