Loughborough University
Browse
radley.pdf (796.94 kB)

Characterization, quantification, and replication of human sinus bone for surgery simulation phantoms

Download (796.94 kB)
journal contribution
posted on 2010-01-26, 09:55 authored by G.J. Radley, A. Sama, Jason Watson, Russell Harris
The requirement for artificial but realistic, tactile, anatomical models for surgical practice in medical simulation is increasingly evident and shows potential for greater efficiency and availability, and lower costs. Anatomically correct, detailed models with the physical surgical characteristics of real tissue, combined with the ability to reproduce one-off cases, would provide an invaluable tool in the development of surgery. This research work investigates the capture of geometrical and physical data from the human sinus to subsequently direct the production and optimization of such simulation phantoms. Micro-computed tomography analysis of the entire sinus was performed to characterize the sinus complex geometry. Following an extensive review, specialized mechanical testing apparatus and methods relevant to the surgical methods employed were designed and produced. This provided comparative analysis methods for both biological and artificial phantom materials and allowed the optimization of phantom materials with respect to the derived target values.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

RADLEY, G.J....et al., 2009. Characterization, quantification, and replication of human sinus bone for surgery simulation phantoms. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 223(7), pp. 875-887

Publisher

© IMechE / Professional Engineering Publishing

Version

  • VoR (Version of Record)

Publication date

2009

Notes

This is an article from the journal, Proceedings of the IMechE, Part H: Journal of Engineering in Medicine [© Professional Engineering Publishing ]. It is also available at: http://dx.doi.org/10.1243/09544119JEIM577

ISSN

0954-4119;2041-3033

Language

  • en