Literature DB >> 24145305

Finite element analysis and CT-based structural rigidity analysis to assess failure load in bones with simulated lytic defects.

Lorenzo Anez-Bustillos1, Loes C Derikx, Nico Verdonschot, Nathan Calderon, David Zurakowski, Brian D Snyder, Ara Nazarian, Esther Tanck.   

Abstract

There is an urgent need to improve the prediction of fracture risk for cancer patients with bone metastases. Pathological fractures that result from these tumors frequently occur in the femur. It is extremely difficult to determine the fracture risk even for experienced physicians. Although evolving, fracture risk assessment is still based on inaccurate predictors estimated from previous retrospective studies. As a result, many patients are surgically over-treated, whereas other patients may fracture their bones against expectations. We mechanically tested ten pairs of human cadaveric femurs to failure, where one of each pair had an artificial defect simulating typical metastatic lesions. Prior to testing, finite element (FE) models were generated and computed tomography rigidity analysis (CTRA) was performed to obtain axial and bending rigidity measurements. We compared the two techniques on their capacity to assess femoral failure load by using linear regression techniques, Student's t-tests, the Bland-Altman methodology and Kendall rank correlation coefficients. The simulated FE failure loads and CTRA predictions showed good correlation with values obtained from the experimental mechanical testing. Kendall rank correlation coefficients between the FE rankings and the CTRA rankings showed moderate to good correlations. No significant differences in prediction accuracy were found between the two methods. Non-invasive fracture risk assessment techniques currently developed both correlated well with actual failure loads in mechanical testing suggesting that both methods could be further developed into a tool that can be used in clinical practice. The results in this study showed slight differences between the methods, yet validation in prospective patient studies should confirm these preliminary findings.
© 2013.

Entities:  

Keywords:  CT-based structural rigidity analysis; Femur; Finite element analysis; Lytic lesion

Mesh:

Year:  2013        PMID: 24145305      PMCID: PMC3908856          DOI: 10.1016/j.bone.2013.10.009

Source DB:  PubMed          Journal:  Bone        ISSN: 1873-2763            Impact factor:   4.398


  33 in total

1.  Non-invasive assessment of failure torque in rat bones with simulated lytic lesions using computed tomography based structural rigidity analysis.

Authors:  Vahid Entezari; Pamela A Basto; Vartan Vartanians; David Zurakowski; Brian D Snyder; Ara Nazarian
Journal:  J Biomech       Date:  2011-02-03       Impact factor: 2.712

2.  Estimation of mechanical properties of cortical bone by computed tomography.

Authors:  S M Snyder; E Schneider
Journal:  J Orthop Res       Date:  1991-05       Impact factor: 3.494

3.  Predicting fracture through benign skeletal lesions with quantitative computed tomography.

Authors:  Brian D Snyder; Diana A Hauser-Kara; John A Hipp; David Zurakowski; Andrew C Hecht; Mark C Gebhardt
Journal:  J Bone Joint Surg Am       Date:  2006-01       Impact factor: 5.284

4.  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.

Authors:  Enrico Schileo; Fulvia Taddei; Luca Cristofolini; Marco Viceconti
Journal:  J Biomech       Date:  2007-11-19       Impact factor: 2.712

5.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

6.  Predicting proximal femoral strength using structural engineering models.

Authors:  Joyce H Keyak; Tadashi S Kaneko; Jamshid Tehranzadeh; Harry B Skinner
Journal:  Clin Orthop Relat Res       Date:  2005-08       Impact factor: 4.176

Review 7.  The systemic treatment of bone metastases.

Authors:  S J Houston; R D Rubens
Journal:  Clin Orthop Relat Res       Date:  1995-03       Impact factor: 4.176

8.  Pathological fracture prediction in patients with metastatic lesions can be improved with quantitative computed tomography based computer models.

Authors:  Esther Tanck; Jantien B van Aken; Yvette M van der Linden; H W Bart Schreuder; Marcin Binkowski; Henk Huizenga; Nico Verdonschot
Journal:  Bone       Date:  2009-06-17       Impact factor: 4.398

Review 9.  Bone metastasis: pathogenesis and therapeutic implications.

Authors:  Philippe Clezardin; Anna Teti
Journal:  Clin Exp Metastasis       Date:  2007-11-16       Impact factor: 5.150

10.  Metastatic bone disease: a 36-year single centre trend-analysis of patients admitted to a tertiary orthopaedic surgical department.

Authors:  C D Toma; M Dominkus; T Nedelcu; F Abdolvahab; O Assadian; P Krepler; R Kotz
Journal:  J Surg Oncol       Date:  2007-10-01       Impact factor: 3.454

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  17 in total

Review 1.  Computed tomography-based rigidity analysis: a review of the approach in preclinical and clinical studies.

Authors:  Juan C Villa-Camacho; Otatade Iyoha-Bello; Shohreh Behrouzi; Brian D Snyder; Ara Nazarian
Journal:  Bonekey Rep       Date:  2014-11-05

2.  Imaging and Clinical Characteristics Predict Near-Term Disablement From Bone Metastases: Implications for Rehabilitation.

Authors:  Andrea L Cheville; Naveen S Murthy; Jeffrey R Basford; Peter S Rose; Kenny Tran; Thomas P Pittelkow; Michael D Ringler
Journal:  Arch Phys Med Rehabil       Date:  2015-10-03       Impact factor: 3.966

3.  Influence of bone lesion location on femoral bone strength assessed by MRI-based finite-element modeling.

Authors:  Chamith S Rajapakse; Nishtha Gupta; Marissa Evans; Hamza Alizai; Malika Shukurova; Abigail L Hong; Nicholas J Cruickshank; Nirmal Tejwani; Kenneth Egol; Stephen Honig; Gregory Chang
Journal:  Bone       Date:  2019-03-07       Impact factor: 4.398

Review 4.  Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey.

Authors:  Amadeus C S de Alcântara; Israel Assis; Daniel Prada; Konrad Mehle; Stefan Schwan; Lucia Costa-Paiva; Munir S Skaf; Luiz C Wrobel; Paulo Sollero
Journal:  Materials (Basel)       Date:  2019-12-24       Impact factor: 3.623

5.  Noninvasive Failure Load Prediction of Vertebrae with Simulated Lytic Defects and Biomaterial Augmentation.

Authors:  Hugo Giambini; Zhong Fang; Heng Zeng; Jon J Camp; Michael J Yaszemski; Lichun Lu
Journal:  Tissue Eng Part C Methods       Date:  2016-06-29       Impact factor: 3.056

6.  The trabecular effect: A population-based longitudinal study on age and sex differences in bone mineral density and vertebral load bearing capacity.

Authors:  Marianna L Oppenheimer-Velez; Hugo Giambini; Asghar Rezaei; Jon J Camp; Sundeep Khosla; Lichun Lu
Journal:  Clin Biomech (Bristol, Avon)       Date:  2018-03-27       Impact factor: 2.063

Review 7.  The effects of metastatic lesion on the structural determinants of bone: Current clinical and experimental approaches.

Authors:  Stacyann Bailey; David Hackney; Deepak Vashishth; Ron N Alkalay
Journal:  Bone       Date:  2019-11-21       Impact factor: 4.398

8.  CT-based structural analyses of vertebral fractures with polymeric augmentation: A study of cadaveric three-level spine segments.

Authors:  Asghar Rezaei; Hugo Giambini; Alan L Miller Ii; Hao Xu; Haocheng Xu; Yong Li; Michael J Yaszemski; Lichun Lu
Journal:  Comput Biol Med       Date:  2021-04-19       Impact factor: 6.698

Review 9.  Biomechanical Properties of Metastatically Involved Osteolytic Bone.

Authors:  Cari M Whyne; Dallis Ferguson; Allison Clement; Mohammedayaz Rangrez; Michael Hardisty
Journal:  Curr Osteoporos Rep       Date:  2020-10-19       Impact factor: 5.096

10.  Predicting Fracture Risk in Patients with Metastatic Bone Disease of the Femur: A Pictorial Review Using Three Different Techniques.

Authors:  Shannon M Kaupp; Kenneth A Mann; Mark A Miller; Timothy A Damron
Journal:  Adv Orthop       Date:  2021-06-16
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