Regenerative Rehabilitation of Complex Musculoskeletal Injuries

复杂肌肉骨骼损伤的再生康复

• 批准号: 10570304
• 负责人: ROBERT E GULDBERG
• 金额: $ 62.01万
• 依托单位: UNIVERSITY OF OREGON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10570304
• 关键词: Acceleration; Accidents; Area; Biocompatible Materials; Biological; Biological Markers; Biological Response Modifier Therapy; Biomechanics; Blood Vessels; Bone Regeneration; Cohort Studies; Complex; Complication; Coupled; Coupling; Data; Defect; Dose; Elements; Environment; Experimental Designs; Feedback; Female; Femur; Functional Regeneration; Funding; Gait; Goals; Histology; Individual; Injury; Interdisciplinary Study; Knowledge; Limb structure; Lower Extremity; Maps; Measurement; Measures; Mechanics; Methodology; Modeling; Multivariate Analysis; Muscle; Musculoskeletal; Natural regeneration; Outcome; Pain; Patients; Physical Rehabilitation; Physicians; Physiological Processes; Pre-Clinical Model; Procedures; Prospective Studies; Protocols documentation; Rattus; Recovery of Function; Regimen; Rehabilitation therapy; Second Look Surgery; Severities; Testing; Time; Tissues; Translating; Trauma patient; Treatment Protocols; Treatment outcome; Variant; Weight-Bearing state; Work; X-Ray Computed Tomography; biomechanical test; bone; clinical practice; cohort; combat; design; disability; evidence base; functional improvement; functional outcomes; functional restoration; gait examination; healing; implanted sensor; improved; instrument; limb injury; male; mechanical signal; mechanical stimulus; microCT; muscle regeneration; musculoskeletal injury; new technology; non-invasive monitor; novel; predictive marker; predictive modeling; prospective; quadriceps muscle; radiological imaging; regeneration model; regenerative; regenerative rehabilitation; regenerative treatment; repaired; response; response biomarker; restoration; sample fixation; sensor; sex; skeletal; skills; tissue regeneration; treatment strategy; wireless; wireless implant

SUMMARY Complex musculoskeletal trauma is common both in combat and high energy civilian accidents and often leads to prolonged disability or skeletal nonunion. Regenerative rehabilitation is an emerging field with the potential to improve functional outcomes for lower limb musculoskeletal trauma patients. Our overall objectives are to (i) investigate rehabilitative loading as a regenerative rehabilitation treatment strategy for severe complex musculoskeletal trauma and (ii) understand the relationship between rehabilitative loading, local regenerative niche mechanics, and the biological response. We will meet these objectives through the following specific aims. Specific Aim 1: Determine the effects of rehabilitative loading, injury severity and sex on regenerative niche mechanical signals and functional regeneration. In a rat model of a femoral bone defect, we will employ a factorial experimental design to determine effective rehabilitative loading protocols in critically sized injuries, and determine the effects of rehabilitation on local and systemic biological responses and functional regeneration as a function of sex and injury size. Specific Aim 2: Integrate sensor-enabled real-time feedback into rehabilitation protocols and test the ability to accelerate bone and muscle functional recovery following severe extremity injury. This aim will use wireless implantable strain sensors to provide noninvasive monitoring of mechanics in the regenerative niche throughout the progression of healing under rehabilitative loading. Sensor mechanical data will be used to identify strain ranges that serve as early indicators of healing status and are used as a criterion for dynamically adjusting the rehabilitation regimen on a subject-specific basis to accelerate functional regeneration of musculoskeletal tissue. Specific Aim 3: Build predictive multivariate models based on co-dependent relationships among local regenerative niche mechanical parameters, systemic biomarkers, and functional regeneration. Finite element modeling will be used to generate simulated strain maps showing local variations in regenerative niche mechanical signals using implantable sensor measurements as time-varying boundary conditions. Linear multivariate analyses will be used to map spatial and temporal relationships between the biological responses and local regenerative niche mechanics under rehabilitative loading regimens. Integrating early mechanical data and systemic biomarker data from the previous aims, nonlinear symbolic regression will be used to develop predictive models of bone and muscle functional outcomes for subjects of both sexes. These models will be tested in a prospective study using an additional cohort of both sexes to validate whether models developed in one sex can be predictive of healing outcomes in both the same and the opposite sexes.

摘要 复杂的肌肉骨骼创伤在战斗和高能平民事故中都很常见，并经常导致 导致长期残疾或骨骼骨不连。再生性康复是一个新兴的领域，具有 改善下肢肌肉骨骼创伤患者的功能结果。我们的总体目标是：(一) 探讨康复负荷作为重症综合体再生性康复治疗策略 了解肌肉骨骼创伤与(二)康复负荷、局部再生的关系 生态位机制和生物反应。我们将通过以下具体目标实现这些目标。 具体目标1：确定康复负荷、损伤严重程度和性别对再生的影响 利基机械信号和功能再生。在股骨骨缺损的大鼠模型中，我们将采用 用于确定危重损伤有效康复负荷方案的析因试验设计， 并确定康复对局部和系统生物反应和功能再生的影响 作为性别和损伤大小的函数。具体目标2：将传感器启用的实时反馈整合到 康复方案和测试加速骨和肌肉功能恢复的能力 四肢严重受伤。这一目标将使用无线植入式应变传感器来提供非侵入性监测 在康复负荷下的整个愈合过程中再生利基中的力学。传感器 机械数据将被用来识别作为愈合状态的早期指标的应变范围，并且 作为根据特定主题动态调整康复方案的标准，以加快 肌肉骨骼组织的功能性再生。具体目标3：建立预测性多变量模型 关于局部再生生态位力学参数之间的相互依赖关系 生物标志物和功能再生。将使用有限元建模来生成模拟应变 使用植入式传感器测量显示再生生态位机械信号的局部变化的地图 作为时变的边界条件。将使用线性多变量分析来绘制空间和时间图 康复训练中生物反应与局部再生生态位机制的关系 装药方案。整合来自先前目标的早期机械数据和系统生物标志物数据， 将使用非线性符号回归来开发骨和肌肉功能结果的预测模型 对男女受试者都适用。这些模型将在一项前瞻性研究中进行测试，该研究使用另外一组这两种模型 性别以验证在一种性别中开发的模型是否可以预测两种性别的康复结果 和相反的性别。