Clinical Neuroradiology

, Volume 29, Issue 4, pp 645–651 | Cite as

MDCT-based Finite Element Analysis of Vertebral Fracture Risk: What Dose is Needed?

  • D. Anitha
  • Kai Mei
  • Michael Dieckmeyer
  • Felix K. Kopp
  • Nico Sollmann
  • Claus Zimmer
  • Jan S. Kirschke
  • Peter B. Noel
  • Thomas Baum
  • Karupppasamy SubburajEmail author
Original Article



The aim of this study was to compare vertebral failure loads, predicted from finite element (FE) analysis of patients with and without osteoporotic vertebral fractures (OVF) at virtually reduced dose levels, compared to standard-dose exposure from multidetector computed tomography (MDCT) imaging and evaluate whether ultra-low dose derived FE analysis can still differentiate patient groups.

Materials and Methods

An institutional review board (IRB) approval was obtained for this retrospective study. A total of 16 patients were evaluated at standard-dose MDCT; eight with and eight without OVF. Images were reconstructed at virtually reduced dose levels (i. e. half, quarter and tenth of the standard dose). Failure load was determined at L1–3 from FE analysis and compared between standard, half, quarter, and tenth doses and used to differentiate between fracture and control groups.


Failure load derived at standard dose (3254 ± 909 N and 3794 ± 984 N) did not significantly differ from half (3390 ± 890 N and 3860 ± 1063 N) and quarter dose (3375 ± 915 N and 3925 ± 990 N) but was significantly higher for one tenth dose (4513 ± 1762 N and 4766 ± 1628 N) for fracture and control groups, respectively. Failure load differed significantly between the two groups at standard, half and quarter doses, but not at tenth dose. Receiver operating characteristic (ROC) curve analysis also demonstrated that standard, half, and quarter doses can significantly differentiate the fracture from the control group.


The use of MDCT enables a dose reduction of at least 75% compared to standard-dose for an adequate prediction of vertebral failure load based on non-invasive FE analysis.


Multidetector computed tomography Radiation dosage Spinal fractures Finite element analysis Osteoporosis 



This study received funding by the Deutsche Forschungsgemeinschaft (DFG) BA 4906/2-1 (TB), and TUM Faculty of Medicine KKF grant H01 (TB).

Conflict of interest

D. Anitha, K. Mei, M. Dieckmeyer, F.K. Kopp, N. Sollmann, C. Zimmer, J.S. Kirschke, P.B. Noel, T. Baum and K. Subburaj declare that they have no competing interests.


  1. 1.
    Francis RM, Aspray TJ, Hide G, Sutcliffe AM, Wilkinson P. Back pain in osteoporotic vertebral fractures. Osteoporos Int. 2008;19:895–903.CrossRefPubMedGoogle Scholar
  2. 2.
    Schuit SC, van der Klift M, Weel AE, de Laet CE, Burger H, Seeman E, Hofman A, Uitterlinden AG, van Leeuwen JP, Pols HA. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone. 2004;34:195–202.CrossRefGoogle Scholar
  3. 3.
    Wang X, Sanyal A, Cawthon PM, Palermo L, Jekir M, Christensen J, Ensrud KE, Cummings SR, Orwoll E, Black DM; Osteoporotic Fractures in Men (MrOS) Research Group, Keaveny TM. Prediction of new clinical vertebral fractures in elderly men using finite element analysis of CT scans. J Bone Miner Res. 2012;27:808–16.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Kopperdahl DL, Aspelund T, Hoffmann PF, Sigurdsson S, Siggeirsdottir K, Harris TB, Gudnason V, Keaveny TM. Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans. J Bone Miner Res. 2014;29:570–80.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Anitha D, Subburaj K, Mei K, Kopp FK, Foehr P, Noel PB, Kirschke JS, Baum T. Effects of dose reduction on bone strength prediction using finite element analysis. Sci Rep. 2016;6:38441.CrossRefGoogle Scholar
  6. 6.
    Anitha D, Subburaj K, Baum T, Kirschke JS. Vertebral stability in multiple myeloma patients: a finite-element study. European Orthopaedic Research Society 24th Annual Meeting; Bologna, Italy. 2016.Google Scholar
  7. 7.
    Bauer JS, Sidorenko I, Mueller D, Baum T, Issever AS, Eckstein F, Rummeny EJ, Link TM, Raeth CW. Prediction of bone strength by muCT and MDCT-based finite-element-models: how much spatial resolution is needed? Eur J Radiol. 2014;83:e36–42.CrossRefPubMedGoogle Scholar
  8. 8.
    Liebl H, Garcia EG, Holzner F, Noel PB, Burgkart R, Rummeny EJ, Baum T, Bauer JS. In-vivo assessment of femoral bone strength using Finite Element Analysis (FEA) based on routine MDCT imaging: a preliminary study on patients with vertebral fractures. PLoS One. 2015;10:e116907.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Yi JW, Park HJ, Lee SY, Rho MH, Hong HP, Choi YJ, Kim MS. Radiation dose reduction in multidetector CT in fracture evaluation. Br J Radiol. 2017;90(1077):20170240.CrossRefGoogle Scholar
  10. 10.
    Wiest PW, Locken JA, Heintz PH, Mettler FA Jr.. CT scanning: a major source of radiation exposure. Semin Ultrasound Ct Mr. 2002;23:402–10.CrossRefGoogle Scholar
  11. 11.
    Costello JE, Cecava ND, Tucker JE, Bau JL. CT radiation dose: current controversies and dose reduction strategies. AJR Am J Roentgenol. 2013;201:1283–90.CrossRefGoogle Scholar
  12. 12.
    Pontana F, Duhamel A, Pagniez J, Flohr T, Faivre JB, Hachulla AL, Remy J, Remy-Jardin M. Chest computed tomography using iterative reconstruction vs filtered back projection (Part 2): image quality of low-dose CT examinations in 80 patients. Eur Radiol. 2011;21:636–43.CrossRefGoogle Scholar
  13. 13.
    Niu YT, Mehta D, Zhang ZR, Zhang YX, Liu YF, Kang TL, Xian JF, Wang ZC. Radiation dose reduction in temporal bone CT with iterative reconstruction technique. AJNR Am J Neuroradiol. 2012;33:1020–6.CrossRefGoogle Scholar
  14. 14.
    Silva AC, Lawder HJ, Hara A, Kujak J, Pavlicek W. Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm. AJR Am J Roentgenol. 2010;194:191–9.CrossRefGoogle Scholar
  15. 15.
    Konda SR, Goch AM, Leucht P, Christiano A, Gyftopoulos S, Yoeli G, Egol KA. The use of ultra-low-dose CT scans for the evaluation of limb fractures. Bone Jt J. 2016;98-B:1668–73.CrossRefGoogle Scholar
  16. 16.
    Mulkens TH, Marchal P, Daineffe S, Salgado R, Bellinck P, te Rijdt B, Kegelaers B, Termote JL. Comparison of low-dose with standard-dose multidetector CT in cervical spine trauma. AJNR Am J Neuroradiol. 2007;28:1444–50.CrossRefGoogle Scholar
  17. 17.
    Zabić S, Wang Q, Morton T, Brown KM. A low dose simulation tool for CT systems with energy integrating detectors. Med Phys. 2013;40:31102.CrossRefGoogle Scholar
  18. 18.
    Mei K, Kopp FK, Bippus R, Köhler T, Schwaiger BJ, Gersing AS, Fehringer A, Sauter A, Münzel D, Pfeiffer F, Rummeny EJ, Kirschke JS, Noël PB, Baum T. Is multidetector CT-based bone mineral density and quantitative bone microstructure assessment at the spine still feasible using ultra-low tube current and sparse sampling? Eur Radiol. 2017;27:5261–71.CrossRefGoogle Scholar
  19. 19.
    Huber MB, Carballido-Gamio J, Bauer JS, Baum T, Eckstein F, Lochmüller EM, Majumdar S, Link TM. Proximal femur specimens: Automated 3D trabecular bone mineral density analysis at multidetector CT—Correlation with biomechanical strength measurement. Radiology. 2008;247:472–81.CrossRefGoogle Scholar
  20. 20.
    Rho JY, Hobatho MC, Ashman RB. Relations of mechanical properties to density and CT numbers in human bone. Med Eng Phys. 1995;17:347–55.CrossRefGoogle Scholar
  21. 21.
    Goulet RW, Goldstein SA, Ciarelli MJ, Kuhn JL, Brown MB, Feldkamp LA. The relationship between the structural and orthogonal compressive properties of trabecular bone. J Biomech. 1994;27:375–89.CrossRefPubMedGoogle Scholar
  22. 22.
    Keller TS. Predicting the compressive mechanical behavior of bone. J Biomech. 1994;27:1159–68.CrossRefGoogle Scholar
  23. 23.
    Keyak JH. Improved prediction of proximal femoral fracture load using nonlinear finite element models. Med Eng Phys. 2001;23:165–73.CrossRefGoogle Scholar
  24. 24.
    Keyak JH, Lee IY, Skinner HB. Correlations between orthogonal mechanical-properties and density of trabecular bone—use of different densitometric measures. J Biomed Mater Res. 1994;28:1329–36.CrossRefGoogle Scholar
  25. 25.
    Keyak JH, Falkinstein Y. Comparison of in situ and in vitro CT scan-based finite element model predictions of proximal femoral fracture load. Med Eng Phys. 2003;25:781–7.CrossRefGoogle Scholar
  26. 26.
    Crawford RP, Cann CE, Keaveny TM. Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography. Bone. 2003;33:744–50.CrossRefGoogle Scholar
  27. 27.
    Imai K. Analysis of vertebral bone strength, fracture pattern, and fracture location: a validation study using a computed tomography-based nonlinear finite element analysis. Aging Dis. 2015;6:180–7.CrossRefGoogle Scholar
  28. 28.
    Giavarina D. Understanding Bland Altman analysis. Biochem Med (Zagreb). 2015;25:141–51.CrossRefGoogle Scholar
  29. 29.
    Tack D, Jahnen A, Kohler S, Harpes N, De Maertelaer V, Back C, Gevenois PA. Multidetector CT radiation dose optimisation in adults: short- and long-term effects of a clinical audit. Eur Radiol. 2014;24:169–75.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Engineering Product Development (EPD) PillarSingapore University of Technology and Design (SUTD)SingaporeSingapore
  2. 2.Department of Radiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  3. 3.Department of Neuroradiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany

Personalised recommendations