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Prediction of Cobb-angle for Monitoring System in Adolescent Girls with Idiopathic Scoliosis using Multiple Regression Analysis

  • Seo, Eun Ji (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University) ;
  • Choi, Ahnryul (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University) ;
  • Oh, Seung Eel (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University) ;
  • Park, Hyun Joon (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University) ;
  • Lee, Dong Jun (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University) ;
  • Mun, Joung H. (Department of Bio-Mechatronic Engineering, College of Biotechnology & Bioengineering, Sungkyunkwan University)
  • Received : 2012.10.18
  • Accepted : 2013.02.28
  • Published : 2013.03.01

Abstract

Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle: $10^{\circ}-25^{\circ}$), and 14 severe scoliosis patients (Cobb angle: $25^{\circ}-50^{\circ}$) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement ($R^2$ = 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately $3.2{\pm}1.8$. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.

Keywords

References

  1. Byl, N. N. and J. M. Gray. 1993. Complex balance reactions in different sensory conditions: adolescents with and without idiopathic scoliosis. Journal of orthopaedic research 11(2):215-227. https://doi.org/10.1002/jor.1100110209
  2. Chow, D. H., M. L. Kwok, J. C. Cheng, M. L. Lao, A. D. Holmes, A. Au-Yang, F. Y. Yao and M. S. Wong. 2006. The effect of backpack weight on the standing posture and balance of schoolgirls with adolescent idiopathic scoliosis and normal controls. Gait & Posture 24(2): 173-181. https://doi.org/10.1016/j.gaitpost.2005.08.007
  3. Claus, A. P., J. A. Hides, G. L. Moseley and P. W. Hodges. 2009. Different ways to balance the spine: subtle changes in sagittal spinal curves affect regional muscle activity. Spine 34(6):E208-E214 https://doi.org/10.1097/BRS.0b013e3181908ead
  4. Cobb. J. R. 1948. Outline for the study of scoliosis. In Instructional course lectures, The American academy of orthopaedic surgeons 5:261-275.
  5. Dalleau, G., P. Leroyer, M. Beaulieu, C. Verkindt, C. H. Rivard and P. Allard. 2012. Pelvis Morphology, Trunk Posture and Standing Imbalance and Their Relations to the Cobb Angle in Moderate and Severe Untreated AIS. PLoS ONE 7(7):e36755. https://doi.org/10.1371/journal.pone.0036755
  6. Dang, N. R., M. J. Moreau, D. L. Moreau, J. K. Mahood and J. Raso. 2005. Intra-observer reproducibility and interobserver reliability of the radiographic parameters in the Spinal Deformity Study Group's AIS Radiographic Measurement Manual. Spine 30(9): 1064-1069. https://doi.org/10.1097/01.brs.0000160840.51621.6b
  7. Davis, R. B., S. Oonupuu, D. Tyurski and J. Gage. 1991. A gait analysis data collection and reduction. Human Movement Science 10(5):575-587. https://doi.org/10.1016/0167-9457(91)90046-Z
  8. Duval-Beaupere, G. 1971. Pathogenic relationship between scoliosis and growth. In Scoliosis and Growth. Churchill Livingstone 58-64.
  9. Fisher, B., S. Anderson, ER. Fisher, C. Redmond, DL. Wickerham, N. Wolmark, EP. Mamounas, M. Deutsch and R. Margolese. 1991. Significance of ipsilateral breast tumour recurrence after lumpectomy. Lancet 338(8763):327-331. https://doi.org/10.1016/0140-6736(91)90475-5
  10. Fortin, C., D. E. Feldman, F. Cheriet and H. Labelle. 2010. Validity of a quantitative clinical measurement tool of trunk posture in idiopathic scoliosis. Spine 35(19): E988-E994. https://doi.org/10.1097/BRS.0b013e3181cd2cd2
  11. Fortin, C., D. E. Feldman, F. Cheriet and H. Labelle. 2011. Clinical methods for quantifying body segment posture: a literature review. Disability and Rehabilitation 33(5): 367-383. https://doi.org/10.3109/09638288.2010.492066
  12. Fortin, C., D. E. Feldman, F. Cheriet, D. Gravel, F. Gauthier and H. Labelle. 2012. Reliability of a quantitative clinical posture assessment tool among persons with idiopathic scoliosis. Physiotherapy 98(1):64-75. https://doi.org/10.1016/j.physio.2010.12.006
  13. Greendale, G. A., N. S. Nili, M. H. Huang, L. Seeger and A. S. Karlamangla. 2011. The reliability and validity of three non-radiological measures of thoracic kyphosis and their relations to the standing radiological Cobb angle. Osteoporosis International 22(6): 1897-1905. https://doi.org/10.1007/s00198-010-1422-z
  14. Jaremko, J. L., P. Poncet, J. Ronsky, J. Harder, J. Dansereau, H. Labelle and R. F. Zernicke. 2002. Genetic algorithmneural network estimation of cobb angle from torso asymmetry in scoliosis. Journal of Biomechanical Engineering 124: 496-503. https://doi.org/10.1115/1.1503375
  15. Karol, L. A. 2001. Effectiveness of bracing in male patients with idiopathic scoliosis. The Spine Journal 26(18): 2001-2005. https://doi.org/10.1097/00007632-200109150-00013
  16. Korovessis, P. G. and M. V. Stamatakis. 1996. Prediction of scoliotic Cobb angle with the use of the scoliometer. Spine 21(14):1661-1666. https://doi.org/10.1097/00007632-199607150-00010
  17. Masso, P. D. and G. E. Gorton. 2000. Quantifying changes in standing body segment alignment following spinal instrumentation and fusion in idiopathic scoliosis using an optoelectronic using an optoelectronic measurement system. Spine 25(4): 457-462. https://doi.org/10.1097/00007632-200002150-00011
  18. Nault, M. L., P. Allard, S. Hinse, R. Le Blanc, O. Caron, H. Labelle and H. Sadeghi. 2002. Relations between standing stability and body posture parameters in adolescent idiopathic scoliosis. Spine 27(17):1911-1917. https://doi.org/10.1097/00007632-200209010-00018
  19. Negrini, S., G. Antonini, R. Carabalona and S. Minozzi. 2003. Physical exercises as a treatment for adolescent idiopathic scoliosis. A systematic review. Pediatric Rehabilitation 6(3-4):227-235. https://doi.org/10.1080/13638490310001636781
  20. Poncet, P., S. delorme, J. L. Ronsky, J. Dansereau, J. Harder and G. Clynch. 2000. Reconstruction of laser- scanned 3D torso topography and stereo-radiographical spine and rib-cage geometry in scoliosis. Computer Methods in Biomechanics and Biomedical Engineering 4(1): 59-75.
  21. Quervain, I. A. K., R. Müller, A. Stacoff, D. Grob and E. Stüssi. 2004. Gait analysis in patients with idiopathic scoliosis. European Spine Journal 13(5): 449-456.
  22. Reamy, B. V. and J. B. Slakey. 2001. Adolescent idiopathic scoliosis: review and current concepts. American Family Physician 64(1): 111-116.
  23. Sapkas, G., P. J. Papagelopoulos, K. Kateros, G. L. Koundis, P. J. Boscainos, U. I. Koukou and P. Katonis. 2003. Prediction of Cobb anlge in idiopathic adolescent scoliosis. Clinical orthopaedics and related research 411: 32-39. https://doi.org/10.1097/01.blo.0000068360.47147.30
  24. Soucacos, P. N., K. Zacharis, J. Gelalis, K. Soultanis, N. Kalos, A. Beris, T. Xenakis and E.O. Johnson. 1998. Assessment of curve progression in idiopathic scoliosis. European Spine Journal 7(4):270-277. https://doi.org/10.1007/s005860050074
  25. Stokes, I. A. F., J. G. Armstrong and M. S. Moreland. 1988. Spinal deformity and back surface asymmetry in idiopathic scoliosis. Journal of orthopaedic research 6(1): 129-137. https://doi.org/10.1002/jor.1100060117
  26. Stokes, I. A. F. 1989. Axial rotation component of thoracic scoliosis. Journal of orthopaedic research 7(5): 702-708. https://doi.org/10.1002/jor.1100070511
  27. Stylianides, G. A., M. Beaulieu, G. Dalleau, C. H. Rivard and P. Allard. 2012. Iliac crest orientation and geometry in able-bodied and non-treated adolescent idiopathic scoliosis girls with moderate and severe spinal deformity. European Spine Journal, 21(4):725-732. https://doi.org/10.1007/s00586-011-2070-5
  28. Ylikoski, M. 1993. Spinal growth and progression of adolescent idiopathic scoliosis. European Spine Journal 1(4):236-239. https://doi.org/10.1007/BF00298366
  29. Zabjek, K. F., M. A. Leroux, C. Coillard, F. Prince and C. H. Rivard, FRCS(C), FAAOS, FACS. 2008. Postural characteristics of adolescents with idiopathic scoliosis. Journal of Pediatric Orthopaedics 28(2):218-224. https://doi.org/10.1097/BPO.0b013e3181651bdc
  30. Zhu, F., W. C. Chu, G. Sun, Z. Zhu, W. Wang, J. C. Y. Cheng and Y. Qiu. 2011. Rib length asymmetry in thoracic adolescent idiopathic scoliosis: is it primary or secondary?. European Spine Journal 20(2):254-259. https://doi.org/10.1007/s00586-010-1637-x

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