Title:Quantitative Comparison of Liver Volume, Proton Density Fat Fraction, and
Time Burden between Automatic Whole Liver Segmentation and Manual
Sampling MRI Strategies for Diagnosing Metabolic Dysfunction-associated
Steatotic Liver Disease in Obese Patients
Volume: 20
Author(s): Di Cao, Yifan Yang, Mengyi Li, Yang Liu, Dawei Yang, Hui Xu, Han Lv, Zhongtao Zhang, Peng Zhang, Xibin Jia*Zhenghan Yang*
Affiliation:
- Faculty of information technology, Beijing University of Technology, 100 Pingleyuan, Chao-yang District, Beijing 100124, China
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong-an Road, Xi-Cheng District, Beijing 100050, China
Keywords:
MRI-based proton density fat fraction, Sampling strategy, Liver segmentation, Liver volume, Hepatic steatosis, Time burden.
Abstract:
Background:
The performance of automatic liver segmentation and manual sampling MRI strategies needs be compared to determine interchangeability.
Objective:
To compare automatic liver segmentation and manual sampling strategies (manual whole liver segmentation and standardized manual region of
interest) for performance in quantifying liver volume and MRI-proton density fat fraction (MRI-PDFF), identifying steatosis grade, and time
burden.
Methods:
Fifty patients with obesity who underwent liver biopsy and MRI between December 2017 and November 2018 were included. Sampling strategies
included automatic and manual whole liver segmentation and 4 and 9 large regions of interest. Intraclass correlation coefficient (ICC),
Bland–Altman, linear regression, receiver operating characteristic curve, and Pearson correlation analyses were performed.
Results:
Automatic whole liver segmentation liver volume and manual whole liver segmentation liver volume showed excellent agreement (ICC=0.97),
high correlation (R2=0.96), and low bias (3.7%, 95% limits of agreement, -4.8%, 12.2%) in liver volume. There was the best agreement
(ICC=0.99), highest correlation (R2=1.00), and minimum bias (0.84%, 95% limits of agreement, -0.20%, 1.89%) between automated whole liver
segmentation MRI-PDFF and manual whole liver segmentation MRI-PDFF. There was no difference of each paired comparison of receiver
operating characteristic curves for detecting steatosis (P=0.07–1.00). The minimum time burden for automatic whole liver segmentation was 0.32 s
(0.32–0.33 s).
Conclusion:
Automatic measurement has similar effects to manual measurement in quantifying liver volume, MRI-PDFF, and detecting steatosis. Time burden
of automatic whole liver segmentation is minimal among all sampling strategies. Manual measurement can be replaced by automatic measurement
to improve quantitative efficiency.
