Kabir Mohammad Humayun, Reformat Marek, Hryniuk Sarah Southon, Stampe Kyle, Lou Edmond
Department of Electrical and Computer Engineering, University of Alberta, 11-263 Donadeo Innovation Centre for Engineering, 9211-116 St, Edmonton, AB, T6G 1H9, Canada.
Department of Surgery, University of Alberta, Edmonton, AB, Canada.
Med Biol Eng Comput. 2025 Jan;63(1):101-110. doi: 10.1007/s11517-024-03181-1. Epub 2024 Aug 16.
The magnetically controlled growing rod technique is an effective surgical treatment for children who have early-onset scoliosis. The length of the instrumented growing rods is adjusted regularly to compensate for the normal growth of these patients. Manual measurement of rod length on posteroanterior spine radiographs is subjective and time-consuming. A machine learning (ML) system using a deep learning approach was developed to automatically measure the adjusted rod length. Three ML models-rod model, 58 mm model, and head-piece model-were developed to extract the rod length from radiographs. Three-hundred and eighty-seven radiographs were used for model development, and 60 radiographs with 118 rods were separated for final testing. The average precision (AP), the mean absolute difference (MAD) ± standard deviation (SD), and the inter-method correlation coefficient (ICC) between the manual and artificial intelligence (AI) adjustment measurements were used to evaluate the developed method. The AP of the 3 models were 67.6%, 94.8%, and 86.3%, respectively. The MAD ± SD of the rod length change was 0.98 ± 0.88 mm, and the ICC was 0.90. The average time to output a single rod measurement was 6.1 s. The developed AI provided an accurate and reliable method to detect the rod length automatically.
磁控生长棒技术是治疗早发性脊柱侧弯患儿的一种有效手术方法。定期调整植入生长棒的长度，以补偿这些患者的正常生长。通过脊柱正位X线片手动测量棒长具有主观性且耗时。开发了一种采用深度学习方法的机器学习（ML）系统，以自动测量调整后的棒长。开发了三种ML模型——棒模型、58毫米模型和头端模型，用于从X线片中提取棒长。387张X线片用于模型开发，60张包含118根棒的X线片留作最终测试。使用手动测量与人工智能（AI）测量调整值之间的平均精度（AP）、平均绝对差值（MAD）±标准差（SD）以及方法间相关系数（ICC）来评估所开发的方法。三种模型的AP分别为67.6%、94.8%和86.3%。棒长变化的MAD±SD为0.98±0.88毫米，ICC为0.90。输出单次棒测量结果的平均时间为6.1秒。所开发的人工智能提供了一种准确可靠的自动检测棒长的方法。
