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

Di Cao; Yifan Yang; Mengyi Li; Yang Liu; Dawei Yang; Hui Xu; Han Lv; Zhongtao Zhang; Peng Zhang; Xibin Jia; Zhenghan Yang

doi:10.2174/0115734056282249231206060136

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

Curr Med Imaging. 2024 Mar 7. doi: 10.2174/0115734056282249231206060136. Online ahead of print.

Authors

Di Cao¹, Yifan Yang², Mengyi Li³, Yang Liu³, Dawei Yang¹, Hui Xu¹, Han Lv¹, Zhongtao Zhang³, Peng Zhang³, Xibin Jia², Zhenghan Yang¹

Affiliations

¹ Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong-an Road, Xi-Cheng District, Beijing 100050, China.
² Beijing University of Technology, 100 Pingleyuan, Chao-Yang District, Beijing 100124, China.
³ Department of General Surgery, Beijing Friendship Hospital, Capital Medical University & National Clinical Research Center for Digestive Diseases, No. 95 Yong-an Road, Xi-Cheng District, Beijing 100050, China.

PMID: 38462830
DOI: 10.2174/0115734056282249231206060136

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.

Keywords: MRI-based proton density fat fraction; hepatic steatosis; liver segmentation; liver volume; sampling strategy; time burden.