Document Detail

Prediction of the T2-T12 kyphosis in adolescent idiopathic scoliosis using a multivariate regression model.
MedLine Citation:
PMID:  18810035     Owner:  NLM     Status:  MEDLINE    
The paper presents a nonlinear regression model built on the coronal thoracic curvature, the lumbar lordosis and the slope of the first lumbar vertebra in order to estimate the thoracic kyphosis measure between T2 and T12. To train the proposed model, a large database containing scoliotic spines demonstrating several types of scoliotic deformities was used to train the proposed system by a cross-validation method. Validation was performed on patients exhibiting three different types of sagittal thoracic profiles: normal, hypo-kyphotic, and hyper-kyphotic. Results show that a multivariate regression model based on dependent variables is able to predict with a reasonable accuracy the sagittal thoracic kyphosis for the automatic assessment and classification of the spinal curve.
S Kadoury; F Cheriet; H Labelle
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Studies in health technology and informatics     Volume:  140     ISSN:  0926-9630     ISO Abbreviation:  Stud Health Technol Inform     Publication Date:  2008  
Date Detail:
Created Date:  2008-09-23     Completed Date:  2008-10-17     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214582     Medline TA:  Stud Health Technol Inform     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  269-72     Citation Subset:  T    
Ecole Polytechnique de Montréal, Succ. Centre-Ville, Montreal, Canada H3C 3A7.
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MeSH Terms
Kyphosis / diagnosis,  physiopathology*
Lumbar Vertebrae / pathology
Models, Statistical
Multivariate Analysis
Scoliosis / diagnosis,  physiopathology*
Thoracic Vertebrae / pathology*

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