Bone health assessment through magnetic susceptibility mapping

通过磁化率图评估骨骼健康

• 批准号: 10534656
• 负责人: Brandon Clinton Jones
• 金额: $ 4.77万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2025-02-26
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10534656
• 关键词: 3-Dimensional; Affect; Anatomy; Binding; Biomechanics; Bone Density; Bone Diseases; Bone remodeling; Bone structure; Brain imaging; Cadaver; Calcium; Clinical; Clinical Treatment; Clinical assessments; Complex; Computing Methodologies; Densitometry; Diagnosis; Disease; Dual-Energy X-Ray Absorptiometry; Enrollment; Europe; Evaluation; Fatty acid glycerol esters; Femur; Fracture; Functional disorder; Funding; Future; Gold; Health; Hip Fractures; Hip region structure; Human; Image; Intervention; Intervention Studies; Ionizing radiation; Lumbar Regions; Magic; Magnetic Resonance Imaging; Magnetism; Maps; Marrow; Measurement; Measures; Mechanics; Metals; Methods; Minerals; Modeling; Morbidity - disease rate; Morphology; Network-based; Neural Network Simulation; Obesity; Observational Study; Organ; Osteoclasts; Osteoporosis; Osteoporotic; Participant; Pelvis; Persons; Pharmacologic Substance; Physiologic pulse; Porosity; Postmenopause; Predisposition; Property; Protocols documentation; Radiation; Reproducibility; Research; Research Design; Sampling; Scanning; Site; Specimen; Structure; Techniques; Testing; Time; Tissues; United States; United States National Institutes of Health; Validation; Water; Woman; Work; X-Ray Computed Tomography; Zoledronic Acid; absorption; age related; bone; bone health; bone quality; bone strength; clinical translation; clinically relevant; cohort; cone-beam computed tomography; convolutional neural network; deep learning; efficacy evaluation; experience; experimental study; falls; fracture risk; health assessment; imaging biomarker; improved; in vivo; inhibitor; lumbar vertebra bone structure; magnetic field; mortality; novel; osteoporosis with pathological fracture; pharmacologic; radiological imaging; skeletal disorder; success; tibia; treatment effect; validation studies

Project Summary / Abstract Osteoporosis (OP) is a degenerative skeletal disease which affects an estimated 200 million people worldwide including 30% of all postmenopausal women in the United States and Europe. Hip fractures are the second most common type of OP fracture and cause the greatest mortality and morbidity of all OP fractures, with the one- year mortality rate reaching 20%. Clinical assessment of fracture risk is made via bone densitometric techniques such as dual-energy X-ray absorptiometry (DXA) or quantitative Computed Tomography (QCT), however, these methods are poor predictors of hip fractures with sensitivities of less than 50%. There is thus a need to develop adjunctive, novel, and accurate methods for non-invasively assessing bone quality to better inform clinical treatment of osteoporosis and to enable new research discoveries in bone pathophysiology. The proposed work builds on recent research conducted in the applicant’s lab based on magnetic resonance imaging (MRI) ultrashort echo time (UTE) pulse sequences for assessing bone material composition. I propose to develop and validate a protocol for mapping bone susceptibility in the proximal femur in vivo. First, I will evaluate the efficacy of regularization and deep learning methods for computing the ill-posed dipole inversion through comparisons in cadaveric femora specimens with the gold standard susceptibility method, Calculation of Susceptibility through Multiple Orientation Sampling. Next, I will investigate the extent to which magnetic susceptibility is related to bone health through validation experiments with other imaging biomarkers and with whole bone mechanical testing that mimics a sideways fall. Finally, I will assess the clinical feasibility of bone susceptibility by tracking longitudinal changes following treatment in a small cohort of postmenopausal women. Susceptibility measurement reproducibility and associations with DXA will also be quantified. I anticipate that the results of this study can lead to a clinically feasible approach to measure bone health beyond what is currently possible and could assist in future pharmaceutical or pathophysiological studies of bone diseases.

项目总结/摘要 骨质疏松症（OP）是一种退行性骨骼疾病，影响全球约2亿人 包括美国和欧洲30%的绝经后妇女。髋部骨折是第二大 OP骨折的常见类型，并导致所有OP骨折的最大死亡率和发病率，其中一个- 年死亡率达到20%。骨折风险的临床评估是通过骨密度测定技术进行的 例如双能X射线吸收测定法（DXA）或定量计算机断层扫描（QCT），然而， 方法对髋部骨折的预测效果不佳，敏感性低于50%。因此需要开发 用于非侵入性评估骨质量以更好地为临床提供信息的可靠、新颖且准确的方法 治疗骨质疏松症，并使新的研究发现，在骨病理生理学。 拟议的工作建立在申请人实验室基于磁共振的最新研究基础上 成像（MRI）超短回波时间（UTE）脉冲序列，用于评估骨材料成分。我提议 开发和验证体内股骨近端骨敏感性标测方案。首先我会 评估正则化和深度学习方法计算不适定偶极子反演的有效性 通过比较尸体股骨标本与金标准磁化率方法，计算 通过多方位抽样的易感性。接下来，我将研究磁性 通过其他成像生物标志物的验证实验， 模拟侧摔的全骨力学测试最后，我将评估骨的临床可行性 通过追踪绝经后妇女小队列治疗后的纵向变化来评估易感性。 还将量化敏感性测量再现性和与DXA的关联。 我预计，这项研究的结果可以导致一个临床可行的方法来衡量骨骼健康超越 什么是目前可能的，并可能有助于未来的药物或病理生理学研究的骨 疾病