Abstract
Conclusive evidence indicates that osteopenia occurs due to a lack of physical activity in the skeleton such as in microgravity and long-term bed rest. Early diagnosis of these skeletal disorders (i.e., osteoporosis), leads to prompt treatment and could dramatically reduce the risk of complications. Using our newly developed scanning confocal acoustic diagnostic (SCAD) system, we evaluated the ability of quantitative ultrasound to non-invasively predict trabecular bone quantity and quality on 63 sheep bone samples. The structural and strength of bone were confirmed using μCT and mechanical testing in three orthogonal directions. While there are fair correlations between broadband ultrasonic attenuation and μCT determined parameters such as bone volume fraction (BV/TV) (R=-0.68), as well as tissue bulk modulus (R=-0.31), strong correlations exist between ultrasound velocity and bone strength and structural parameters such as bulk modulus (R=0.82), and BV/TV (R=0.93). The correlations between SCAD prediction and bone quantity and quality parameters were improved by using a parameter to combine BUA and UV in a linear regression analysis, yielding R=0.96 (BV/TV) and R=0.82 (bulk modulus). These results suggest that SCAD has the capability to non-invasively assess bone mass and strength.
Original language | English (US) |
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Pages (from-to) | 2174-2175 |
Number of pages | 2 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 3 |
State | Published - 2002 |
Externally published | Yes |
Event | Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States Duration: Oct 23 2002 → Oct 26 2002 |
Keywords
- Attenuation
- Confocal scanning ultrasound
- Mechanical properties
- Micro-CT
- Trabecular bone
- Ultrasound
- Velocity
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics