title: Development of a fully automatic shape model matching (FASMM) system to derive statistical shape models from radiographs: application to the accurate capture and global representation of proximal femur shape.
abstract: OBJECTIVE
  To evaluate the accuracy and sensitivity of a fully automatic shape model matching (FASMM) system to derive statistical shape models (SSMs) of the proximal femur from non-standardised anteroposterior (AP) pelvic radiographs.
  
  
  METHODS
  AP pelvic radiographs obtained with informed consent and appropriate ethical approval were available for 1105 subjects with unilateral hip osteoarthritis (OA) who had been recruited previously for The arcOGEN Study. The FASMM system was applied to capture the shape of the unaffected (i.e., without signs of radiographic OA) proximal femur from these radiographs. The accuracy and sensitivity of the FASMM system in calculating geometric measurements of the proximal femur and in shape representation were evaluated relative to validated manual methods.
  
  
  RESULTS
  De novo application of the FASMM system had a mean point-to-curve error of less than 0.9 mm in 99% of images (n = 266). Geometric measurements generated by the FASMM system were as accurate as those obtained manually. The analysis of the SSMs generated by the FASMM system for male and female subject groups identified more significant differences (in five of 17 SSM modes after Bonferroni adjustment) in their global proximal femur shape than those obtained from the analysis of conventional geometric measurements. Multivariate gender-classification accuracy was higher when using SSM mode values (76.3%) than when using conventional hip geometric measurements (71.8%).
  
  
  CONCLUSIONS
  The FASMM system rapidly and accurately generates a global SSM of the proximal femur from radiographs of varying quality and resolution. This system will facilitate complex morphometric analysis of global shape variation across large datasets. The FASMM system could be adapted to generate SSMs from the radiographs of other skeletal structures such as the hand, knee or pelvis.
authors: Imaging Sciences, The University of Manchester, Manchester, UK. Electronic address: claudia.lindner@postgrad.manchester.ac.uk.
authors: C
authors: C
authors: Lindner
authors: S
authors: S
authors: Thiagarajah
authors: J M
authors: JM
authors: Wilkinson
authors: G A
authors: GA
authors: Wallis
authors: T F
authors: TF
authors: Cootes
mesh_terms: D005260:Female; D005269:Femur / Q000000981:diagnostic imaging* / Q000473:pathology; D005270:Femur Head / Q000000981:diagnostic imaging / Q000473:pathology; D005272:Femur Neck / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D008297:Male; D008953:Models, Anatomic; D015233:Models, Statistical; D015588:Observer Variation; D015207:Osteoarthritis, Hip / Q000000981:diagnostic imaging* / Q000473:pathology; D010384:Pelvic Bones / Q000000981:diagnostic imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012727:Sex Characteristics
keywords: Hip morphology; Osteoarthritis; Proximal femur; Shape analysis; Statistical shape models