Artificial intelligence data-driven 3D model for AIS

M. Tajdari, A. Maqsood, H. Li, S. Saha, J. F. Sarwark*, W. K. Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Scoliosis is a 3D deformation of the spinal column, characterized by a lateral deviation of the spine, accompanied by axial rotation of the vertebrae. Adolescent Idiopathic Scoliosis (AIS), is the most common type, affecting children between ages 8 to 18 when bone growth is at its maximum rate. The selection of the most appropriate treatment options is based on the surgeon's experience. So, developing a clinically validated patient-specific model of the spine would aid surgeons in understanding AIS in early stages and propose an efficient method of treatment for the individual patient. This project steps include: Developing a clinically validated patient-specific Reduced Order Finite Element Model (ROFEM) of the spine, predicting AIS progression using data mining and proposing a method of treatment. First we implement FE synergistically with bio-mechanical information, image processing and data science techniques to improve predictive ability. Initial geometry of the spine will be extracted from the X-ray images from different planes and imported to FEM software to generate the spine model and perform analysis. A RO model is developed based on the detailed spinal FEM. Next, a neural network is used to predict the spinal curvature. The ability to predict the severity of AIS will have an immense impact on the treatment of AIS-affected children. Access to a predictive and patient-specific model will enable the physicians to have a better understanding of spinal curvature progression. Consequently, the physicians will be able to educate families, choose the most appropriate treatment option and asses for surgical intervention.

Original languageEnglish (US)
Title of host publicationResearch into Spinal Deformities 9
EditorsXue-Cheng Liu, John G. Thometz
PublisherIOS Press BV
Pages141-145
Number of pages5
ISBN (Electronic)9781643681825
DOIs
StatePublished - 2021

Publication series

NameStudies in Health Technology and Informatics
Volume280
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Keywords

  • 3D Modeling
  • Adolescent Idiopathic Scoliosis
  • Finite Element Model
  • Spine

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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