Assessment of Liver Fibrosis Using the Coefficient of Variation on Gadoxetic Acid-Enhanced Hepatobiliary Phase MR Imaging: A Prospective Multicenter Study

Background: Accurate non-invasive assessment of liver fibrosis is needed in patients with chronic liver disease. Gadoxetic acid (Gd-EOB-DTPA)-enhanced hepatobiliary phase (HBP) magnetic resonance (MR) imaging reflects hepatocyte function and parenchymal heterogeneity, and the coefficient of variation (CV), which quantifies pixel-level signal inhomogeneity, has been proposed as a quantitative imaging biomarker of liver fibrosis. However, previous studies were retrospective, single-center, and lacked direct pathological validation. Objectives: To investigate the factors associated with CV on HBP images, evaluate the correlation between CV and pathologically confirmed liver fibrosis stage, and compare the diagnostic performance of CV with serum biomarkers, including the aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4), in a prospective multicenter setting. Methods: This prospective multicenter study was conducted between April 2017 and August 2020 at three medical centers. Ninety-nine participants who underwent Gd-EOB-DTPA-enhanced HBP T1-weighted MRI and liver biopsy or surgery were enrolled. CV was measured on HBP images, and the METAVIR fibrosis stage was used as the reference standard. Univariate and multivariable linear regression analyses, including an additional model adjusted for institution and pathology confirmation method, Welch’s analysis of variance with the Games–Howell post hoc test, Spearman’s rank correlation analysis, receiver operating characteristic (ROC) curve analysis with DeLong’s method for AUROC comparison, and intraclass correlation coefficient (ICC) analyses were performed. Results: Ninety-nine participants (64 men and 35 women; mean age, 55.5 ± 15.1 years) were enrolled. In multivariable linear regression analysis adjusted for institution and pathology confirmation method, pathologic fibrosis stage (B = 0.468; 95% CI, 0.358–0.578; p < 0.001) and serum albumin level (B = −0.341; p = 0.015) were independently associated with CV. Spearman’s correlation coefficient between CV and fibrosis stage was 0.74 (p < 0.001). The AUROCs of CV for significant fibrosis (≥F2), advanced fibrosis (≥F3), and cirrhosis (F4) were 0.92, 0.88, and 0.86, respectively (all p < 0.001). CV outperformed APRI and FIB-4 across most fibrosis thresholds (p < 0.001 to p = 0.045), except for FIB-4 in the diagnosis of ≥F2 fibrosis (p = 0.09). The intra- and inter-observer ICC values were 0.94 and 0.84, respectively. Conclusions: In this prospective multicenter study with pathologically confirmed fibrosis stages, CV derived from Gd-EOB-DTPA-enhanced HBP MR images showed a strong correlation with liver fibrosis stage and higher diagnostic performance than APRI and FIB-4 across most fibrosis thresholds. Because CV can be calculated from routine clinical MRI acquisitions without additional hardware or blood tests, it may serve as a practical biomarker for non-invasive liver fibrosis assessment. However, because this study was conducted in a Korean cohort with predominantly hepatitis B virus-related liver disease, further validation in other ethnic groups and etiologies is needed.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-10-15
DOI
https://doi.org/10.3390/jcm15207996
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of Liver Fibrosis Using the Coefficient of Variation on Gadoxetic Acid-Enhanced Hepatobiliary Phase MR Imaging: A Prospective Multicenter Study

Yong Yeon Jeong, Youe Ree Kim, Dong Min Kang, Yousun Ko et al.
Journal of Clinical Medicine
Liver Disease Diagnosis and Treatment
article

Assessment of Liver Fibrosis Using the Coefficient of Variation on Gadoxetic Acid-Enhanced Hepatobiliary Phase MR Imaging: A Prospective Multicenter Study

Yong Yeon Jeong, Youe Ree Kim, Dong Min Kang, Yousun Ko, Youngbin Shin, Chang‐Won Jeong, Kwon‐Ha Yoon, Tae‐Hoon Kim, Kyung Won Kim, Young Hwan Lee, Suk Hee Heo, Keum Ha Choi, Eun Young Cho
article en

Abstract

Background: Accurate non-invasive assessment of liver fibrosis is needed in patients with chronic liver disease. Gadoxetic acid (Gd-EOB-DTPA)-enhanced hepatobiliary phase (HBP) magnetic resonance (MR) imaging reflects hepatocyte function and parenchymal heterogeneity, and the coefficient of variation (CV), which quantifies pixel-level signal inhomogeneity, has been proposed as a quantitative imaging biomarker of liver fibrosis. However, previous studies were retrospective, single-center, and lacked direct pathological validation. Objectives: To investigate the factors associated with CV on HBP images, evaluate the correlation between CV and pathologically confirmed liver fibrosis stage, and compare the diagnostic performance of CV with serum biomarkers, including the aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4), in a prospective multicenter setting. Methods: This prospective multicenter study was conducted between April 2017 and August 2020 at three medical centers. Ninety-nine participants who underwent Gd-EOB-DTPA-enhanced HBP T1-weighted MRI and liver biopsy or surgery were enrolled. CV was measured on HBP images, and the METAVIR fibrosis stage was used as the reference standard. Univariate and multivariable linear regression analyses, including an additional model adjusted for institution and pathology confirmation method, Welch’s analysis of variance with the Games–Howell post hoc test, Spearman’s rank correlation analysis, receiver operating characteristic (ROC) curve analysis with DeLong’s method for AUROC comparison, and intraclass correlation coefficient (ICC) analyses were performed. Results: Ninety-nine participants (64 men and 35 women; mean age, 55.5 ± 15.1 years) were enrolled. In multivariable linear regression analysis adjusted for institution and pathology confirmation method, pathologic fibrosis stage (B = 0.468; 95% CI, 0.358–0.578; p < 0.001) and serum albumin level (B = −0.341; p = 0.015) were independently associated with CV. Spearman’s correlation coefficient between CV and fibrosis stage was 0.74 (p < 0.001). The AUROCs of CV for significant fibrosis (≥F2), advanced fibrosis (≥F3), and cirrhosis (F4) were 0.92, 0.88, and 0.86, respectively (all p < 0.001). CV outperformed APRI and FIB-4 across most fibrosis thresholds (p < 0.001 to p = 0.045), except for FIB-4 in the diagnosis of ≥F2 fibrosis (p = 0.09). The intra- and inter-observer ICC values were 0.94 and 0.84, respectively. Conclusions: In this prospective multicenter study with pathologically confirmed fibrosis stages, CV derived from Gd-EOB-DTPA-enhanced HBP MR images showed a strong correlation with liver fibrosis stage and higher diagnostic performance than APRI and FIB-4 across most fibrosis thresholds. Because CV can be calculated from routine clinical MRI acquisitions without additional hardware or blood tests, it may serve as a practical biomarker for non-invasive liver fibrosis assessment. However, because this study was conducted in a Korean cohort with predominantly hepatitis B virus-related liver disease, further validation in other ethnic groups and etiologies is needed.

Journal of Clinical MedicineVol. 15(20)
Asan Medical Center (KR), Wonkwang University Hospital (KR), Chonnam National University Hwasun Hospital (KR), Wonkwang University (KR)
Bayer Korea
Good health and well-being
Openalex Percentile: Top 13%
Liver Disease Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.