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Development and Validation of an Image Based, Computed Trabecular Network Model for Estimating Vertebral Fracture Risk in the Aging Population

Development and Validation of an Image Based, Computed Trabecular Network Model for Estimating Vertebral Fracture Risk in the Aging Population
开发和验证基于图像的计算小梁网络模型,用于估计老龄化人群中的椎骨骨折风险
批准号:
10579221
负责人:
Austin Mark Moore
金额:
$5.27万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
未结题
起止时间:
2019-04-01 至 2025-03-31

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英文摘要
Project Summary The aging process often results in decreased bone health in the lumbar spine which can lead to increased risk of vertebral injury. Osteoporosis most affects the density and distribution of trabecular (spongy) bone, but current models overlook the heterogeneous qualities of this region. Finite element (FE) modeling offers a noninvasive method to assess fracture risk using metrics of bone quality measured from quantitative computed tomography scans (qCT). However, due to current limitations of CT scans, it can be difficult to accurately quantify bone degradation clinically. The primary objectives of this proposed study are to develop a novel computed trabecular matrix for lumbar vertebrae trabeculae that will be used to extract additional information from CT scans. The computed trabecular matrix that results from this study could provide additional insight into the relationship between image data and bone strength. Bone morphology, bone volume fraction (BV/TV), and cortical thickness will be measured in qCT scans of cadaveric lumbar spine. In addition, average daily compressive load at each vertebra will be calculated from patient weight and height. These metrics will be input to Optistruct, which will then perform topology optimization to optimally distribute the load throughout the trabecular region. These vertebral models will be compressed until failure. To validate the biomechanical properties of the computed trabecular matrix, the same cadaveric vertebrae will be removed and compressed to failure using a servohydraulic uniaxial loading system. The novel computed trabecular matrix will then be used to model the effects of aging on bone quality degradation. Bone quality metrics of the lumbar spine will be obtained from 30 adults between 50-79 years of age who underwent baseline and follow-up CT scans 12-48 months apart. A computed trabecular matrix will be created for each follow-up and baseline scan to analyze changes in bone strength, vertebral geometry, and cortical thickness. This research will employ an interdisciplinary approach by using radiology, biomechanics, and orthopaedics to study age-related bone decrement. The project will yield a novel computed trabecular matrix to extract additional clinically relevant data from image series, further adding value to CT scans in the fields of geriatrics and orthopaedics.
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Development and Validation of an Image Based, Computed Trabecular Network Model for Estimating Vertebral Fracture Risk in the Aging Population
Development and Validation of an Image Based, Computed Trabecular Network Model for Estimating Vertebral Fracture Risk in the Aging Population
Development and Validation of an Image Based, Computed Trabecular Network Model for Estimating Vertebral Fracture Risk in the Aging Population
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