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.

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Current Medical Imaging Reviews Pub Date : 2024-03-07 DOI:10.2174/0115734056282249231206060136
Di Cao, Yifan Yang, Mengyi Li, Yang Liu, Dawei Yang, Hui Xu, Han Lv, Zhongtao Zhang, Peng Zhang, Xibin Jia, Zhenghan Yang
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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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自动全肝分割和手动取样磁共振成像策略在诊断肥胖患者代谢功能障碍相关性脂肪肝时对肝脏体积、质子密度脂肪率和时间负担的定量比较。
背景:需要对自动肝脏分割和手动取样 MRI 策略的性能进行比较,以确定其互换性:需要对自动肝脏分割和手动取样 MRI 策略的性能进行比较,以确定其互换性:比较自动肝脏分割和手动取样策略(手动全肝分割和标准化手动感兴趣区)在量化肝脏体积和 MRI 质子密度脂肪分数(MRI-PDFF)、确定脂肪变性等级和时间负担方面的性能:纳入2017年12月至2018年11月期间接受肝活检和MRI检查的50名肥胖症患者。取样策略包括自动和手动全肝分割以及 4 个和 9 个大的感兴趣区。进行了类内相关系数(ICC)、Bland-Altman、线性回归、接收者操作特征曲线和皮尔逊相关分析:自动全肝分割肝脏体积和手动全肝分割肝脏体积显示出极好的一致性(ICC=0.97)、高相关性(R2=0.96)和低偏差(3.7%,95%的一致性范围,-4.8%,12.2%)。自动全肝分割 MRI-PDFF 与手动全肝分割 MRI-PDFF 的一致性最好(ICC=0.99),相关性最高(R2=1.00),偏差最小(0.84%,95% 的一致性范围,-0.20%,1.89%)。在检测脂肪变性方面,接收者操作特征曲线的配对比较没有差异(P=0.07-1.00)。自动全肝分割的最短时间为0.32秒(0.32-0.33秒):结论:在量化肝脏体积、MRI-PDFF 和检测脂肪变性方面,自动测量与手动测量效果相似。在所有采样策略中,自动全肝分割的时间负担最小。自动测量可取代人工测量,提高定量效率。
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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
246
审稿时长
1 months
期刊介绍: Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques. The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.
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