A preliminary study on automatic measurement of abduction angle after total hip arthroplasty using artificial intelligence algorithm on antero-posterior radiographs
10.3969/j.issn.1002-1671.2024.01.033
- VernacularTitle:利用人工智能算法在双髋正位X线图像上自动测量全髋关节置换术后外展角的研究
- Author:
Kexin WANG
1
,
2
;
Xiaodong ZHANG
;
Pengsheng WU
;
Jialun LI
;
Daojian ZHANG
;
He WANG
Author Information
1. 首都医科大学基础医学院,北京 100069
2. 北京大学第一医院医学影像科,北京 100034
- Keywords:
deep learning;
total hip arthroplasty;
abduction angle;
artificial intelligence;
segmentation
- From:
Journal of Practical Radiology
2024;40(1):140-144
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the feasibility of automating the measurement of abduction angle after total hip arthroplasty(THA)on postoperative radiographs by using deep learning algorithms.Methods The data were retrospectively collected.A total of 381 cases were used to develop deep learning model.Two radiologists annotated the key points on the images(lateral-superior point and medial-inferior point of acetabular cups,tear drops).The data was split into training dataset(304 cases),tuning dataset(38 cases),and test dataset(39 cases).A 2D U-net model was trained to segment the key points and the abduction angle were automatically meas-ured.After development of the model,an external validation dataset was collected(143 cases).Dice similarity coefficient(DSC)and mean absolute error(MAE)were used to evaluate the prediction efficiency of the model in the test dataset and the external validation dataset.Bland-Altman test was used to analyze the agreement between the abduction angle measured automatically by the model and the physician measurement.Results The DSC were 0.870-0.905 and 0.690-0.750 in the test dataset and the external validation dataset,and the corresponding MAE were 0.311-0.561 and 0.951-1.310.For the result of Bland-Altman analysis,only 6.52％(3/46)and 2.08％(3/144)of the abduction angle measurements in the test dataset and external validation dataset were outside the 95％limit of agreement(LoA).In the qualitative evaluation of the abduc-tion angle,the agreement of the model with the physician were 97.8％and 90.3％in the test dataset and the external validation dataset.Conclusion It is feasible to use deep learning algorithms to automatically measure the abduction angle after THA on X-ray images,achieving similar accuracy to that of physician.
