人工智能辅助半自动分割软件在肝脏血管瘤CT测量中的应用  

Clinical application evaluation of artificial intelligence-assisted semi-automatic segmentation software for liver hemangiomas

作　　者：肖兰 陈友三 卢翼 肖诗银 李锦巍[1] 杨磊[1] XIAO Lan;CHEN You-san;LU Yi(Department of radiology.Traditional Chinese Medicine Hospital(Wuhan Hubei,430074),China.)

机构地区：[1]湖北省中医院放射科,湖北武汉430074

出　　处：《中西医结合肝病杂志》2024年第12期1132-1135,共4页Chinese Journal of Integrated Traditional and Western Medicine on Liver Diseases

基　　金：湖北省中医院院内科研项目(No.2021YJKT-19)。

摘　　要：目的:评估一种人工智能(AI)辅助的半自动分割软件在肝脏血管瘤CT测量上的应用的表现。方法:回顾性分析2022年2月至2023年2月收治的52例肝脏血管瘤患者的临床资料。采用联影医疗基于深度学习技术开发的肝脏血管瘤分析软件,由两名医生独立、单盲对52个肝脏血管瘤的多排螺旋计算机断层扫描(MSCT)图像进行手动分割和AI辅助的半自动分割,对其最长径及体积进行了手动和半自动的重复测量,并运用Bland-Altman方法评估两种模式下观察者内及观察者间的差异。利用组内相关系数(ICC)来评估两种模式下测量的一致性。结果:肝血管瘤病灶最长径测量中,观察者内手动、半自动测量偏移均值95%一致性区间分别为-0.70~0.55、-0.52~0.48,观察者间手动、半自动测量偏移均值95%一致性区间分别为-0.15~1.24、-0.76~0.64。肝血管瘤病灶体积测量中,观察者内纯手动、半自动测量偏移均值95%一致性区间分别为-5.95~6.79、-3.84~3.23,观察者间手动、半自动测量偏移均值95%一致性区间分别为-8.04~5.56、-6.52~5.88。观察者内手动、半自动最长径测量变异度的ICC分别为0.901、0.976,观察者间手动、半自动最长径测量变异度的ICC分别为0.865、0.892。观察者内手动、半自动体积测量变异度的ICC分别为0.907、0.982,观察者间手动、半自动体积测量变异度的ICC分别为0.825、0.913。相对于手动分割病灶,使用AI辅助的肝血管瘤自动分割软件进行半自动病灶分割所需要的时间大大缩短[(26.00±4.82)s vs(7.23±2.89)s,t=-24.289,P<0.01]。结论:AI辅助的半自动分割软件在肝脏血管瘤的分割中展现出良好的观察者内及观察者间的一致性,并显著提高了分割效率,减少了临床工作所需时间,有潜力成为临床随访和疗效评估的定量分析工具。Objective:This study aimed to evaluate the performance of an artificial intelligence(AI)-assisted semi-automatic segmentation software in the segmentation of hepatic hemangiomas and compare it with traditional manual segmentation methods to determine if it can reduce intra-and inter-observer variability.Methods:A retrospective analysis was conducted on the clinical data of 52 patients with hepatic hemangiomas admitted from February 2022 to February 2023.A liver hemangioma analysis software developed by United Imaging Healthcare,based on deep learning technology,was used.Two physicians independently and blindly performed manual segmentation and AI-assisted semi-automatic segmentation of multi-slice spiral computed tomography(MSCT)images of the 52 hepatic hemangiomas.The longest diameter and volume were measured repeatedly using both manual and semi-automatic methods.Bland-Altman analysis was applied to assess intra-observer and inter-observer variability under both modes.The intraclass correlation coefficient(ICC)was used to evaluate the consistency of measurements between the two modes.Results:For the longest diameter measurement of liver hemangioma lesions,the mean deviations for intra-observer manual and semi-automatic measurements were-0.70 to 0.55 and-0.52 to 0.48,respectively,with 95%limits of agreement.Inter-observer mean deviations were-0.15 to 1.24 for manual and-0.76 to 0.64 for semi-automatic measurements.For volume measurement,intra-observer mean deviations for manual and semi-automatic were-5.95 to 6.79 and-3.84 to 3.23,respectively,and inter-observer mean deviations were-8.04 to 5.56 for manual and-6.52 to 5.88 for semi-automatic.The ICC for intra-observer variability in the longest diameter measurement was 0.901 for manual and 0.976 for semi-automatic,and for inter-observer variability was 0.865 for manual and 0.892 for semi-automatic.For volume measurement,the ICC for intra-observer variability was 0.907 for manual and 0.982 for semi-automatic,and for inter-observer variability was 0.825 for manual

关 键 词：肝脏血管瘤 人工智能 半自动分割软件 多排螺旋计算机断层扫描 

分 类 号：R575[医药卫生—消化系统]