Arts et Metiers Institute of Technology, Institut de Biomecanique Humaine Georges Charpak, Paris, France; Laboratoire de recherche en imagerie et orthopédie, Centre de recherche du Centre hospitalier de l'Université de Montréal, Montréal, Canada.
Arts et Metiers Institute of Technology, Institut de Biomecanique Humaine Georges Charpak, Paris, France.
Med Eng Phys. 2023 Oct;120:104043. doi: 10.1016/j.medengphy.2023.104043. Epub 2023 Aug 27.
Patient-specific scapular shape in functional posture can be highly relevant to clinical research. Biplanar radiography is a relevant modality for that purpose with already two existing assessment methods. However, they are either time-consuming or lack accuracy. The aim of this study was to propose a new, more user-friendly and accurate method to determine scapular shape.
The proposed method relied on simplified manual inputs and an upgraded version of the first 3D estimate based on statistical inferences and Moving-Least Square (MLS) deformation of a template. Then, manual adjustments, with real-time MLS algorithm and contour matching adjustments with an adapted minimal path method, were added to improve the match between the projected 3D model and the radiographic contours. The accuracy and reproducibility of the method were assessed (with 6 and 12 subjects, respectively).
The shape accuracy was in average under 2 mm (1.3 mm in the glenoid region). The reproducibility study on the clinical parameters found intra-observer 95% confidence intervals under 3 mm or 3° for all parameters, except for glenoid inclination and Critical Shoulder Angle, ranging between 3° and 6°.
This method is a first step towards an accurate reconstruction of the scapula to assess clinical parameters in a functional posture. This can already be used in clinical research on non-pathologic bones to investigate the scapulothoracic joint in functional position.
功能位下患者肩胛骨的形态与临床研究密切相关。为此，双平面 X 线摄影是一种相关的方法，已经有两种现有的评估方法。然而，它们要么耗时，要么缺乏准确性。本研究的目的是提出一种新的、更用户友好和准确的方法来确定肩胛骨的形状。
所提出的方法依赖于简化的手动输入和基于统计推断和模板的移动最小二乘（MLS）变形的第一个 3D 估计的升级版本。然后，通过实时 MLS 算法和带有自适应最小路径方法的轮廓匹配调整进行手动调整，以提高投影 3D 模型与射线照片轮廓之间的匹配度。评估了该方法的准确性和可重复性（分别有 6 名和 12 名受试者）。
该方法的形状精度平均在 2 毫米以内（关节盂区域为 1.3 毫米）。对临床参数的重复性研究发现，除了关节盂倾斜度和关键肩角外，所有参数的观察者内 95%置信区间均在 3 毫米或 3°以内，其中 3°和 6°之间。
该方法是准确重建肩胛骨以评估功能位下临床参数的第一步。这已经可以用于非病理性骨骼的临床研究中，以研究功能位置下的肩胛胸关节。
