Literature DB >> 28994795

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation.

Timothy Rossman1, Susheil Uthamaraj1, Asghar Rezaei2, Sean McEligot1, Hugo Giambini3, Iwona Jasiuk4, Michael J Yaszemski3, Lichun Lu3, Dan Dragomir-Daescu5.   

Abstract

This protocol describes the method using digital image correlation to estimate cortical strain from high speed video images of the cadaveric femoral surface obtained from mechanical testing. This optical method requires a texture of many contrasting fiduciary marks on a solid white background for accurate tracking of surface deformation as loading is applied to the specimen. Immediately prior to testing, the surface of interest in the camera view is painted with a water-based white primer and allowed to dry for several minutes. Then, a black paint is speckled carefully over the white background with special consideration for the even size and shape of the droplets. Illumination is carefully designed and set such that there is optimal contrast of these marks while minimizing reflections through the use of filters. Images were obtained through high speed video capture at up to 12,000 frames/s. The key images prior to and including the fracture event are extracted and deformations are estimated between successive frames in carefully sized interrogation windows over a specified region of interest. These deformations are then used to compute surface strain temporally during the fracture test. The strain data is very useful for identifying fracture initiation within the femur, and for eventual validation of proximal femur fracture strength models derived from Quantitative Computed Tomography-based Finite Element Analysis (QCT/FEA).

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Year:  2017        PMID: 28994795      PMCID: PMC5752248          DOI: 10.3791/54942

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  8 in total

1.  Accuracy of finite element predictions in sideways load configurations for the proximal human femur.

Authors:  L Grassi; E Schileo; F Taddei; L Zani; M Juszczyk; L Cristofolini; M Viceconti
Journal:  J Biomech       Date:  2011-11-12       Impact factor: 2.712

2.  Subject-specific finite element models of long bones: An in vitro evaluation of the overall accuracy.

Authors:  Fulvia Taddei; Luca Cristofolini; Saulo Martelli; H S Gill; Marco Viceconti
Journal:  J Biomech       Date:  2005-10-06       Impact factor: 2.712

3.  Robust QCT/FEA models of proximal femur stiffness and fracture load during a sideways fall on the hip.

Authors:  Dan Dragomir-Daescu; Jorn Op Den Buijs; Sean McEligot; Yifei Dai; Rachel C Entwistle; Christina Salas; L Joseph Melton; Kevin E Bennet; Sundeep Khosla; Shreyasee Amin
Journal:  Ann Biomed Eng       Date:  2010-10-29       Impact factor: 3.934

4.  Prediction of femoral fracture load using automated finite element modeling.

Authors:  J H Keyak; S A Rossi; K A Jones; H B Skinner
Journal:  J Biomech       Date:  1998-02       Impact factor: 2.712

5.  Validated finite element models of the proximal femur using two-dimensional projected geometry and bone density.

Authors:  Jorn Op Den Buijs; Dan Dragomir-Daescu
Journal:  Comput Methods Programs Biomed       Date:  2010-12-14       Impact factor: 5.428

6.  Femoral strength is better predicted by finite element models than QCT and DXA.

Authors:  D D Cody; G J Gross; F J Hou; H J Spencer; S A Goldstein; D P Fyhrie
Journal:  J Biomech       Date:  1999-10       Impact factor: 2.712

7.  Fracture prediction for the proximal femur using finite element models: Part I--Linear analysis.

Authors:  J C Lotz; E J Cheal; W C Hayes
Journal:  J Biomech Eng       Date:  1991-11       Impact factor: 2.097

8.  How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

Authors:  Lorenzo Grassi; Sami P Väänänen; Matti Ristinmaa; Jukka S Jurvelin; Hanna Isaksson
Journal:  J Biomech       Date:  2016-02-18       Impact factor: 2.712

  8 in total

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