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Virginia Tech

On the Geometric Characterization of the Lenke Classification Scheme for Idiopathic Scoliosis

Abstract

dc:description.abstract

Current methods for treating and diagnosing spinal deformities caused by scoliosis are both surgically intensive and rarely allow for complete correction. This is mainly due to the fact that the diagnostic techniques used are rough estimates made by angles defined by observations of 2-D radiographs. By utilizing the latest software, our research is based on designing a tool that creates a 3-D representation of the spine. When creating a three-dimensional spinal model, it becomes possible to determine local curvature and local torsion values at each specific vertebrae. By manipulating these values at discrete locations on the spine, one can generate "virtual" spines in a three-dimensional environment. The Scoliosis Learning Tool includes algorithmic steps that determine the Lenke Classification of the "virtual" spines. The Lenke Classification is the most commonly accepted method for diagnosing spinal deformities. This patient building program will produce a group of spines with random values for curvature, torsion and initial spinal orientation. An algorithm within the software determines the Lenke Classification of each, and discards any curves that appear unnatural. By defining a metric that places an emphasis on certain geometric similarities, the software is able to define diameters of classification groups and separations between different classification groups. In turn it is possible to determine minor to major differences between spines within the same classification. In doing so, the opportunity exists to possibly find an undiscovered deformity that had previously fallen under another classification category.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Biomedical Engineering and Sciences
Department dc:contributor.department
Biomedical Engineering and Sciences
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2004

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Entrekin, Dean Allen
Chair dc:contributor.committeechair
  • Dankowicz, Harry J.
Committee members dc:contributor.committeemember
  • Madigan, Michael L.
  • Shilt, Jeff

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-05262004-144020
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/9957

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Entrekin, Dean Allen. On the Geometric Characterization of the Lenke Classification Scheme for Idiopathic Scoliosis. masters thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9957