Shape-based Assessment of Vertebral Fracture Risk in Postmenopausal Women Using Discriminative Shape Alignment

Academic Radiology

Volumn 19, Issue 4, 2012, Pages 446-454

  Crimi, Alessandro ^a   Loog, Marco ^b   De Bruijne, Marleen ^a,d   Nielsen, Mads ^a   Lillholm, Martin ^c  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^c BiomedIQ A/S   (Denmark)

^d ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

Osteoporosis; Shape model; Vertebral fracture prediction; Vertebral morphometry; X ray

Indexed keywords

ADULT; ARTICLE; BODY MASS; BONE DENSITY; CASE CONTROL STUDY; CLINICAL ARTICLE; CLINICAL ASSESSMENT TOOL; CONTROLLED STUDY; DISCRIMINATIVE SHAPE ALIGNMENT; FEMALE; FOLLOW UP; HUMAN; LUMBAR VERTEBRA; MORPHOMETRICS; POSTMENOPAUSE; POSTMENOPAUSE OSTEOPOROSIS; PRIORITY JOURNAL; RISK ASSESSMENT; VERTEBRA FRACTURE; X RAY FILM;

AGED; ALGORITHMS; DENMARK; DISCRIMINANT ANALYSIS; FEMALE; HUMANS; INCIDENCE; OSTEOPOROTIC FRACTURES; PATTERN RECOGNITION, AUTOMATED; POSTMENOPAUSE; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; RISK ASSESSMENT; RISK FACTORS; SENSITIVITY AND SPECIFICITY; SPINAL FRACTURES; SUBTRACTION TECHNIQUE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84858799313     PISSN: 10766332     EISSN: 18784046     Source Type: Journal    
DOI: 10.1016/j.acra.2011.12.012     Document Type: Article

References (42)

1. Szulc P., Delmas P. Vertebral fracture initiative resource document 2005, International Osteoporosis Foundation Report, Nyon, Switzerland.
2. Black D., Arden N., Palermo L. Prevalent vertebral deformities predict hip fractures and new vertebral deformities but not wrist fractures. J Bone Miner Res 1999, 14:821-828.
3. Melton L.J., Atkinson E.J., Cooper C. Vertebral fractures predict subsequent fractures. Osteoporos Int 1999, 10:214-221.
4. Kanis J., Borgstrom F., Laet C.D., et al. Assessment of fracture risk. Osteoporos Int 2005, 16:581-589.
5. Burge R., Dawson-Hughes B., Solomon D., et al. Incidence and economic burden of osteoporosis-related fractures in the united states. J Bone Miner Res 2007, 22:465-475.
6. Laet C.D., Oden A., Johnell O., et al. The impact of the use of multiple risk factors on case finding strategies: a mathematical framework. Osteoporos Int 2005, 16:313-318.
7. World Health Organization Collaborating Centre for Metabolic Bone Diseases, University of Sheffield. FRAX®: WHO Fracture Risk Assessment Tool. Available at: . Accessed January 13, 2012. http://www.shef.ac.uk/frax.
8. Genant H.K., Wu C., van Kuijk C., et al. Vertebral fracture assessment using a semiquantitative technique. J Bone Miner Res 1993, 8:1137-1148.
9. Eastell R., Cedel S.L., Wahner H.W., et al. Classification of vertebral fractures. J Bone Miner Res 1991, 6:207-215.
10. McCloskey E.V., Spector T.D., Eyres K.S., et al. The assessment of vertebral deformity: a method for use in population studies and clinical trials. Osteoporos Int 1994, 4:138-147.
11. Hurxthal L.M. Measurement of vertebral heights. AJR Am J Roentgenol 1968, 103:635-644.
12. Genant H.K., Jergas M., Palermo L., et al. Comparison of semi-quantitative visual and quantitative morphometric assessment of prevalent and incident vertebral fractures. J Bone Miner Res 1996, 11:984-996.
13. Jiang G., Eastell R., Barrington N., et al. Comparison of methods for the visual identification of prevalent vertebral fracture in osteoporosis. Osteoporos Int 2004, 15:887-896.
14. Aouache M, Hussain A, Samad S, et al. Active shape modeling of medical images for vertebral fracture computer assisted assessment system. Available at: . Accessed January 13, 2012. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4451397.
15. de Bruijne M., Lund M.T., Tanko L.B., et al. Quantitative vertebral morphometry using neighbor-conditional shape models. Med Image Anal 2007, 11:503-512.
16. de Bruijne M., Pettersen P., Tanko L., et al. Vertebral fracture classification. Proc SPIE Med Imaging 2007, 6512:651219.
17. Roberts M., Cootes T., Pacheco E., et al. Quantitative vertebral fracture detection on DXA images using shape and appearance models. Acad Radiol 2007, 14:1166-1178.
18. Roberts M., Pacheco E., Mohamkumar R., et al. Detection of vertebral fractures in DXA VFA images using statistical models of appearance and a semi-automatic segmentation. Osteoporos Int 2010, 21:2037-2046.
19. Diacinti D., Pisani D., Barone-Adesi F., et al. A new predictive index for vertebral fractures: The sum of the anterior vertebral body heights. Bone 2010, 46:768-773.
20. Lillholm M., Ghosh A., de Bruijne M., et al. Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal women. Osteoporos Int 2011, 22:2119-2128.
21. Loog M., Bruijne M. Discriminative shape alignment. Proc 21st Int Conf Inform Proc Med Imaging 2009, 12:459-466.
22. Pettersen P.C., de Bruijne M., Chen J., et al. A computer-based measure of irregularity in vertebral alignment is a BMD-independent predictor of fracture risk in postmenopausal women. Osteoporos Int 2007, 18:1525-1530.
23. Ruyssen-Witrand A., Gossec L., Kolta S., et al. Vertebral dimensions as risk factor of vertebral fracture in osteoporotic patients: a systematic literature review. Osteoporos Int 2007, 18:1271-1278.
24. Baker-LePain J., Luker K., Lynch J., et al. Active shape modeling of the hip in the prediction of incident hip fracture. J Bone Miner Res 2011, 26:468-474.
25. Gregory J., Stewart A., Undrill P., et al. Bone shape, structure and density as determinants of osteoporotic hip fracture: a pilot study investigating the combination of risk factors. Invest Radiol 2005, 40:591-597.
26. Bouxsein M., Karasik D. Bone geometry and skeletal fragility. Curr Osteoporos Rep 2006, 4:49-56.
27. Bagger Y.Z., Tanko L.B., Alexandersen P., et al. The long-term predictive value of bone mineral density measurements for fracture risk is independent of the site of measurement and the age at diagnosis: results from the prospective epidemiological risk factors study. Osteoporos Int 2006, 17:471-477.
28. Bookstein F.L. Shape and the information in medical images: a decade of morphometric synthesis. Comput Vis Image Understand 1997, 66:97-118.
29. Goodall C. Procrustes methods in the statistical analysis of shape. J R Stat Soc 1991, 53:285-339.
30. Dryden I., Mardia K. Statistical shape analysis 1998, John Wiley, New York.
31. Bookstein F.L. Landmark methods for forms without landmarks: localizing group differences in outline shape. Med Image Anal 1997, 1:225-243.
32. Jolliffe I.T. Principal component analysis 2002, Springer, New York.
33. Cootes T.F., Taylor C.J., Cooper D.H., et al. Active shape models-their training and application. J Comput Vis Image Understand 1995, 61:38-59.
34. Bellman R.E. Dynamic programming 2003, Courier Dover, Mineola, NY.
35. Duda R.O., Hart P.E. Pattern recognition and scene analysis 1973, John Wiley, New York.
36. Hastie T., Tibshirani R., Friedman J. The elements of statistical learning 2003, Springer, New York.
37. Tikhonov A.N., Arsenin A.N. Solution of ill-posed problems 1977, Winston & Sons, Washington, DC.
38. Hastie T., Buja A., Tibshirani R. Penalized discriminant analysis. Ann Stat 1995, 1:73-102.
39. Hoerl A., Kennard R.W. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 2000, 42:80-86.
40. DeLong E., DeLong D., Clarke-Pearson D. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988, 44:837-845.
41. Zebaze R.M.D., Maalouf G., Seeman N.M.E. Loss of regularity in the curvature of the thoracolumbar spine: a measure of structural failure. J Bone Miner Res 2004, 19:1099-1104.
42. McCance L., Huether S.E. Pathophysiology: the biologic basis for disease in adults and children 2009, Mosby, St. Louis, MO.