Clinical Assessment of Vertebral Bone Quality Using Direct Biomechanical and Textural Analysis via Digital Tomosynthesis
Abstract
This project relates to the Topic Area “Musculoskeletal Disorders” and specifically to the encouragement area of research on measures to improve diagnosis, prediction, and optimization of health outcomes. This is because the proposed project ultimately aims to improve the accuracy of assessment for spinal bone fragility and fracture risk. The bones of the spine (vertebrae) are the most frequently fractured ones due to osteoporosis. These fractures are economically costly and burden the patients with many downstream problems including back pain. Military personnel are known to be at greater risk for these fractures and complications. An accurate assessment of vertebral fracture risk is essential for appropriate and timely intervention for the prevention of fracture. This research also relates to the Topic Area “Diabetes” because a diabetic cohort will be included in the study. Current standard techniques for fracture risk assessment rely on radiographic bone density scans. Additional information regarding the patient’s demographic status and medical history is also incorporated in tools predicting fracture risk. However, these techniques are not very sensitive in identifying who will have a fracture and who will not. This is not too surprising, considering the fact that the information used in the assessment is a crude indirect measure of bone strength not based on biomechanics. To address this concern, we developed a new method in which two images of a patient’s vertebra are taken in the presence and absence of the patient’s body weight by having them stand and lay down for both images, respectively. The images are obtained using digital tomosynthesis (DTS), a system that is similar to CT (computed tomography). The advantages of DTS over CT are that DTS allows for standing and lying images to be captured, offers high resolution, and exposes patients to less radiation than CT. The two sets of images are compared using an advanced computational method, and deformations in the vertebra caused by standing are measured. From the displacement measurements, vertebral stiffness and overall displacement are calculated as metrics of strength and factor of safety (factor safety is a measure of how strong the bone is relative to the loads it normally experiences). Information on bone microstructure, additional to bone density, is known to increase accuracy in predicting fractures. We can also derive properties related to bone microstructure from DTS images without the biomechanical test. These properties are determined by quantifying the texture in the bone image, and called textural properties. We developed these methods in the laboratory in detail using cadaveric vertebrae and laboratory-standard imaging and strength testing. We also performed pilot human studies to establish feasibility of the methods in the clinic. What remains to be determined is how successful the methods will be in the clinical environment for identifying individuals who are at risk. Therefore, this study will be a clinical validation of the new biomechanical and textural DTS methods. In order to determine the ability of DTS methods to correctly identify at-risk patients, the approach will be to compare patients who have conditions or diseases that are known to increase their risk of fracture to normal patients. Therefore, a group of osteoporotic patients with an existing vertebral deformity, a group with primary hyperparathyroidism (pHPT), and a third group with diabetes will be compared to normal patients. These diseases are considered Service-related and thus represent a greater risk for military families. Importantly, each of these diseases increase the risk of fracture but alter bone in different ways that are not always detectable by bone density scans. For example, osteoporosis primarily results in loss of bone mass, pHPT alters the organization of bone structure and affects the cortical bone (in the case of a vertebra, the d
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 16, 2019
- Source ID
- W81XWH1910374
Entities
People
- Dhanwada Rao
Organizations
- Henry Ford Health
- United States Army