title: Semi-automatic determination of detailed vertebral shape from lumbar radiographs using active appearance models.
abstract: CONCLUSIONS
  The vertebral endplates in lumbar radiographs were located by a semi-automatic annotation method using statistical shape models.
  
  
  BACKGROUND
  Vertebral fractures are common osteoporotic fractures, but current quantitative detection methods (morphometry) lack specificity. We have previously developed more specific quantitative classifiers of vertebral fracture using shape and appearance models. This method has only been applied to DXA vertebral fracture assessment (VFA) images and not to spinal radiographs. The classifiers require a detailed annotation of the outline of the vertebral endplate, so we investigated the application of similar semi-automated annotation methods to lumbar radiographs as the initial step in the generalisation of the statistical classifiers used in VFA images.
  
  
  METHODS
  The vertebral body outlines in a training set of 670 lumbar radiographs were manually annotated by expert radiologists. This training set was used to build statistical models of vertebral shape and appearance using triplets of vertebrae. In order to segment vertebrae, the models were refitted using a sequence of active appearance models of vertebral triplets, using a miss-40-out train/test cross-validation experiment. The accuracy was evaluated against the manual annotation and analysed by fracture grade.
  
  
  RESULTS
  Good accuracy was obtained for normal vertebrae (0.82 mm) and fracture grades 1 and 2 (1.19 mm), but the localisation accuracy deteriorated for grade 3 fractures to 2.12 mm.
  
  
  CONCLUSIONS
  Vertebral body shape annotation can be substantially automated on lumbar radiographs. However, an occasional manual correction may be required, typically with either severe fractures, or when there is a high degree of projectional tilting or scoliosis. The located detailed shapes may enable the development of more powerful quantitative classifiers of osteoporotic vertebral fracture.
authors: Imaging Science and Biomedical Engineering, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. martin.roberts@manchester.ac.uk
authors: M G
authors: MG
authors: Roberts
authors: T
authors: T
authors: Oh
authors: E M B
authors: EM
authors: Pacheco
authors: R
authors: R
authors: Mohankumar
authors: T F
authors: TF
authors: Cootes
authors: J E
authors: JE
authors: Adams
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods; D000465:Algorithms; D006801:Humans; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging* / Q000293:injuries; D015233:Models, Statistical; D058866:Osteoporotic Fractures / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D016103:Spinal Fractures / Q000000981:diagnostic imaging*