Whole-Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis

You Zheng; Yong-Sheng Xu; Zhao Liu; Hai-Feng Liu; Ya-Nan Zhai; Xiao-Rong Mao; Jun-Qiang Lei

doi:10.1002/jmri.26987

Whole-Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis

J Magn Reson Imaging. 2020 Jun;51(6):1745-1754. doi: 10.1002/jmri.26987. Epub 2019 Nov 15.

Authors

You Zheng^{1

2}, Yong-Sheng Xu¹, Zhao Liu¹, Hai-Feng Liu³, Ya-Nan Zhai¹, Xiao-Rong Mao⁴, Jun-Qiang Lei¹

Affiliations

¹ First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China.
² Department of Radiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China.
³ Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China.
⁴ Department of Infectious Diseases, First Hospital of Lanzhou University, Lanzhou, Gansu, China.

PMID: 31729811
DOI: 10.1002/jmri.26987

Abstract

Background: Conventional diffusion-weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole-liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis.

Purpose: To explore the value of whole-liver ADC histogram parameters in the diagnosis and staging of liver fibrosis.

Study type: Retrospective.

Population: Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients.

Field strength/sequence: 3.0T/T₁ -weighted, T₂ -weighted, and diffusion-weighted images.

Assessment: A region of interest (ROI) was drawn in each slice of the diffusion-weighted images. Whole-liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed.

Statistical tests: Mann-Whitney U-test and receiver operating characteristic curve analysis.

Results: Kurtosis, entropy, skewness, mode, and 90^th and 75^th percentiles exhibited significant differences among the pathological fibrosis stages (P < 0.05). Kurtosis was found to be the most meaningful parameter in differentiating fibrosis stages of the viral hepatitis, autoimmune hepatitis, and unexplained liver fibrosis group (area under the curve) (AUC = 0.793, 0.771, 0.798, respectively). In the combined liver fibrosis group, kurtosis achieved the highest AUC (0.801; 95% confidence interval [CI]: 0.702-0.900; sensitivity: 0.750; specificity: 0.850; positive likelihood ratio: 4.953; negative likelihood ratio: 0.302; positive predictive value: 0.946; negative predictive value: 0.486), with a cutoff value of 1.817, in differentiating fibrosis stage ≥F1.

Data conclusion: Kurtosis, entropy, skewness, mode, and 90^th and 75^th percentiles may contribute to the diagnosis and staging of liver fibrosis, especially kurtosis.

Level of evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1745-1754.

Keywords: apparent diffusion coefficient; histogram; liver fibrosis; magnetic resonance imaging.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Diffusion Magnetic Resonance Imaging*
Humans
Image Interpretation, Computer-Assisted*
Liver Cirrhosis / diagnostic imaging
ROC Curve
Retrospective Studies
Sensitivity and Specificity

Grants and funding

U24 EB028980/EB/NIBIB NIH HHS/United States