Neurosurgical Department, Spine Unit, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.
Health Informatic Department, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.
World Neurosurg. 2024 Jul;187:e363-e382. doi: 10.1016/j.wneu.2024.04.091. Epub 2024 Apr 20.
Measuring spinal alignment with radiological parameters is essential in patients with spinal conditions likely to be treated surgically. These evaluations are not usually included in the radiological report. As a result, spinal surgeons commonly perform the measurement, which is time-consuming and subject to errors. We aim to develop a fully automated artificial intelligence (AI) tool to assist in measuring alignment parameters in whole-spine lateral radiograph (WSL X-rays).
We developed a tool called Vertebrai that automatically calculates the global spinal parameters (GSPs): Pelvic incidence, sacral slope, pelvic tilt, L1-L4 angle, L4-S1 lumbo-pelvic angle, T1 pelvic angle, sagittal vertical axis, cervical lordosis, C1-C2 lordosis, lumbar lordosis, mid-thoracic kyphosis, proximal thoracic kyphosis, global thoracic kyphosis, T1 slope, C2-C7 plummet, spino-sacral angle, C7 tilt, global tilt, spinopelvic tilt, and hip odontoid axis. We assessed human-AI interaction instead of AI performance alone. We compared the time to measure GSP and inter-rater agreement with and without AI assistance. Two institutional datasets were created with 2267 multilabel images for classification and 784 WSL X-rays with reference standard landmark labeled by spinal surgeons.
Vertebrai significantly reduced the measurement time comparing spine surgeons with AI assistance and the AI algorithm alone, without human intervention (3 minutes vs. 0.26 minutes; P < 0.05). Vertebrai achieved an average accuracy of 83% in detecting abnormal alignment values, with the sacral slope parameter exhibiting the lowest accuracy at 61.5% and spinopelvic tilt demonstrating the highest accuracy at 100%. Intraclass correlation analysis revealed a high level of correlation and consistency in the global alignment parameters.
Vertebrai's measurements can accurately detect alignment parameters, making it a promising tool for measuring GSP automatically.
在可能需要手术治疗的脊柱疾病患者中,用放射学参数测量脊柱的排列至关重要。这些评估通常不包括在放射学报告中。因此,脊柱外科医生通常会进行测量,但这既耗时又容易出错。我们旨在开发一种全自动人工智能 (AI) 工具,以协助测量全脊柱侧位片 (WSL X 射线) 的排列参数。
我们开发了一个名为 Vertebrai 的工具,它可以自动计算全局脊柱参数 (GSP):骨盆入射角、骶骨倾斜角、骨盆倾斜度、L1-L4 角、L4-S1 腰骶角、T1 骨盆角、矢状垂直轴、颈椎前凸、C1-C2 前凸、腰椎前凸、中胸段后凸、近胸段后凸、全胸段后凸、T1 斜率、C2-C7 垂线、脊柱-骶骨角、C7 倾斜角、整体倾斜角、脊柱-骨盆倾斜角和髋齿状突轴。我们评估了人类与 AI 的交互作用,而不仅仅是 AI 的性能。我们比较了使用和不使用 AI 辅助测量 GSP 的时间以及组内一致性。创建了两个机构数据集,一个包含 2267 张多标签图像,用于分类,另一个包含 784 张 WSL X 射线,由脊柱外科医生参考标准地标进行标记。
Vertebrai 显著减少了脊柱外科医生在使用 AI 辅助和单独使用 AI 算法时的测量时间,无需人工干预 (3 分钟比 0.26 分钟;P<0.05)。Vertebrai 在检测异常排列值方面的平均准确率为 83%,其中骶骨倾斜角参数的准确率最低,为 61.5%,脊柱-骨盆倾斜角的准确率最高,为 100%。组内相关分析显示,全局排列参数具有高度的相关性和一致性。
Vertebrai 的测量结果可以准确地检测排列参数,因此是一种有前途的自动测量 GSP 的工具。