Patient-specific spine digital twins: a computational characterization of the idiopathic scoliosis.

J Orthop Surg Res

Biomedical Engineering Department, Universidad de los Andes, Bogotá, Colombia.

Published: January 2025

AI Article Synopsis

  • Scoliosis is identified through Cobb's angle, and this study aims to create a digital twin of the spine to analyze biomechanical stresses and disc degeneration related to idiopathic scoliosis using patient-specific data.
  • A 3D computational model was developed that modifies intervertebral disc properties based on radiological measurements, validated by comparing with patient images; finite element analysis clarified the impact of deformity on spinal biomechanics.
  • The results showed that the model accurately represented thoracic scoliosis and revealed that disc strain increases near the apex, with "type-C" curves at higher risk for herniation compared to "type-S," thereby enhancing understanding of scoliosis and aiding in treatment planning.

Article Abstract

Background: Scoliosis is an idiopathic three-dimensional spine strain. The orthopedic parameter used to diagnose and evaluate the severity of the strain is Cobb's angle. This study proposes using this clinical parameter to reproduce a digital twin of the spine, calculate biomechanical stress changes, and characterize idiopathic scoliosis deformity through symmetrical degeneration of intervertebral discs, relying on patient-specific radiological measurements of the scoliotic curves.

Methods: A three-dimensional computational model of the spine was developed, where patient-specific curves were generated by modifying intervertebral disc mechanical properties via a mathematical model derived from radiological data. Validation of the model was performed by comparing the resultant scoliotic curves with patient radiological images. Finite element analysis was then used to elucidate the biomechanical effects on the spine due to the deformity.

Results: The model successfully replicated patient-specific thoracic scoliotic deformities, revealing a discernible relationship between disc strain and its proximity to the apex, indicating a heightened risk of disc stress closer to the apex. Moreover, "type-C" curves exhibited a greater risk of herniation compared to "type-S" curves due to differences in compressive stress distribution.

Conclusion: This modeling approach enhances the understanding of scoliosis biomechanics, facilitating risk assessment for disc prolapse and aiding in treatment selection, including the design of condition-specific orthotics. Furthermore, it establishes a quantitative link between scoliosis severity and disc strain, integrating Cobb's angle and other orthopedic parameters into computational models to approximate patient-specific conditions.

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http://dx.doi.org/10.1186/s13018-024-05417-0DOI Listing

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Article Synopsis
  • Scoliosis is identified through Cobb's angle, and this study aims to create a digital twin of the spine to analyze biomechanical stresses and disc degeneration related to idiopathic scoliosis using patient-specific data.
  • A 3D computational model was developed that modifies intervertebral disc properties based on radiological measurements, validated by comparing with patient images; finite element analysis clarified the impact of deformity on spinal biomechanics.
  • The results showed that the model accurately represented thoracic scoliosis and revealed that disc strain increases near the apex, with "type-C" curves at higher risk for herniation compared to "type-S," thereby enhancing understanding of scoliosis and aiding in treatment planning.
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