Abstract
Summary
Millions of CT scans are performed annually and could be also used to opportunistically assess musculoskeletal health; however, it is unknown how well this secondary assessment relates to osteoporotic fracture. This study demonstrates that opportunistic CT screening is a promising tool to predict individuals with previous osteoporotic fracture.
Introduction
Opportunistic computed tomography (oCT) screening for osteoporosis and fracture risk determination complements current dual X-ray absorptiometry (DXA) diagnosis. This study determined major osteoporotic fracture prediction by oCT at the spine and hip from abdominal CT scans.
Methods
Initial 1158 clinical abdominal CT scans were identified from administrative databases and were the basis to generate a cohort of 490 men and women with suitable abdominal CT scans. Participant CT scans met the following criteria: over 50 years of age, the scan had no image artifacts, and the field-of-view included the L4 vertebra and proximal femur. A total of 123 participants were identified as having previously suffered a fracture within 5 years of CT scan date. Fracture cause was identified from clinical data and used to create a low-energy fracture sub-cohort. At each skeletal site, bone mineral density (BMD) and finite element (FE)-estimated bone strength were determined. Logistic regression predicted fracture and receiver-operator characteristic curves analyzed prediction capabilities.
Results
In participants with a fracture, low-energy fractures occurred in 88% of women and 79% of men. Fracture prediction by combining both BMD and FE-estimated bone strength was not statistically different than using either BMD or FE-estimated bone strength alone. Predicting low-energy fractures in women determined the greatest AUC of 0.710 by using both BMD and FE-estimated bone strength.
Conclusions
oCT screening using abdominal CT scans is effective at predicting individuals with previous fracture at major osteoporotic sites and offers a promising screening tool for skeletal health assessment.
This is a preview of subscription content, access via your institution.



Abbreviations
- aBMD:
-
Areal bone mineral density
- AUC:
-
Area under the receiver-operator characteristic curve
- BMD:
-
Bone mineral density
- CT:
-
Computed tomography
- DXA:
-
Dual X-ray absorptiometry
- FE:
-
Finite element
- ICD-10:
-
International Classification of Diseases 10th Revision
- KUB:
-
Kidney, urinary, and bladder
- oCT:
-
Opportunistic computed tomography
- ROC:
-
Receiver-operator characteristic curve
References
- 1.
Bouxsein ML, Kaufman J, Tosi L, Cummings S, Lane J, Johnell O (2004) Recommendations for optimal care of the fragility fracture patient to reduce the risk of future fracture. J Am Acad Orthop Surg 12:385–395. https://doi.org/10.5435/00124635-200411000-00003
- 2.
Budhia S, Mikyas Y, Tang M, Badamgarav E (2012) Osteoporotic fractures: a systematic review of U.S. healthcare costs and resource utilization. PharmacoEconomics 30:147–170. https://doi.org/10.2165/11596880-000000000-00000
- 3.
Cauley JA, Thompson DE, Ensrud KC, Scott JC, Black D (2000) Risk of mortality following clinical fractures. Osteoporos Int 11:556–561. https://doi.org/10.1007/s001980070075
- 4.
Kanis JA, Oden A, Johnell O, Jonsson B, de Laet C, Dawson A (2001) The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 12:417–427. https://doi.org/10.1007/s001980170112
- 5.
O’Malley CD, Johnston SS, Lenhart G et al (2011) Trends in dual-energy X-ray absorptiometry in the United States, 2000–2009. J Clin Densitom 14:100–107. https://doi.org/10.1016/j.jocd.2011.03.003
- 6.
Sinclair A, Morrison A, Young C, Pyke L (2018) The Canadian Medical Imaging Inventory, 2017. CADTH, Ottawa
- 7.
Schileo E, Balistreri L, Grassi L, Cristofolini L, Taddei F (2014) To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations? J Biomech 47:3531–3538. https://doi.org/10.1016/j.jbiomech.2014.08.024
- 8.
Nishiyama KK, Gilchrist S, Guy P, Cripton P, Boyd SK (2013) Proximal femur bone strength estimated by a computationally fast finite element analysis in a sideways fall configuration. J Biomech 46:1231–1236. https://doi.org/10.1016/j.jbiomech.2013.02.025
- 9.
Crawford RP, Cann CE, Keaveny TM (2003) Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography. Bone 33:744–750
- 10.
Keyak JH, Kaneko TS, Tehranzadeh J, Skinner HB (2005) Predicting proximal femoral strength using structural engineering models. Clin Orthop Relat Res:219–228
- 11.
Lee SJ, Graffy PM, Zea RD, Ziemlewicz TJ, Pickhardt PJ (2018) Future osteoporotic fracture risk related to lumbar vertebral trabecular attenuation measured at routine body CT. J Bone Miner Res 33:860–867
- 12.
Emohare O, Cagan A, Morgan R, Davis R, Asis M, Switzer J, Polly DW Jr (2014) The use of computed tomography attenuation to evaluate osteoporosis following acute fractures of the thoracic and lumbar vertebra. Geriatr Orthop Surg Rehabil 5:50–55. https://doi.org/10.1177/2151458514525042
- 13.
Emohare O, Cagan A, Polly DW, Gertner E (2015) Opportunistic computed tomography screening shows a high incidence of osteoporosis in ankylosing spondylitis patients with acute vertebral fractures. J Clin Densitom 18:17–21. https://doi.org/10.1016/j.jocd.2014.07.006
- 14.
Pickhardt PJ, Pooler BD, Lauder T, del Rio AM, Bruce RJ, Binkley N (2013) Opportunistic screening for osteoporosis using abdominal computed tomography scans obtained for other indications. Ann Intern Med 158:588–595. https://doi.org/10.7326/0003-4819-158-8-201304160-00003
- 15.
Black DM, Bouxsein ML, Marshall LM, Cummings SR, Lang TF, Cauley JA, Ensrud KE, Nielson CM, Orwoll ES, Osteoporotic Fractures in Men (MrOS) Research Group (2008) Proximal femoral structure and the prediction of hip fracture in men: a large prospective study using QCT. J Bone Miner Res 23:1326–1333. https://doi.org/10.1359/jbmr.080316
- 16.
Bousson VD, Adams J, Engelke K, Aout M, Cohen-Solal M, Bergot C, Haguenauer D, Goldberg D, Champion K, Aksouh R, Vicaut E, Laredo JD (2011) In vivo discrimination of hip fracture with quantitative computed tomography: results from the prospective European Femur Fracture Study (EFFECT). J Bone Miner Res Off J Am Soc Bone Miner Res 26:881–893. https://doi.org/10.1002/jbmr.270
- 17.
Cheng X, Li J, Lu Y, Keyak J, Lang T (2007) Proximal femoral density and geometry measurements by quantitative computed tomography: association with hip fracture. Bone 40:169–174. https://doi.org/10.1016/j.bone.2006.06.018
- 18.
Nishiyama KK, Ito M, Harada A, Boyd SK (2014) Classification of women with and without hip fracture based on quantitative computed tomography and finite element analysis. Osteoporos Int 25:619–626. https://doi.org/10.1007/s00198-013-2459-6
- 19.
Adams AL, Fischer H, Kopperdahl DL, Lee DC, Black DM, Bouxsein ML, Fatemi S, Khosla S, Orwoll ES, Siris ES, Keaveny TM (2018) Osteoporosis and hip fracture risk from routine computed tomography scans: the Fracture, Osteoporosis, and CT Utilization Study (FOCUS). J Bone Miner Res Off J Am Soc Bone Miner Res 33:1291–1301. https://doi.org/10.1002/jbmr.3423
- 20.
Wang X, Sanyal A, Cawthon PM, Palermo L, Jekir M, Christensen J, Ensrud KE, Cummings SR, Orwoll E, Black DM, for the Osteoporotic Fractures in Men (MrOS) Research Group, Keaveny TM (2012) Prediction of new clinical vertebral fractures in elderly men using finite element analysis of CT scans. J Bone Miner Res 27:808–816. https://doi.org/10.1002/jbmr.1539
- 21.
Lee DC, Hoffmann PF, Kopperdahl DL, Keaveny TM (2017) Phantomless calibration of CT scans for measurement of BMD and bone strength-Inter-operator reanalysis precision. Bone 103:325–333. https://doi.org/10.1016/j.bone.2017.07.029
- 22.
Lee SJ, Anderson PA, Pickhardt PJ (2017) Predicting future hip fractures on routine abdominal CT using opportunistic osteoporosis screening measures: a matched case-control study. Am J Roentgenol 209:395–402. https://doi.org/10.2214/AJR.17.17820
- 23.
Michalski AS, Besler BA, Michalak GJ, Boyd SK (2020) CT-based internal density calibration for opportunistic skeletal assessment using abdominal CT scans. Med Eng Phys 78:55–63. https://doi.org/10.1016/j.medengphy.2020.01.009
- 24.
Mueller DK, Kutscherenko A, Bartel H, Vlassenbroek A, Ourednicek P, Erckenbrecht J (2011) Phantom-less QCT BMD system as screening tool for osteoporosis without additional radiation. Eur J Radiol 79:375–381. https://doi.org/10.1016/j.ejrad.2010.02.008
- 25.
Therkildsen J, Thygesen J, Winther S, Svensson M, Hauge EM, Böttcher M, Ivarsen P, Jørgensen HS (2018) Vertebral bone mineral density measured by quantitative computed tomography with and without a calibration phantom: a comparison between 2 different software solutions. J Clin Densitom Off J Int Soc Clin Densitom 21:367–374. https://doi.org/10.1016/j.jocd.2017.12.003
- 26.
Weaver AA, Beavers KM, Hightower RC, Lynch SK, Miller AN, Stitzel JD (2015) Lumbar bone mineral density phantomless computed tomography measurements and correlation with age and fracture incidence. Traffic Inj Prev 16(Suppl 2):S153–S160. https://doi.org/10.1080/15389588.2015.1054029
- 27.
Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31:1116–1128. https://doi.org/10.1016/j.neuroimage.2006.01.015
- 28.
Keaveny TM (2010) Biomechanical computed tomography-noninvasive bone strength analysis using clinical computed tomography scans. Ann N Y Acad Sci 1192:57–65. https://doi.org/10.1111/j.1749-6632.2009.05348.x
- 29.
Keyak JH, Koyama AK, LeBlanc A, Lu Y, Lang TF (2009) Reduction in proximal femoral strength due to long-duration spaceflight. Bone 44:449–453. https://doi.org/10.1016/j.bone.2008.11.014
- 30.
Michalski AS, Edwards WB, Boyd SK (2019) The influence of reconstruction kernel on bone mineral and strength estimates using quantitative computed tomography and finite element analysis. J Clin Densitom Off J Int Soc Clin Densitom 22:219–228. https://doi.org/10.1016/j.jocd.2017.09.001
- 31.
Keller TS (1994) Predicting the compressive mechanical behavior of bone. J Biomech 27:1159–1168
- 32.
Lewis G (1997) Properties of acrylic bone cement: state of the art review. J Biomed Mater Res 38:155–182
- 33.
Pistoia W, van Rietbergen B, Lochmuller EM et al (2002) Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone 30:842–848
- 34.
Youden WJ (1950) Index for rating diagnostic tests. Cancer 3:32–35. https://doi.org/10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3
- 35.
Core Team R (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
- 36.
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Müller M (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12:77
- 37.
Melton LJ 3rd, Khosla S, Atkinson EJ et al (2000) Cross-sectional versus longitudinal evaluation of bone loss in men and women. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 11:592–599. https://doi.org/10.1007/s001980070080
- 38.
Riggs BL, Melton Iii LJ, Robb RA et al (2004) Population-based study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites. J Bone Miner Res 19:1945–1954. https://doi.org/10.1359/JBMR.040916
- 39.
Riggs BL, Melton LJ, Robb RA et al (2008) A population-based assessment of rates of bone loss at multiple skeletal sites: evidence for substantial trabecular bone loss in young adult women and men. J Bone Miner Res Off J Am Soc Bone Miner Res 23:205–214. https://doi.org/10.1359/jbmr.071020
- 40.
Keaveny TM, Kopperdahl DL, Melton LJ et al (2010) Age-dependence of femoral strength in white women and men. J Bone Miner Res 25:994–1001. https://doi.org/10.1359/jbmr.091033
- 41.
Amin S, Kopperdhal DL, Melton LJ et al (2011) Association of hip strength estimates by finite-element analysis with fractures in women and men. J Bone Miner Res 26:1593–1600. https://doi.org/10.1002/jbmr.347
- 42.
Cumming RG, Nevitt MC, Cummings SR (1997) Epidemiology of hip fractures. Epidemiol Rev 19:244–257. https://doi.org/10.1093/oxfordjournals.epirev.a017956
- 43.
Kanis JA, Johnell O, Oden A, Sernbo I, Redlund-Johnell I, Dawson A, de Laet C, Jonsson B (2000) Long-term risk of osteoporotic fracture in Malmo. Osteoporos Int J Establ Result Coop Eur Found Osteoporos Natl Osteoporos Found USA 11:669–674. https://doi.org/10.1007/s001980070064
- 44.
Melton LJ, Chrischilles EA, Cooper C et al (1992) Perspective. How many women have osteoporosis? J Bone Miner Res 7:1005–1010. https://doi.org/10.1002/jbmr.5650070902
- 45.
Melton LJ 3rd, Atkinson EJ, O’Connor MK et al (1998) Bone density and fracture risk in men. J Bone Miner Res Off J Am Soc Bone Miner Res 13:1915–1923. https://doi.org/10.1359/jbmr.1998.13.12.1915
- 46.
CIHI (2008) In: Canadian Institutes for Health Information (ed) Medical Imaging in Canada, 2007, Ottawa
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Funding
This study was funded in part by the Bob and Nola Rintoul Chair in Bone and Joint Research and a Discovery Grant from the Natural Sciences and Engineering Council (NSERC) of Canada.
Author information
Affiliations
Corresponding author
Ethics declarations
Ethics approval
Data collection and analyses for this study were approved by the University of Calgary Conjoint Health Research Ethics Board (REB 17-1033) with a waiver of informed consent.
Conflicts of interest
None.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
ESM 1
Flow diagram of participants to define the study cohort from the CT scan identification to the final defined cohorts, using specific inclusion criteria of each CT scan. The number of participants removed from the total 1158 participant cohort was identified using each criterion, leading to the final defined cohort. Some participants are excluded due to multiple criteria. (PDF 37 kb)
ESM 2
Fracture numbers specified by sex and anatomical region (DOCX 13 kb)
ESM 3
Outcomes from the ROC curves using combined parameters and the complete fracture cohort (DOCX 14 kb)
ESM 4
Outcomes from the ROC curves using individual parameters and the complete fracture cohort (DOCX 15 kb)
ESM 5
Outcomes from the ROC curves using individual parameters and the low energy fracture sub-cohort (DOCX 15 kb)
Rights and permissions
About this article
Cite this article
Michalski, A., Besler, B., Burt, L. et al. Opportunistic CT screening predicts individuals at risk of major osteoporotic fracture. Osteoporos Int (2021). https://doi.org/10.1007/s00198-021-05863-0
Received:
Accepted:
Published:
Keywords
- Bone fracture
- Osteoporosis
- Patient-specific modeling
- X-ray computed tomography