Prediction of lumbar vertebral body compressive strength of overweight and obese older adults using morphed subject-specific finite-element models to evaluate the effects of weight loss

  • Samantha L. Schoell
  • Kristen M. Beavers
  • Daniel P. Beavers
  • Leon Lenchik
  • Anthony P. Marsh
  • W. Jack Rejeski
  • Joel D. Stitzel
  • Ashley A. Weaver
Original Article



Diet and exercise can promote weight loss in older adults; however, there is potential to increase fracture risk due to loss of bone mineral density (BMD) known to accompany weight loss. Weight loss effects on measures of bone quality and strength are currently unknown.


The purpose of this study is to develop subject-specific finite-element (FE) models of the lumbar spine and study the effect of intentional weight loss on bone strength in a pilot data set.


Computed tomography (CT) scans of the lumbar spine of 30 overweight and obese (mean BMI = 29.7 ± 3.9 kg/m2), older adults (mean age = 65.9 ± 4.6 years) undergoing an 18-month intentional weight loss intervention were obtained at baseline and post-intervention. Measures of volumetric BMD (vBMD) and variable cortical thickness were derived from each subject CT scan. Development of the subject-specific FE models of the lumbar spine involved model morphing techniques to accelerate the development of the models. vBMD-derived material properties and cortical thickness measures were directly mapped to baseline and post-intervention models. Bone strength was estimated through simulation of a quasi-static uniaxial compression test.


From baseline to 18-month post-weight loss intervention, there were statistically significant decreases in estimated bone strength (6.5% decrease; p < 0.05). Adjusting for baseline bone measures and gender revealed no statistically significant correlations between weight change and change in vBMD, cortical thickness, or bone strength.


Integration of CT-based measures and FE models with conventional areal BMD can improve the understanding of the effects of intentional weight loss on bone health.


Obesity Weight loss Lumbar spine strength Finite-element analysis Quantitative computed tomography 



We thank Divya Jain, Caresse Hightower, and Elizabeth Lopez for their assistance with data collection and analysis.


National Institutes of Health (K01 AG047921, R18 HL076441, and P30 AG21332), Wake Forest School of Medicine Translational Science Institute, Wake Forest University Translational Science Center and the National Science Foundation Research Experiences for Undergraduates (REU) under Award No. 1559700. Views expressed are those of the authors and do not represent the views of the sponsors.

Compliance with ethical standards

Conflict of interest

There is no conflict of interest.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Supplementary material

40520_2018_1010_MOESM1_ESM.docx (14 kb)
Supplementary material 1 (DOCX 13 KB)


  1. 1.
    Davies K, Stegman M, Heaney R, et al (1996) Prevalence and severity of vertebral fracture: the saunders county bone quality study. Osteoporis Int 6:160–165CrossRefGoogle Scholar
  2. 2.
    Nevitt MC, Ettinger B, Black DM, et al (1998) The association of radiographically detected vertebral fractures with back pain and function: a prospective study. Ann Intern Med 128:793–800CrossRefPubMedGoogle Scholar
  3. 3.
    Al-Sari U, Tobias J, Clark E (2016) Health-related quality of life in older people with osteoporotic vertebral fractures: a systematic review and meta-analysis. Osteoporis Int 27:2891–2900CrossRefGoogle Scholar
  4. 4.
    Crandall CJ, Yildiz VO, Wactawski-Wende J, et al (2015) Postmenopausal weight change and incidence of fracture: post hoc findings from women’s health initiative observational study and clinical trials. BMJ 350:h25CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Villareal DT, Fontana L, Weiss EP, Racette SB, Steger-May K, Schechtman KB, Klein S, Holloszy JO (2006) Bone mineral density response to caloric restriction–induced weight loss or exercise-induced weight loss: a randomized controlled trial. Arch Intern Med 166:2502–2510CrossRefPubMedGoogle Scholar
  6. 6.
    Villareal DT, Fontana L, Das SK, et al (2016) Effect of two-year caloric restriction on bone metabolism and bone mineral density in non-obese younger adults: a randomized clinical trial. J Bone Miner Res 31:40–51CrossRefPubMedGoogle Scholar
  7. 7.
    D’Elia G, Caracchini G, Cavalli L, et al (2009) Bone fragility and imaging techniques. Clin Cases Miner Bone Metab 6:234–246PubMedPubMedCentralGoogle Scholar
  8. 8.
    Bouxsein ML, Seeman E (2009) Quantifying the material and structural determinants of bone strength. Best Pract Res Clin 23:741–753CrossRefGoogle Scholar
  9. 9.
    Engelke K, van Rietbergen B, Zysset P (2016) FEA to measure bone strength: a review. Clin Rev Bone Miner Metab 14:1–12Google Scholar
  10. 10.
    Siris ES, Chen Y-T, Abbott TA, et al (2004) Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 164:1108–1112CrossRefPubMedGoogle Scholar
  11. 11.
    Netelenbos J, Lems W, Geusens P, et al (2009) Spine radiographs to improve the identification of women at high risk for fractures. Osteoporis Int 20:1347–1352CrossRefGoogle Scholar
  12. 12.
    Hangartner TN, Johnston CC (1990) Influence of fat on bone measurements with dual-energy absorptiometry. Bone Miner 9:71–81CrossRefPubMedGoogle Scholar
  13. 13.
    Brinckmann P, Biggemann M, Hilweg D (1989) Prediction of the compressive strength of human lumbar vertebrae. Clin Biomech 4:iii–i27CrossRefGoogle Scholar
  14. 14.
    Cheng XG, Nicholson PH, Boonen S, et al (1997) Prediction of vertebral strength in vitro by spinal bone densitometry and calcaneal ultrasound. J Bone Miner Res 12:1721–1728CrossRefPubMedGoogle Scholar
  15. 15.
    Edmondston S, Singer K, Day R, et al (1994) In-vitro relationships between vertebral body density, size, and compressive strength the elderly thoracolumbar spine. Clin Biomech 9:180–186CrossRefGoogle Scholar
  16. 16.
    McBroom R, Hayes W, Edwards W, et al (1985) Prediction of vertebral body compressive fracture using quantitative computed tomography. J Bone Jt Surg Am 67:1206–1214CrossRefGoogle Scholar
  17. 17.
    Mosekilde L, Bentzen S, Ørtoft G, et al (1989) The predictive value of quantitative computed tomography for vertebral body compressive strength and ash density. Bone 10:465–470CrossRefPubMedGoogle Scholar
  18. 18.
    Bjarnason K, Hassager C, Svendsen O, et al (1996) Anteroposterior and lateral spinal DXA for the assessment of vertebral body strength: comparison with hip and forearm measurement. Osteoporis Int 6:37–42CrossRefGoogle Scholar
  19. 19.
    Myers BS, Arbogast KB, Lobaugh B, et al (1994) Improved assessment of lumbar vertebral body strength using supine lateral dual-energy X-ray absorptiometry. J Bone Miner Res 9:687–693CrossRefPubMedGoogle Scholar
  20. 20.
    Imai K, Ohnishi I, Bessho M, et al (2006) Nonlinear finite element model predicts vertebral bone strength and fracture site. Spine 31:1789–1794CrossRefPubMedGoogle Scholar
  21. 21.
    Crawford RP, Cann CE, Keaveny TM (2003) Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography. Bone 33:744–750CrossRefPubMedGoogle Scholar
  22. 22.
    Buckley JM, Loo K, Motherway J (2007) Comparison of quantitative computed tomography-based measures in predicting vertebral compressive strength. Bone 40:767–774CrossRefPubMedGoogle Scholar
  23. 23.
    Kopperdahl DL, Aspelund T, Hoffmann PF, et al (2014) Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans. J Bone Miner Res 29:570–580CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Matsumoto T, Ohnishi I, Bessho M, et al (2009) Prediction of vertebral strength under loading conditions occurring in activities of daily living using a computed tomography-based nonlinear finite element method. Spine 34:1464–1469CrossRefPubMedGoogle Scholar
  25. 25.
    Imai K, Ohnishi I, Yamamoto S, et al (2008) In vivo assessment of lumbar vertebral strength in elderly women using computed tomography-based nonlinear finite element model. Spine 33:27–32CrossRefPubMedGoogle Scholar
  26. 26.
    Wang X, Sanyal A, Cawthon PM, et al (2012) Prediction of new clinical vertebral fractures in elderly men using finite element analysis of CT scans. J Bone Miner Res 27:808–816CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Marsh AP, Janssen JA, Ambrosius WT, et al (2013) The Cooperative Lifestyle Intervention Program-II (CLIP-II): design and methods. Contemp Clin Trials 36:382–393CrossRefPubMedGoogle Scholar
  28. 28.
    Rejeski WJ, Ambrosius WT, Burdette JH, et al (2017) Community weight loss to combat obesity and disability in at-risk older adults. J Gerontol A Biol Sci Med Sci. CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Kopperdahl DL, Morgan EF, Keaveny TM (2002) Quantitative computed tomography estimates of the mechanical properties of human vertebral trabecular bone. J Orthop Res 20:801–805CrossRefPubMedGoogle Scholar
  30. 30.
    Shigeta K, Kitagawa Y, Yasuki T Development of next generation human FE model capable of organ injury prediction. In: Proceedings 21st international technical conference on the enhanced safety of vehicles, Stuttgart, Germany (2009) National Highway Traffic Safety Administration, pp 15–18Google Scholar
  31. 31.
    Treece GM, Poole KE, Gee AH (2012) Imaging the femoral cortex: thickness, density and mass from clinical CT. Med Image Anal 16:952–965. pii]CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Treece GM, Gee AH, Mayhew PM, Poole KE (2010) High resolution cortical bone thickness measurement from clinical CT data. Med Image Anal 14:276–290. pii]CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Bookstein FL (1997) Morphometric tools for landmark data: geometry and biology. Cambridge University Press, CambridgeGoogle Scholar
  34. 34.
    Schoell SL, Weaver AA, Urban JE, et al (2015) Development and validation of an older occupant finite element model of a mid-sized male for investigation of age-related injury risk. Stapp Car Crash J 59:359–383PubMedGoogle Scholar
  35. 35.
    Schoell SL, Weaver AA, Vavalle NA, et al (2015) Age and sex-specific thorax finite element model development and simulation. Traffic Inj Prev 16(sup1):S57–S65CrossRefPubMedGoogle Scholar
  36. 36.
    Vavalle NA, Schoell SL, Weaver AA, et al (2014) Application of radial basis function methods in the development of a 95th percentile male seated fea model. Stapp Car Crash J 58:361–384PubMedGoogle Scholar
  37. 37.
    Iwamoto M, Nakahira Y, Kimpara H (2015) Development and validation of the Total HUman Model for Safety (THUMS) toward further understanding of occupant injury mechanisms in precrash and during crash. Traffic Inj Prev 16(sup1):S36–S48CrossRefPubMedGoogle Scholar
  38. 38.
    Schultz A, Warwick D, Berkson M, et al (1979) Mechanical properties of human lumbar spine motion segments—part I: responses in flexion, extension, lateral bending, and torsion. J Biomech Eng 101:46–52CrossRefGoogle Scholar
  39. 39.
    Begeman P, Visarius H, Nolte L-P, et al (1994) Visocelastic shear responses of the cadaver and Hybrid III lumbar spine. Stapp Car Crash J 38:1–14Google Scholar
  40. 40.
    Weaver AA, Nguyen CM, Schoell SL, et al (2015) Image segmentation and registration algorithm to collect thoracic skeleton semilandmarks for characterization of age and sex-based thoracic morphology variation. Comput Biol Med 67: 41–48CrossRefGoogle Scholar
  41. 41.
    Weaver AA, Schoell SL, Stitzel JD (2014) Morphometric analysis of variation in the ribs with age and sex. J Anat 225:246–261. CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Schileo E, Taddei F, Cristofolini L, et al (2008) Subject-specific finite element models implementing a maximum principal strain criterion are able to estimate failure risk and fracture location on human femurs tested in vitro. J Biomech 41:356–367CrossRefPubMedGoogle Scholar
  43. 43.
    Kopperdahl DL, Keaveny TM (1998) Yield strain behavior of trabecular bone. J Biomech 31:601–608CrossRefPubMedGoogle Scholar
  44. 44.
    Liebschner MA, Kopperdahl DL, Rosenberg WS, et al (2003) Finite element modeling of the human thoracolumbar spine. Spine 28:559–565PubMedGoogle Scholar
  45. 45.
    Morgan EF, Bayraktar HH, Keaveny TM (2003) Trabecular bone modulus–density relationships depend on anatomic site. J Biomech 36:897–904CrossRefPubMedGoogle Scholar
  46. 46.
    Silva M, Gibson L (1997) Modeling the mechanical behavior of vertebral trabecular bone: effects of age-related changes in microstructure. Bone 21:191–199CrossRefPubMedGoogle Scholar
  47. 47.
    Zibellini J, Sainsbury RV, Lee CM, et al (2015) Does diet-induced weight loss lead to bone loss in overweight or obese adults? A systematic review and meta-analysis of clinical trials. J Bone Miner Res 30:2168–2178CrossRefPubMedGoogle Scholar
  48. 48.
    Allison SJ, Poole KE, Treece GM, et al (2015) The influence of high-impact exercise on cortical and trabecular bone mineral content and 3D distribution across the proximal femur in older men: a randomized controlled unilateral intervention. J Bone Miner Res 30:1709–1716CrossRefPubMedGoogle Scholar
  49. 49.
    Ensrud KE (2013) Epidemiology of fracture risk with advancing age. J Gerontol A Biol Sci Med Sci 68:1236–1242CrossRefPubMedGoogle Scholar
  50. 50.
    Nevitt MC, Cummings SR, Stone KL, et al (2005) Risk factors for a first-incident radiographic vertebral fracture in women ≥ 65 years of age: the study of osteoporotic fractures. J Bone Miner Res 20:131–140CrossRefPubMedGoogle Scholar
  51. 51.
    Shah K, Armamento-Villareal R, Parimi N, et al (2011) Exercise training in obese older adults prevents increase in bone turnover and attenuates decrease in hip bone mineral density induced by weight loss despite decline in bone-active hormones. J Bone Miner Res 26:2851–2859CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Kohrt W, Bloomfield S, Little K, et al (2004) Physical activity and bone health. Position stand of the American College of Sports Medicine. Med Sci Sports Exerc 36:1985–1996CrossRefPubMedGoogle Scholar
  53. 53.
    Shapses SA, Sukumar D (2012) Bone metabolism in obesity and weight loss. Annu Rev Nutr 32:287CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Orwoll ES, Oviatt SK, Mann T (1990) The impact of osteophytic and vascular calcifications on vertebral mineral density measurements in men. J Clin Endocrinol Metab 70:1202–1207CrossRefPubMedGoogle Scholar
  55. 55.
    Masud T, Langley S, Wiltshire P, et al (1993) Effect of spinal osteophytosis on bone mineral density measurements in vertebral osteoporosis. BMJ 307(6897):172CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Homminga J, Weinans H, Gowin W, et al (2001) Osteoporosis changes the amount of vertebral trabecular bone at risk of fracture but not the vertebral load distribution. Spine 26:1555–1560CrossRefPubMedGoogle Scholar
  57. 57.
    Buckley JM, Leang DC, Keaveny TM (2006) Sensitivity of vertebral compressive strength to endplate loading distribution. J Biomech Eng 128:641–646CrossRefPubMedGoogle Scholar
  58. 58.
    Crawford RP, Rosenberg WS, Keaveny TM (2003) Quantitative computed tomography-based finite element models of the human lumbar vertebral body: effect of element size on stiffness, damage, and fracture strength predictions. J Biomech Eng 125:434–438CrossRefPubMedGoogle Scholar
  59. 59.
    Dall’Ara E, Pahr D, Varga P, et al (2012) QCT-based finite element models predict human vertebral strength in vitro significantly better than simulated DEXA. Osteoporis Int 23:563–572CrossRefGoogle Scholar
  60. 60.
    Viceconti M, Bellingeri L, Cristofolini L, et al (1998) A comparative study on different methods of automatic mesh generation of human femurs. Med Eng Phys 20:1–10CrossRefPubMedGoogle Scholar
  61. 61.
    Chevalier Y, Charlebois M, Pahr D, et al (2008) A patient-specific finite element methodology to predict damage accumulation in vertebral bodies under axial compression, sagittal flexion and combined loads. Comput Methods Biomech Biomed Engin 11:477–487CrossRefPubMedGoogle Scholar
  62. 62.
    Jones AC, Wilcox RK (2008) Finite element analysis of the spine: towards a framework of verification, validation and sensitivity analysis. Med Eng Phys 30:1287–1304CrossRefPubMedGoogle Scholar
  63. 63.
    Schoell SL, Weaver AA, Beavers DP, et al (2018) Development of subject-specific proximal femur finite element models of older adults with obesity to evaluate the effects of weight loss on bone strength. J Osteoporos Phys Act. PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Keller T, Ziv I, Moeljanto E, et al (1993) Interdependence of lumbar disc and subdiscal bone properties: a report of the normal and degenerated spine. Clin Spine Surg 6:106–113Google Scholar
  65. 65.
    Buckley JM, Cheng L, Loo K, et al (2007) Quantitative computed tomography-based predictions of vertebral strength in anterior bending. Spine 32:1019–1027CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Biomedical Engineering, Medical Center BlvdWake Forest University School of MedicineWinston-SalemUSA
  2. 2.Department of Health and Exercise ScienceWake Forest UniversityWinston-SalemUSA
  3. 3.Department of Biostatistical SciencesWake Forest University School of MedicineWinston-SalemUSA
  4. 4.Department of RadiologyWake Forest University School of MedicineWinston-SalemUSA

Personalised recommendations