背景:需要比较自动肝脏分割和手动采样MRI策略的性能,以确定互换性。
目的:为了比较自动肝脏分割和手动采样策略(手动整个肝脏分割和标准化手动感兴趣区域)在量化肝脏体积和MRI质子密度脂肪分数(MRI-PDFF)方面的性能,确定脂肪变性等级,时间负担。
方法:纳入了在2017年12月至2018年11月期间接受肝活检和MRI检查的50例肥胖患者。采样策略包括自动和手动整个肝脏分割以及4个和9个大的感兴趣区域。组内相关系数(ICC),Bland-Altman,线性回归,接收机工作特性曲线,并进行Pearson相关分析。
结果:自动全肝分割肝脏体积和手动全肝分割肝脏体积表现出极好的一致性(ICC=0.97),高相关性(R2=0.96),和低偏差(3.7%,95%的协议限制,-4.8%,12.2%)在肝脏体积中。有最好的协议(ICC=0.99),最高相关性(R2=1.00),和最小偏差(0.84%,95%的协议限制,-0.20%,1.89%)在自动全肝分割MRI-PDFF和手动全肝分割MRI-PDFF之间。检测脂肪变性的受试者工作特征曲线的每个配对比较没有差异(P=0.07-1.00)。自动全肝分割的最小时间负担为0.32s(0.32-0.33s)。
结论:自动测量在定量肝脏体积方面与手动测量具有相似的效果,MRI-PDFF,并检测脂肪变性。在所有采样策略中,自动整个肝脏分割的时间负担最小。手动测量可以由自动测量代替,以提高定量效率。
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).
CONCLUSIONS: 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.