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Computer-Aided Tissue Engineering of a Human Vertebral Body

Overview of attention for article published in Annals of Biomedical Engineering, October 2005
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Title
Computer-Aided Tissue Engineering of a Human Vertebral Body
Published in
Annals of Biomedical Engineering, October 2005
DOI 10.1007/s10439-005-6744-1
Pubmed ID
Authors

M. A. Wettergreen, B. S. Bucklen, W. Sun, M. A. K. Liebschner

Abstract

Tissue engineering is developing into a less speculative science involving the careful interplay of numerous design parameters and multidisciplinary professionals. Problem solving abilities and state of the art research tools are required to develop solutions for a wide variety of clinical issues. One area of particular interest is orthopedic biomechanics, a field that is responsible for the treatment of over 700,000 vertebral fractures in the United States alone last year. Engineers are currently lacking the technology and knowledge required to govern the subsistence of cells in vivo, let alone the knowledge to create a functional tissue replacement for a whole organ. Despite this, advances in computer-aided tissue engineering are continually growing. Using a combinatory approach to scaffold design, patient-specific implants may be constructed. Computer-aided design, optimization of geometry using voxel finite element models or other optimization routines, creation of a library of architectures with specific material properties, rapid prototyping, and determination of a defect site using imaging modalities highlight the current availability of design resources. This study proposes a novel methodology from start to finish which could, in the future, be used to design a tissue-engineered construct for the replacement of an entire vertebral body.

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The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Netherlands 1 1%
Colombia 1 1%
Germany 1 1%
Unknown 80 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 20%
Student > Master 12 14%
Researcher 11 13%
Professor > Associate Professor 6 7%
Student > Doctoral Student 5 6%
Other 18 21%
Unknown 16 19%
Readers by discipline Count As %
Engineering 42 49%
Medicine and Dentistry 6 7%
Materials Science 6 7%
Biochemistry, Genetics and Molecular Biology 3 4%
Agricultural and Biological Sciences 2 2%
Other 7 8%
Unknown 19 22%