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dc.contributor.advisorMary L. Bouxsein.en_US
dc.contributor.authorBruno, Alexander Gen_US
dc.contributor.otherHarvard--MIT Program in Health Sciences and Technology.en_US
dc.date.accessioned2015-09-17T19:07:49Z
dc.date.available2015-09-17T19:07:49Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/98727
dc.descriptionThesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractVertebral fractures are the most common complication of osteoporosis and are associated with significant pain, height loss, disfigurement, respiratory impairment, depression, and decreased life span. Despite the high personal and societal costs of vertebral fractures, little is known regarding their biomechanical etiology. In particular, whereas much is known about the determinants of vertebral strength, little is known about the in vivo loading of the spine that may contribute to vertebral fracture. Prior efforts to understand the possible contribution of spine mechanics to vertebral fractures have been limited by the inability to accurately assess in vivo spinal loading, especially in the thoracic region. Thus, the overall goal of this work was to improve the understanding of vertebral fractures through detailed analysis of spinal loading. We first developed and validated a novel musculoskeletal model capable of predicting forces in the thoracolumbar spine during daily activities. Model-derived predictions of vertebral compressive loading and trunk muscle activity were highly correlated with previously collected in vivo measurements of pressure, vertebral compression from telemeterized implants, and trunk muscle myoelectric activity from electromyography. To gain insights into how individual variation in trunk anatomy influences vertebral loading, we developed a robust set of methods for rapid, automated generation of subject-specific musculoskeletal models of the thoracolumbar spine using computed tomography based measurements of spine curvature and trunk muscle morphology. Using these subject-specific models, we found that normal variations in spine curvature and muscle morphology in the adult population have a large effect on vertebral loading predictions. Specifically, we found that increasing thoracic kyphosis and reducing lumbar lordosis, changes that commonly occur with age, were both associated with higher spinal loads. Lastly, we used our musculoskeletal model to describe how vertebral loading and the factor-of-risk (load-to-strength ratio) vary along the spine for a large number of activities. For a majority of activities, the highest loads and factor-of- risk were in the thoracolumbar region, which is the spine region with the highest incidence of vertebral fracture. Further, we identified a unique biomechanical mechanism responsible for the high loads in this region.en_US
dc.description.statementofresponsibilityby Alexander G. Bruno.en_US
dc.format.extent188 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectHarvard--MIT Program in Health Sciences and Technology.en_US
dc.titleInvestigation of spine loading to understand vertebral fracturesen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.identifier.oclc920873263en_US


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