_version_ 1866902172961079296
author Jimenez-Pastor, A
Marti-Aguado, D
Pereira, B
Alfaro-Cervello, C
Perez-Girbes, A
Alberich-Bayarri, A
Marti-Bonmati, L
author_facet Jimenez-Pastor, A
Marti-Aguado, D
Pereira, B
Alfaro-Cervello, C
Perez-Girbes, A
Alberich-Bayarri, A
Marti-Bonmati, L
contents ObjectivesThis 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 methodsThis 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.ResultsA 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.ConclusionExcluding 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 statementFat 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 PointsThe 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.
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id zenodo_https___doi_org_10_1186_s41747-025-00663-1
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Impact of hepatic vessels on whole liver proton density fat fraction and R2*quantification
Jimenez-Pastor, A
Marti-Aguado, D
Pereira, B
Alfaro-Cervello, C
Perez-Girbes, A
Alberich-Bayarri, A
Marti-Bonmati, L
adolescent
adult
aged
Article
body mass
chronic liver disease
clinical practice
cohort analysis
fat mass
female
histology
human
human tissue
image analysis
image quality
liver biopsy
liver blood vessel
major clinical study
male
multicenter study
nuclear magnetic resonance imaging
prospective study
R2 quantification
T2 weighted imaging
whole liver proton density fat fraction
biopsy
clinical trial
diagnostic imaging
fatty liver
liver
middle aged
pathology
procedures
vascularization
proton
Adult
Aged
Biopsy
Fatty Liver
Female
Humans
Liver
Magnetic Resonance Imaging
Male
Middle Aged
Prospective Studies
Protons
ObjectivesThis 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 methodsThis 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.ResultsA 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.ConclusionExcluding 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 statementFat 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 PointsThe 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.
title Impact of hepatic vessels on whole liver proton density fat fraction and R2*quantification
topic adolescent
adult
aged
Article
body mass
chronic liver disease
clinical practice
cohort analysis
fat mass
female
histology
human
human tissue
image analysis
image quality
liver biopsy
liver blood vessel
major clinical study
male
multicenter study
nuclear magnetic resonance imaging
prospective study
R2 quantification
T2 weighted imaging
whole liver proton density fat fraction
biopsy
clinical trial
diagnostic imaging
fatty liver
liver
middle aged
pathology
procedures
vascularization
proton
Adult
Aged
Biopsy
Fatty Liver
Female
Humans
Liver
Magnetic Resonance Imaging
Male
Middle Aged
Prospective Studies
Protons
url https://doi.org/10.1186/s41747-025-00663-1