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Proceedings Paper

Visualizing bone porosities using a tabletop scanning electron microscope
Author(s): D. Krishnamoorthy; J. DaPonte; C. C. Broadbridge; D. Daniel; L. Alter
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Paper Abstract

Pores are naturally occurring entities in bone. Changes in pore size and number are often associated with diseases such as Osteoporosis and even microgravity during spaceflight. Studying bone perforations may yield great insight into bone's material properties, including bone density and may contribute to identifying therapies to halt or potentially reverse bone loss. Current technologies used in this field include nuclear magnetic resonance, micro-computed tomography and the field emission scanning electron microscope (FE-SEM) 2, 5. However, limitations in each method limit further advancement. The objective of this study was to assess the effectiveness of using a new generation of analytical instruments, the TM-1000 tabletop, SEM with back-scatter electron (BSE) detector, to analyze cortical bone porosities. Hind limb unloaded and age-based controlled mouse femurs were extracted and tested in vitro for changes in pores on the periosteal surface. An important advantage of using the tabletop is the simplified sample preparation that excludes extra coatings, dehydration and fixation steps that are otherwise required for conventional SEM. For quantitative data, pores were treated as particles in order to use an analyze particles feature in the NIH ImageJ software. Several image-processing techniques for background smoothing, thresholding and filtering were employed to produce a binary image suitable for particle analysis. It was hypothesized that the unloaded bones would show an increase in pore area, as the lack of mechanical loading would affect bone-remodeling processes taking place in and around pores. Preliminary results suggest only a slight different in frequency but not in size of pores between unloaded and control femurs.

Paper Details

Date Published: 15 April 2010
PDF: 8 pages
Proc. SPIE 7701, Visual Information Processing XIX, 77010U (15 April 2010); doi: 10.1117/12.850246
Show Author Affiliations
D. Krishnamoorthy, Carnegie Mellon Univ. (United States)
J. DaPonte, Southern Connecticut State Univ. (United States)
C. C. Broadbridge, Southern Connecticut State Univ. (United States)
D. Daniel, Southern Connecticut State Univ. (United States)
L. Alter, Wilber Cross High School (United States)


Published in SPIE Proceedings Vol. 7701:
Visual Information Processing XIX
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)

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