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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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Research Article

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

Author(s): Di Cao, Yifan Yang, Mengyi Li, Yang Liu, Dawei Yang, Hui Xu, Han Lv, Zhongtao Zhang, Peng Zhang, Xibin Jia* and Zhenghan Yang*

Volume 20, 2024

Published on: 07 March, 2024

Article ID: e15734056282249 Pages: 17

DOI: 10.2174/0115734056282249231206060136

Price: $65

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.

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