评估人工智能模型自动测量婴儿髋关节发育指标的临床应用价值。

选取2019年1月至11月于广东省妇幼保健院超声科进行髋关节超声检查的婴儿231例（共462张标准髋关节图片），使用组内相关系数（ICC）、Deming回归对高年资医师与人工智能测量髋关节数据进行一致性分析，使用ICC对高年资医师、低年资医师、人工智能测量数据进行观察者间一致性分析，对高年资与低年资医师测量数据进行观察者内一致性分析。

高年资医师与人工智能测量α角和β角的ICC分别为0.823、0.745；Deming回归斜率分别为0.856、1.205；回归残差图围绕参考线相对对称。高年资医师与低年资医师测量α角的ICC为0.77，β角的ICC为0.70；低年资医师与人工智能测量α角的ICC为0.79，β角的ICC为0.71；高年资医师与人工智能测量α角的ICC为0.87，β角的ICC为0.79。高年资医师测量2次α角的ICC为0.89，β角的ICC为0.84；低年资医师测量2次α角的ICC为0.88，β角的ICC为0.82。

深度学习的人工智能模型测量髋关节数据与医师测量数据一致性好，且更接近高年资医师测量水平，可辅助超声医师进行临床早期筛查和诊断。

To evaluate the clinical value of artificial intelligence model for automatic measurement of infant hip joint development.

A total of 231 infants who underwent hip joint ultrasonic examination (with 462 standard hip joint images) at the Ultrasound Diagnosis Department of Guangdong Women and Children Hospital from January to November 2019 were selected. Intraclass correlation coefficient (ICC) and Deming regression were used for consistency analysis of measurement data of hip joint between a senior sonographer and artificial intelligence. ICC was used for consistency analysis of measurement data between a senior sonographer, a junior sonographer, and artificial intelligence, and for intra-observer agreement of the senior sonographer and junior sonographer.

The ICCs of α angle and β angle measured by the senior sonographer and artificial intelligence were 0.823 and 0.745, respectively; Deming regression slopes were 0.856 and 1.205, respectively, and regression residual plots were relatively symmetric. The ICCs of α angle and β angle measured by the senior sonographer and junior sonographer were 0.77 and 0.70, the ICCs of α angle and β angle measured by the junior sonographer and artificial intelligence were 0.79 and 0.71, and the ICCs of α angle and β angle measured by the senior sonographer and artificial intelligence was 0.87 and 0.79. The ICC of α angle double measured by the senior sonographer was 0.89, and the ICC of β angle was 0.84. The ICC of α angle double measured by the junior sonographer was 0.88, and the ICC of β angle was 0.82.

There is good data consistency between the deep learning-based artificial intelligence model and sonographers in measuring infant hip joints. The accuracy of artificial intelligence is closer to that of senior sonographer, and it can be used to assist in clinical ultrasound screening and diagnosis.