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增大 Cobb 角:使用 Bezier 曲线对整个脊柱形状进行三维分析。

Augmenting the Cobb angle: Three-dimensional analysis of whole spine shapes using Bézier curves.

机构信息

Mathematical Institute, University Koblenz-Landau, Koblenz, Germany.

Institute for Medical Engineering and Information Processing (MTI Mittelrhein), University Koblenz-Landau, Koblenz, Germany; Mechanical Systems Engineering, Swiss Federal Laboratories for Materials Science and Technology (EMPA), Duebendorf, Switzerland.

出版信息

Comput Methods Programs Biomed. 2022 Oct;225:107075. doi: 10.1016/j.cmpb.2022.107075. Epub 2022 Aug 15.

Abstract

BACKGROUND AND OBJECTIVE

The identification and classification of pathological spinal deformities poses a major challenge to any diagnostician. First, available medical images are usually two-dimensional projections, obscuring elaborated spatial information. Second, several measurement techniques with different thresholds for certain clinical syndromes make it difficult to classify measured results. Here, a method is presented to augment and standardize the analysis of spinal shapes in three dimensions.

METHODS

Regarding the first limitation, (semi-)automatic, three-dimensional segmentation techniques of medical images have already been developed. To overcome the second, we propose here a representation of the whole spine by a Bézier curve using the vertebral centers as control points. After normalization, a differential-geometric approach yields information on curvature and torsion at each spinal level as well as in between.

RESULTS

Based on literature data and multi-body simulations, we show how these quantities alter with individual posture and during motion. Robustness with respect to missing data is investigated. Approaches towards the identification of spinal disorders are motivated.

CONCLUSION

Our results emphasize the need for individualizable identification and classification of spinal deformities and give an outlook on how it might be achieved. The presented methodology constitutes the first fully three-dimensional analysis of spinal shapes, i.e. without the requirement of certain physiological planes (e.g. the sagittal plane) or landmarks (e.g. the apex vertebra).

摘要

背景与目的

病理脊柱畸形的识别和分类对任何诊断医师来说都是一个重大挑战。首先,现有的医学图像通常是二维投影,掩盖了详细的空间信息。其次,针对某些临床综合征,存在几种具有不同阈值的测量技术,这使得难以对测量结果进行分类。这里提出了一种方法来增强和规范三维脊柱形状的分析。

方法

针对第一个限制,已经开发出了用于医学图像的(半)自动三维分割技术。为了克服第二个限制,我们在这里提出了一种使用椎骨中心作为控制点的贝塞尔曲线来表示整个脊柱的方法。归一化后,微分几何方法可在每个脊柱水平以及水平之间提供曲率和扭转信息。

结果

基于文献数据和多体模拟,我们展示了这些数量如何随个体姿势和运动而变化。研究了对缺失数据的稳健性。提出了识别脊柱疾病的方法。

结论

我们的结果强调了对脊柱畸形进行个体化识别和分类的必要性,并展望了如何实现这一目标。所提出的方法构成了对脊柱形状的首次完全三维分析,即无需特定的生理平面(例如矢状面)或标志点(例如顶点椎骨)。

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