Augmenting the Cobb angle: Three-dimensional analysis of whole spine shapes using Bézier curves. (October 2022)

• Record Type: Journal Article
• Authors: Rockenfeller, Robert; Müller, Andreas
• Is Part Of: Computer methods and programs in biomedicine. Volume 225(2022)
• Publication Date: 2022-10
• Subjects: Spine -- Lumbar and cervical lordosis -- Thoracic kyphosis -- Scoliosis -- Kent plot -- Biomechanics; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2022.107075
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Spinal shapes are analyzed using the orientation of Bézier curves. Therefore, vertebral centers of mass are fitted for whole human spines. Curvature and torsion are calculated continuously among spinal levels. The concept is thought to enhance the well-known Cobb angle in 3D. Applications include assessment of motions and clinical diagnostics. 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).