Noninvasive clinical assessment of trunk deformities associated with scoliosis

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DOIResolve DOI: http://doi.org/10.1109/TITB.2012.2222425
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TypeArticle
Journal titleIEEE Journal of Biomedical and Health Informatics
ISSN2168-2194
2168-2208
Volume17
Issue2
Pages392401
Subjectshape analysis; Clustering; functional data analysis; scoliosis
AbstractBesides the spinal deformity, scoliosis modifies notably the general appearance of the trunk resulting in trunk rotation, imbalance, and asymmetries that constitutes patients' major concern. Existing classifications of scoliosis, based on the type of spinal curve as depicted on radiographs, are currently used to guide treatment strategies. Unfortunately, even though a perfect correction of the spinal curve is achieved, some trunk deformities remain, making patients dissatisfied with the treatment received. The purpose of this study is to identify possible shape patterns of trunk surface deformity associated with scoliosis. First, trunk surface is represented by a multivariate functional trunk shape descriptor based on 3-D clinical measurements computed on cross sections of the trunk. Then, the classical formulation of hierarchical clustering is adapted to the case of multivariate functional data and applied to a set of 236 trunk surface 3-D reconstructions. The highest internal validity is obtained when considering 11 clusters that explain up to 65% of the variance in our dataset. Our clustering result shows a concordance with the radiographic classification of spinal curves in 68% of the cases. As opposed to radiographic evaluation, the trunk descriptor is 3-D and its functional nature offers a compact and elegant description of not only the type, but also the severity and extent of the trunk surface deformity along the trunk length. In future work, new management strategies based on the resulting trunk shape patterns could be thought of in order to improve the esthetic outcome after treatment, and thus patients satisfaction.
Publication date
PublisherInstitute of Electrical and Electronics Engineers
LanguageEnglish
AffiliationNational Research Council Canada
Peer reviewedYes
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This is a non-NRC publication

"Non-NRC publications" are publications authored by NRC employees prior to their employment by NRC.

NPARC number23000993
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Record identifier21ac41c8-ed61-40c9-b2a2-ef926d9d5e75
Record created2016-11-25
Record modified2016-11-25
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