We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D image registration to account for misalignment between images. This reduced variability in longitudinal FE estimates and improved our ability to measure in vivo changes in HR-pQCT studies of bone strength.
We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D rigid-body registration (3DR) to maximize reproducibility by accounting for misalignment between images.
In our proposed approach, we used the full common bone volume defined by 3DR to estimate standard FE parameters. Using standard HR-pQCT imaging protocols, we validated the 3DR approach with ex vivo samples of the distal radius (n = 10, four repeat scans) by assessing whether 3DR can reduce measurement variability from repositioning error. We used in vivo data (n = 40, five longitudinal scans) to assess the sensitivity of 3DR to detect changes in bone strength at the distal radius by the standard deviation of the rate of change (σ), where the ideal value of σ is minimized to define true change. FE estimates by 3DR were compared to estimates by no registration (NR) and slice-matching (SM).
Group-wise comparisons of ex vivo variation (CVRMS, %) found that FE measurement precision was improved by SM (CVRMS < 0.80%) and 3DR (CVRMS < 0.62%) compared to NR (CVRMS~2%), and 3DR was advantageous as repositioning error increased. Longitudinal in vivo reproducibility was minimized by 3DR for failure load estimates (σ = 0.008 kN/month).
Although 3D registration cannot negate motion artifacts, it plays an important role in detecting and reducing variability in FE estimates for longitudinal HR-pQCT data and is well suited for estimating effects of interventions in in vivo longitudinal studies of bone strength.
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Cheung AM, Adachi JD, Hanley DA, Kendler DL, Davison KS, Josse R, Brown JP, Ste-Marie LG, Kremer R, Erlandson MC, Dian L, Burghardt AJ, Boyd SK (2013) High-resolution peripheral quantitative computed tomography for the assessment of bone strength and structure: a review by the Canadian Bone Strength Working Group. Curr Osteoporos Rep 11(2):136–146. https://doi.org/10.1007/s11914-013-0140-9
Boutroy S, Bouxsein ML, Munoz F, Delmas PD (2005) In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography. J Clin Endocrinol Metab 90(12):6508–6515. https://doi.org/10.1210/jc.2005-1258
Whittier DE, Boyd SK, Burghardt AJ, Paccou J, Ghasem-Zadeh A, Chapurlat R, Engelke K, Bouxsein ML (2020) Guidelines for the assessment of bone density and microarchitecture in vivo using high-resolution peripheral quantitative computed tomography. Osteoporos Int 31(9):1607–1627. https://doi.org/10.1007/s00198-020-05438-5
Agarwal S, Rosete F, Zhang C, McMahon DJ, Guo XE, Shane E, Nishiyama KK (2016) In vivo assessment of bone structure and estimated bone strength by first- and second-generation HR-pQCT. Osteoporos Int 27(10):2955–2966. https://doi.org/10.1007/s00198-016-3621-8
Manske SL, Zhu Y, Sandino C, Boyd SK (2015) Human trabecular bone microarchitecture can be assessed independently of density with second generation HR-pQCT. Bone 79:213–221. https://doi.org/10.1016/j.bone.2015.06.006
Burghardt AJ, Kazakia GJ, Sode M, de Papp AE, Link TM, Majumdar S (2010) A longitudinal HR-pQCT study of alendronate treatment in postmenopausal women with low bone density: relations among density, cortical and trabecular microarchitecture, biomechanics, and bone turnover. J Bone Miner Res 25(12):2282–2295. https://doi.org/10.1002/jbmr.157
Burt LA, Billington EO, Rose MS, Raymond DA, Hanley DA, Boyd SK (2019) Effect of high-dose vitamin D supplementation on volumetric bone density and bone strength: a randomized clinical trial. JAMA 322(8):736–745. https://doi.org/10.1001/jama.2019.11889
Tsai JN, Nishiyama KK, Lin D, Yuan A, Lee H, Bouxsein ML, Leder BZ (2017) Effects of denosumab and teriparatide transitions on bone microarchitecture and estimated strength: the DATA-Switch HR-pQCT study. J Bone Miner Res 32(10):2001–2009. https://doi.org/10.1002/jbmr.3198
Gabel L, Macdonald HM, Nettlefold L, McKay HA (2017) Physical activity, sedentary time, and bone strength from childhood to early adulthood: a mixed longitudinal HR-pQCT study. J Bone Miner Res 32(7):1525–1536. https://doi.org/10.1002/jbmr.3115
Vico L, van Rietbergen B, Vilayphiou N, Linossier M-T, Locrelle H, Normand M, Zouch M, Gerbaix M, Bonnet N, Novikov V, Thomas T, Vassilieva G (2017) Cortical and trabecular bone microstructure did not recover at weight-bearing skeletal sites and progressively deteriorated at non-weight-bearing sites during the year following international space station missions. J Bone Miner Res 32(10):2010–2021. https://doi.org/10.1002/jbmr.3188
Kemp TD, de Bakker CMJ, Gabel L, Hanley DA, Billington EO, Burt LA, Boyd SK (2020) Longitudinal bone microarchitectural changes are best detected using image registration. Osteoporos Int 31(10):1995–2005. https://doi.org/10.1007/s00198-020-05449-2
Ellouz R, Chapurlat R, van Rietbergen B, Christen P, Pialat JB, Boutroy S (2014) Challenges in longitudinal measurements with HR-pQCT: evaluation of a 3D registration method to improve bone microarchitecture and strength measurement reproducibility. Bone 63:147–157. https://doi.org/10.1016/j.bone.2014.03.001
van Rietbergen B, Ito K (2015) A survey of micro-finite element analysis for clinical assessment of bone strength: the first decade. J Biomech 48(5):832–841. https://doi.org/10.1016/j.jbiomech.2014.12.024
Burt LA, Gaudet S, Kan M, Rose MS, Billington EO, Boyd SK, Hanley DA (2018) Methods and procedures for: a randomized double-blind study investigating dose-dependent longitudinal effects of vitamin D supplementation on bone health. Contemp Clin Trials 67:68–73. https://doi.org/10.1016/j.cct.2018.02.009
Sode M, Burghardt AJ, Pialat JB, Link TM, Majumdar S (2011) Quantitative characterization of subject motion in HR-pQCT images of the distal radius and tibia. Bone 48(6):1291–1297. https://doi.org/10.1016/j.bone.2011.03.755
Buie HR, Campbell GM, Klinck RJ, MacNeil JA, Boyd SK (2007) Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis. Bone 41(4):505–515. https://doi.org/10.1016/j.bone.2007.07.007
Burghardt AJ, Buie HR, Laib A, Majumdar S, Boyd SK (2010) Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone 47(3):519–528. https://doi.org/10.1016/j.bone.2010.05.034
Whittier DE, Manske SL, Kiel DP, Bouxsein M, Boyd SK (2018) Harmonizing finite element modelling for non-invasive strength estimation by high-resolution peripheral quantitative computed tomography. J Biomech 80:63–71. https://doi.org/10.1016/j.jbiomech.2018.08.030
van Rietbergen B, Weinans H, Huiskes R, Odgaard A (1995) A new method to determine trabecular bone elastic properties and loading using micromechanical finite-element models. J Biomech 28(1):69–81. https://doi.org/10.1016/0021-9290(95)80008-5
Pistoia W, van Rietbergen B, Lochmuller EM, Lill CA, Eckstein F, Ruegsegger P (2002) Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone 30(6):842–848. https://doi.org/10.1016/s8756-3282(02)00736-6
Glüer CC, Blake G, Lu Y, Blunt BA, Jergas M, Genant HK (1995) Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques. Osteoporos Int 5(4):262–270. https://doi.org/10.1007/bf01774016
Glüer CC (1999) Monitoring skeletal changes by radiological techniques. J Bone Miner Res 14(11):1952–1962. https://doi.org/10.1359/jbmr.1922.214.171.1242
Shepherd JA, Lu Y (2007) A generalized least significant change for individuals measured on different DXA systems. J Clin Densitom 10(3):249–258. https://doi.org/10.1016/j.jocd.2007.05.002
MacNeil JA, Boyd SK (2008) Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality. Med Eng Phys 30(6):792–799. https://doi.org/10.1016/j.medengphy.2007.11.003
Paggiosi MA, Eastell R, Walsh JS (2014) Precision of high-resolution peripheral quantitative computed tomography measurement variables: influence of gender, examination site, and age. Calcif Tissue Int 94(2):191–201. https://doi.org/10.1007/s00223-013-9798-3
Pauchard Y, Ayres FJ, Boyd SK (2011) Automated quantification of three-dimensional subject motion to monitor image quality in high-resolution peripheral quantitative computed tomography. Phys Med Biol 56(20):6523–6543. https://doi.org/10.1088/0031-9155/56/20/001
Bonaretti S, Vilayphiou N, Chan CM, Yu A, Nishiyama K, Liu D, Boutroy S, Ghasem-Zadeh A, Boyd SK, Chapurlat R, McKay H, Shane E, Bouxsein ML, Black DM, Majumdar S, Orwoll ES, Lang TF, Khosla S, Burghardt AJ (2017) Operator variability in scan positioning is a major component of HR-pQCT precision error and is reduced by standardized training. Osteoporos Int 28(1):245–257. https://doi.org/10.1007/s00198-016-3705-5
Boyd SK (2008) Site-specific variation of bone micro-architecture in the distal radius and tibia. J Clin Densitom 11(3):424–430. https://doi.org/10.1016/j.jocd.2007.12.013
The authors thank J.M. Allan, J.A. Allan, S. Gaudet, M. Kan, and B. Love for participant recruitment and A. Cooke, S. Kwong, and D. Raymond for scan acquisition and analysis. The authors acknowledge the Natural Sciences and Engineering Research Council (NSERC) of Canada (Discovery Grant: RGPIN-2019-04135) and Pure North S’Energy Foundation by an investigator-initiated grant for funding this study. The authors also thank the study participants for generously donating their time to support our research.
This study was funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada (Discovery Grant: RGPIN-2019-04135) and Pure North S’Energy Foundation in response to an investigator-initiated research proposal.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Conflict of interest
RMP, TDK, LAB and DAH have nothing to declare. EOB has previously received honoraria from Amgen and Eli Lilly, and a research grant from Amgen. SKB has received honorariums from Amgen and Servier.
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Plett, R.M., Kemp, T.D., Burt, L.A. et al. Using 3D image registration to maximize the reproducibility of longitudinal bone strength assessment by HR-pQCT and finite element analysis. Osteoporos Int (2021). https://doi.org/10.1007/s00198-021-05896-5
- 3D registration
- Bone strength
- Finite element analysis
- Longitudinal analysis