Advertisement

Cluster Computing

, Volume 22, Supplement 6, pp 15111–15119 | Cite as

Morphometric analysis of X-ray and CT images for evaluating osteoporosis

  • N. ShankarEmail author
  • S. Sathish Babu
  • C. Viswanathan
Article
  • 72 Downloads

Abstract

Osteoporosis is a diminishing of the bone that prompts break with least compel. It influences postmenopausal ladies and elderly of both sexual orientations. Bone mineral density (BMD) is one of the parameter identified with bone quality. Double energy x-beam absorptiometry (DXA) is at present considered as the “highest quality level” for measuring BMD. Morphometric analysis of femur bone is done on both radiographic images and Computed tomography image. An aggregate number of 50 (n = 50) Indian ladies, 18 solid pre menopausal ladies (n = 18, 36.3 ± 8.7 years) and 32 post menopausal ladies (n = 32, 58 ± 9.1 years) whose age extended from 20 to 85 years were incorporated. The patients are subjected to take X-ray,CT and DXA. The outcomes gotten by DXA found that 20 and 34% of the Indian ladies were having osteoporosis and osteopenia separately. Using SPSS software, the morphometrics analysis like neck of the bone, width of the neck, thickness of shaft, width of acetabular bone is measured and in CT images using MIMICS software the Hounsfield is measured in neck of femur, trochanter head and shaft. Est volume is calculated through measured Hounsfield unit. These qualities were observed to be diminished by − 29%, − 23, − 17, − 15, and − 10% separately, when contrasting with typical Indian ladies. The obtained square of the correlation coefficients (r2) were 0.22, 0.25, 0.23, 0.41, and 0.34 respectively. In osteoporotic women, The estimated volume of femur neck were significantly reduced by 71.8% and in measured BMD DXA value is reduced by 36.7% compared with normal women. Further, osteoporotic women, the mean values of BMD-DXA as well as Est-vol.BMD of trochanter were significantly (p = 0.01) reduced by 45.7 and 80.2% respectively, when comparing to normal healthy women. The femur neck and aggregate hip BMD and Singh’s list were lesser by 41.6 and 33.7, 40% (p < 0.01) individually in osteoporotic post-menopausal ladies, contrasting with typical post-menopausal ladies. The mean estimations of range and the volume of the proximal neck were diminished − 20% and − 21% in the osteoporotic Indian ladies than in typical Indian ladies.

Keywords

Index term—computed tomography X-ray Dexa Indian postmenopausal women 

References

  1. 1.
    Gandhi, A.B., Shukla, A.K.R.: Evaluation of BMD of women above 40 years of age. J. Obstet. Gynecol. India 55(3), 265–267 (2005)Google Scholar
  2. 2.
  3. 3.
    Pramudito, J.T., Soegijoko, S., Mengko, T.R., Muchtadi, F.I., Wachjudi, R.G.: Trabecular pattern analysis of proximal femur radiographs for osteoporosis detection. J. Biomed. Pharma. Eng. 1(1), 45–51 (2007)Google Scholar
  4. 4.
    Hui, S.L., Slemenda, C.W., Johnston Jr., C.C.: Age and bone mass as predictors of fracture in a prospective study. J. Clin. Invest. 81, 1804–1809 (1988)CrossRefGoogle Scholar
  5. 5.
    Chapuy, M.C., Arlot, M.E., Dubocuf, F., Brun, J., Crouzet, B., Arnaud, S., Delmas, P.D., Meunier, P.J.: Vitamin D3 and calcium to prevent hip fractures in elderly women. N. Engl. J. Med. 327, 1637–1642 (1992)CrossRefGoogle Scholar
  6. 6.
    Tothil, P.: Methods of bone mineral measurement-review article. Phys. Med. Biol. 34, 543–572 (1989)CrossRefGoogle Scholar
  7. 7.
    Anburajan, M.: Evaluation of osteoporosis using conventional radiographic methods and dual energy x-ray absorptiometry. PhD Thesis, Anna University, Chennai (1999)Google Scholar
  8. 8.
    Gluer, C.C., Cummings, S.R., Pressman, A., Li, J., Gluer, K., Faulkner, K.G., Grampp, S., Geant, H.K.: Prediction of hip fractures from pelvic radiographs: the study of osteoporotic fractures. J Bone Min. Res. 9, 671–677 (1994)CrossRefGoogle Scholar
  9. 9.
    Soontrapa, S., Soontrapa, S., Srinakarin, J., Chowchuene, P.: Singh index screening for femoral neck osteoporosis. J. Med. Assoc. Thail. 88, S13 (2005)Google Scholar
  10. 10.
    http://www.medassocthai.org/journal. Accessed 30 Sept 2010
  11. 11.
  12. 12.
    Gregory, J.S., Aspden, R.M.: Femoral geometry as a risk factor for osteoporotic hip fracture in men and women. J. Med. Eng. Phys. 30, 1275–1286 (2008)CrossRefGoogle Scholar
  13. 13.
    Faulkner, K.G., Cummings, S.R., Black, D., Palemol, L., Gliier, C.C., Genant, H.K.: Simple measurements of femoral geometry predicts hip fracture, the study of osteoporotic fracture. J. Bone Miner. Res. 8, 1211 (1993)CrossRefGoogle Scholar
  14. 14.
    Dretakis, E.K., Papakistou, E., Kontakis, G.M., Dretakis, K., Psarakis, S., Streiopoulos, K.A.: Bone mineral density, Body mass index and hip axis length in post menopausal cretan women with cervical and trochanteric fractures. J. Cal. Tissue Int. 64, 257–258 (1999)CrossRefGoogle Scholar
  15. 15.
    Anburajan, M., Rethinasabapathi, C., Paul Korath, M., Ponnappa, B.G., Paul Korath, M., Jagadeesan, K.: Evaluation of post-menopausal osteoporosis using DXA, Singh’s index, radiographic hip geometry, and serum biochemical analysis: a comparison. JIMSA 14, 186–190 (2001)Google Scholar
  16. 16.
    Masud, T., Jawed, S., Doyle, D., Spector, T.D.: A population study of the screening potential of assessment of trabecular pattern of the femoral neck (Singh’s index): the Chingford study. Br. J. Radiol. 68, 389–393 (1995)CrossRefGoogle Scholar
  17. 17.
    Hauschild, O., Ghanem, N., Oberst, M., Baumann, T., Kreuz, P.C., Langer, M., Suedkamp, N.P., Niemeyer, P.: Evaluation of Singh index for assessment of osteoporosis using digital radiography. Eur. J. Radiol. 71(1), 152–158 (2008)CrossRefGoogle Scholar
  18. 18.
    Koot, V.C.M., Kesselaer, S.M., Clevers, G.J., Dehooge, P., Wetts, T., Werken, C.: Evaluation of the singh index for measuring osteoporosis. J. Bone Joint Surg. Br. 78-B(5), 831–834 (1996)Google Scholar
  19. 19.
    Chung, C.Y., Son, Y.C., Bae, J.B., Park, B.J.: Evaluation of the Singh index for measurement of osteoporosis. J. Osteoporos. Int. 34(5), 871–875 (1999)Google Scholar
  20. 20.
    Singh, M., Nagrath, A.R., Maini, P.S.: Changes in trabecular pattern of the upper end of the femur as an index of osteoporosis. J. Bone Joint Surg. Am. 52, 457–467 (1970)CrossRefGoogle Scholar
  21. 21.
    Jiang, H.X., Majumdar, S.R., Dick, D.A., Moreau, M., Raso, J., Johnston, D.: Development and initial validation of a risk score for predicting in-hospital and 1-year mortality in patients with hip fractures. J. Bone Miner. Res. 20(3), 494–500 (2005)CrossRefGoogle Scholar
  22. 22.
    Gandhi, B., Shukla, A.K.R.: Evaluation of BMD of women above 40 years of age. J. Obstet. Gynecol India 55(3), 265–267 (2005)Google Scholar
  23. 23.
    Baum, T., Carballido-Gamio, J., Huber, M.B., Müller, D., Monetti, R., Räth, C., Eckstein, F., Lochmüller, E.M., Majumdar, S., Rummeny, E.J., Link, T.M., Bauer, J.S.: Automated 3D trabecular bone structure analysis of the proximal femur-prediction of biomechanical strength by CT and DXA. Osteoporos. Int. 21, 1553–1564 (2009)CrossRefGoogle Scholar
  24. 24.
    Hui, S.L., Slemenda Jr., C.W., Johnston, C.C.: Age and bone mass as predictors of fracture in a prospective study. J. Clin. Invest. 81, 1804–1809 (1988)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of E&IAnnamalai UniversityChidambaramIndia
  2. 2.Department of ECEGRT Institute of Engineering & TechnologyTiruttaniIndia

Personalised recommendations