| Title |
Non-invasive Predictors of Human Cortical Bone Mechanical Properties: T2-Discriminated 1H NMR Compared with High Resolution X-ray
|
|---|---|
| Published in |
PLOS ONE, January 2011
|
| DOI | 10.1371/journal.pone.0016359 |
| Pubmed ID | |
| Authors |
R. Adam Horch, Daniel F. Gochberg, Jeffry S. Nyman, Mark D. Does |
| Abstract |
Recent advancements in magnetic resonance imaging (MRI) have enabled clinical imaging of human cortical bone, providing a potentially powerful new means for assessing bone health with molecular-scale sensitivities unavailable to conventional X-ray-based diagnostics. To this end, (1)H nuclear magnetic resonance (NMR) and high-resolution X-ray signals from human cortical bone samples were correlated with mechanical properties of bone. Results showed that (1)H NMR signals were better predictors of yield stress, peak stress, and pre-yield toughness than were the X-ray derived signals. These (1)H NMR signals can, in principle, be extracted from clinical MRI, thus offering the potential for improved clinical assessment of fracture risk. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| United Kingdom | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 60 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 27% |
| Researcher | 15 | 23% |
| Student > Master | 6 | 9% |
| Professor | 5 | 8% |
| Professor > Associate Professor | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 10 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 21 | 33% |
| Medicine and Dentistry | 8 | 13% |
| Physics and Astronomy | 8 | 13% |
| Agricultural and Biological Sciences | 2 | 3% |
| Chemistry | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 17 | 27% |