Comprehensive assessment of global spinal sagittal alignment and related normal spinal loads in a healthy population

• Published in: Journal of biomechanics Vol. 170; p. 112127
• Main Authors: Rieger, Florian, Rothenfluh, Dominique A., Ferguson, Stephen J., Ignasiak, Dominika
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.06.2024; Elsevier Limited
• Subjects: Adult; Aged; Alignment; Biomechanical Phenomena; Biomechanics; Female; Humans; Lower bounds; Lumbar Vertebrae - diagnostic imaging; Lumbar Vertebrae - physiology; Male; Middle Aged; Models, Biological; Musculoskeletal Modeling; Older people; Patients; Physiology; Principal Component Analysis; Principal components analysis; Spinal sagittal alignment; Spine - diagnostic imaging; Spine - physiology; Statistical models; Statistical Shape Modeling; Variability; Vertebrae; Weight-Bearing - physiology; Statistical Shape Modeling; Spinal sagittal alignment; Musculoskeletal Modeling; Principal Component Analysis
• ISSN: 0021-9290; 1873-2380; 1873-2380
• DOI: 10.1016/j.jbiomech.2024.112127

Abnormal postoperative global sagittal alignment (GSA) is associated with an increased risk of mechanical complications after spinal surgery. Typical assessment of sagittal alignment relies on a few selected measures, disregarding global complexity and variability of the sagittal curvature. The normative range of spinal loads associated with GSA has not yet been considered in clinical evaluation. The study objectives were to develop a new GSA assessment method that holistically describes the inherent relationships within GSA and to estimate the related spinal loads. Vertebral endplates were annotated on radiographs of 85 non-pathological subjects. A Principal Component Analysis (PCA) was performed to derive a Statistical Shape Model (SSM). Associations between identified GSA variability modes and conventional alignment measures were assessed. Simulations of respective Shape Modes (SMs) were performed using an established musculoskeletal AnyBody model to estimate normal variation in cervico-thoraco-lumbar loads. The first six principal components explained 97.96% of GSA variance. The SSM provides the normative range of GSA and a visual representation of the main variability modes. Normal variation relative to the population mean in identified alignment features was found to influence spinal loads, e.g. the lower bound of the second shape mode (SM2-2σ) corresponds to an increase in L4L5-compression by 378.64 N (67.86%). Six unique alignment features were sufficient to describe GSA almost entirely, demonstrating the value of the proposed method for an objective and comprehensive analysis of GSA. The influence of these features on spinal loads provides a normative biomechanical reference, eventually guiding surgical planning of deformity correction in the future.