Osteoporosis is a pervasive disease, affecting over 75 million people in the U.S., Europe, and Japan. Over 1.5 million osteoporosis-related fractures are reported annually in the U.S., with associated costs rising over $16 billion. The current “gold standard” in osteoporosis and fracture risk detection is based on a patient’s clinical profile and a measurement of the patient’s bone mineral density (BMD) via dual energy X-ray absorptiometry (DEXA), either at axial or peripheral sites. While DEXA may provide useful information, it cannot provide enough information for bone fracture risk prediction, especially as only 10% to 44% of most types of fractures can be attributed to low bone density.
Transcutaneous Raman Spectroscopy for bone imagine to predict bone fractures
Researchers at the University of Michigan have developed Transcutaneous Raman Spectroscopy (TRS) for in vivo bone imaging and diagnostics. The system uses specialized fiber-optical probes to capture signals that arise from bone apatitic phosphate, which has a unique Raman signature. Subsequently, multivariate reconstruction techniques are utilized for assessment of state of bone development (calvarial mineralization), mechanical properties (loading and damage), modeled osteogenesis imperfecta (crosslinking and composition changes), and osteoporosis (crosslinking and composition changes in biopsy specimens). While the use of DEXA for BMD measurements only provides limited information for bone fracture risk prediction, TRS is uniquely capable of addressing the current limitations in the diagnosis of osteoporosis, and has the potential to enable early screening and detection for preventative treatments.
Applications and Advantages
- Earlier diagnosis of osteoporosis and recovery of currently inaccessible bone properties
- Measurement of calcification in (malignant)-nl-breast tumors, arterial plaque (no phosphate),-nl-and glucose content (no phosphate)
- Does not use dangerous x-rays
- Higher resolution and more effective-nl-assessment of fracture ris
- Higher accuracy and less false positives than-nl-current technologies