Literature DB >> 30243888

Variability in strain distribution in the mice tibia loading model: A preliminary study using digital volume correlation.

M Giorgi1, E Dall'Ara2.   

Abstract

It is well known that bone has an enormous adaptive capacity to mechanical loadings, and to this extent, several in vivo studies on mouse tibia use established cyclic compressive loading protocols to investigate the effects of mechanical stimuli. In these experiments, the applied axial load is well controlled but the positioning of the hind-limb between the loading endcaps may dramatically affect the strain distribution induced on the tibia. In this study, the full field strain distribution induced by a typical in vivo setup on mouse tibiae was investigated through a combination of in situ compressive testing, µCT scanning and a global digital volume correlation (DVC) approach. The precision of the DVC method and the effect of repositioning on the strain distributions were evaluated. Acceptable uncertainties of the DVC approach for the analysis of loaded tibiae (411 ± 58µɛ) were found for nodal spacing of approximately 50 voxels (520 µm). When pairs of in situ preloaded and loaded images were registered, low variability of the strain distributions within the tibia were seen (range of mean differences in principal strains: 585-1800µɛ). On contrary, larger differences were seen after repositioning (range of mean differences in principal strains: 2500-5500µɛ). To conclude, these preliminary results on thee specimens showed that the DVC approach applied to the mouse tibia can be precise enough to evaluate local strain distributions under loads, and that repositioning of the hind-limb within the testing machine can induce large differences in the strain distributions that should be accounted for when modelling this system.
Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Digital volume correlation (DVC); Ex vivo µCT; In situ µCT; In vivo µCT; Mouse tibia; Strain variability; microCT

Mesh:

Year:  2018        PMID: 30243888     DOI: 10.1016/j.medengphy.2018.09.001

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  7 in total

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Authors:  Edmund Pickering; Matthew J Silva; Peter Delisser; Michael D Brodt; YuanTong Gu; Peter Pivonka
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Review 4.  Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments.

Authors:  Enrico Dall'Ara; Gianluca Tozzi
Journal:  Front Bioeng Biotechnol       Date:  2022-10-04

5.  The Role of the Loading Condition in Predictions of Bone Adaptation in a Mouse Tibial Loading Model.

Authors:  Vee San Cheong; Visakan Kadirkamanathan; Enrico Dall'Ara
Journal:  Front Bioeng Biotechnol       Date:  2021-06-11

6.  A novel algorithm to predict bone changes in the mouse tibia properties under physiological conditions.

Authors:  Vee San Cheong; Ana Campos Marin; Damien Lacroix; Enrico Dall'Ara
Journal:  Biomech Model Mechanobiol       Date:  2019-11-30

7.  Prenatal growth map of the mouse knee joint by means of deformable registration technique.

Authors:  Mario Giorgi; Vivien Sotiriou; Niccolo' Fanchini; Simone Conigliaro; Cristina Bignardi; Niamh C Nowlan; Enrico Dall'Ara
Journal:  PLoS One       Date:  2019-01-03       Impact factor: 3.240

  7 in total

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