Multi-faceted Approach to Modeling ACL Injury Mechanisms

ACL 损伤机制建模的多方面方法

基本信息

  • 批准号:
    8911250
  • 负责人:
  • 金额:
    $ 62.78万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-05-15 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Anterior cruciate ligament (ACL) injury is a major medical and financial burden. Despite identification of modifiable risk factors and effective preventive measures, global ACL injury incidence remains largely unaffected. Under the parent grant we identified plausible valgus collapse mechanisms for ACL injury without concomitant medial collateral ligament (MCL) injury. A novel cadaveric testing setup we developed under the funded grant has demonstrated a nearly 90% rate of ACL tear. Our findings show that combined knee abduction moment (KAM), anterior tibial shear force (ATS) and internal tibial rotation moment (ITR) generates significantly greater strain in the ACL relative to the MCL, and reproduces kinematics similar to those observed during ACL injury. While these types of loading, in isolation, increase ACL strain and potentially risk of injury, their combined effects o ACL biomechanics are not well understood. In this competing renewal application we will develop a highly impactful and unique ACL injury risk assessment protocol that accounts for multiplanar biomechanics. The protocol will be developed through a novel, integrative in vivo, in vitro and in silico (in sim) approach. The Specific Aims are: I) To develop and validate a multiplanar ACL injury risk assessment algorithm that predicts ACL injury risk based on dynamic ACL strain, and II) To integrate in vivo, in vitro and in silico approaches to establish a 'continuum of risk' that accounts for the relative contributions of KAM, ITR, and ATS to ACL rupture. The critical distinction between the two Aims is the biomechanical context: Aim I will determine how the ACL is strained during non-injurious screening tasks that can be performed in a laboratory or clinical setting. Aim II will establish a direct link between high strain movemet patterns and the ACL injury mechanism(s). We hypothesize that: I) Peak input values of KAM, ITR, and ATS from in vivo data will accurately predict peak ACL strain when landing biomechanics are reproduced in vitro and in silico, and II) Incremental increases in KAM, ITR and ATS, scaled from 'high-risk' in vivo measures will lead to ACL rupture in vitro and in silico. In Specific Aim I, multi-planar kinematics and kinetics will be directly used as inputs to our validated, sex-specific, viscoelastic FE knee models and in vitro test protocols to test our hypotheses. We will also aim to identify and validate simple, clinically-based predictors for KAM, ITR, and ATS to maximize the clinical applicability of the protocol. In Aim II, we will directly examine the roles of KAM, ITR and anterior tibial shear on the likelihood of ACL rupture. High-risk in vivo values for KAM, ATS, and ITR will be incrementally increased until tissue failure is achieved in cadavers, or ACL failure strains are reached in FE models. Furthermore, in Aim II we will optimize our FE modeling approach through validation of a methodology to customize models that accounts for variability in anatomy and tissue mechanics. This research will significantly improve the ability of researchers and clinicians to effectively screen athletes for ACL injury risk, and will increase ACL injury prevention program enrollment and efficacy.
描述(申请人提供):前十字韧带(ACL)损伤是一个主要的医疗和经济负担。尽管确定了可改变的危险因素和有效的预防措施,但全球前交叉韧带损伤发生率基本上仍未受到影响。在父母的资助下,我们确定了没有伴随的内侧副韧带(MCL)损伤的前交叉韧带损伤的可信的外翻塌陷机制。我们在基金资助下开发的一种新的身体测试装置显示出近90%的前交叉韧带撕裂率。我们的研究结果表明,膝关节外展力矩(KAM)、胫骨前剪力(ATS)和胫骨内旋转力(ITR)的联合作用在前交叉韧带中产生的应变明显大于前交叉韧带,并重现了与前交叉韧带损伤时相似的运动学。虽然这些类型的负荷单独存在会增加前交叉韧带的张力和潜在的损伤风险,但它们对前交叉韧带生物力学的综合影响尚不清楚。在这一竞争性的更新应用中,我们将开发一种高度有效和独特的前交叉韧带损伤风险评估方案,该方案考虑了多平面生物力学。该方案将通过一种新颖的、一体化的体内、体外和硅胶(在SIM)方法来开发。具体目标是:i)开发和验证基于动态ACL应变预测ACL损伤风险的多平面ACL损伤风险评估算法;ii)整合体内、体外和计算机方法,以建立考虑KAM、ITR和ATS在ACL断裂中的相对贡献的风险连续体。这两个AIM之间的关键区别是生物力学背景:Aim I将确定在实验室或临床环境下执行的非损伤性筛查任务中前交叉韧带如何受到张力。目的II将建立高应变运动模式与前交叉韧带损伤机制之间的直接联系(S)。我们假设:i)来自体内数据的KAM、ITR和ATS的峰值输入值将准确地预测落地生物力学在体外和硅胶中复制时的ACL峰值应变,以及ii)KAM、ITR和ATS的增量增加将导致在体外和硅胶中的前交叉韧带断裂。在具体目标I中,多平面运动学和动力学将直接用作我们经过验证的、特定于性别的粘弹性FE膝关节模型和体外测试方案的输入,以测试我们的假设。我们还将致力于识别和验证KAM、ITR和ATS的简单、基于临床的预测因素,以最大限度地提高该方案的临床适用性。在AIM II中,我们将直接研究KAM、ITR和胫前剪切力在前交叉韧带断裂可能性中的作用。KAM、ATS和ITR的体内高危值将逐渐增加,直到身体出现组织衰竭,或者在FE模型中达到前交叉韧带衰竭应变。此外,在AIM II中,我们将通过验证一种定制模型的方法来优化我们的有限元建模方法,该方法可以解释解剖学和组织力学中的可变性。这项研究将显著提高研究人员和临床医生有效筛查运动员前交叉韧带损伤风险的能力,并将增加前交叉韧带损伤预防计划的登记人数和疗效。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Timothy E Hewett其他文献

ACL graft metabolic activity assessed by 18FDG PET-MRI.
通过 18FDG PET-MRI 评估 ACL 移植物代谢活性。
  • DOI:
    10.1016/j.knee.2017.04.008
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Robert A Magnussen;K. Binzel;Jun Zhang;Wen;Melanie U Knopp;David C Flanigan;Timothy E Hewett;Christopher C Kaeding;Michael V Knopp
  • 通讯作者:
    Michael V Knopp

Timothy E Hewett的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Timothy E Hewett', 18)}}的其他基金

Multi-faceted Approach Modeling ACL Injury Mechanisms
多方位方法模拟 ACL 损伤机制
  • 批准号:
    7846129
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Multi-faceted Approach Modeling ACL Injury Mechanisms
多方位方法模拟 ACL 损伤机制
  • 批准号:
    8284418
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Multi-faceted Approach to Modeling ACL Injury Mechanisms
ACL 损伤机制建模的多方面方法
  • 批准号:
    8651985
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Multi-faceted Approach to Modeling ACL Injury Mechanisms
ACL 损伤机制建模的多方面方法
  • 批准号:
    8735607
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Multi-faceted Approach Modeling ACL Injury Mechanisms
多方位方法模拟 ACL 损伤机制
  • 批准号:
    7654283
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Multi-faceted Approach Modeling ACL Injury Mechanisms
多方位方法模拟 ACL 损伤机制
  • 批准号:
    8069179
  • 财政年份:
    2009
  • 资助金额:
    $ 62.78万
  • 项目类别:
Neuromuscular Intervention Targeted to Mechanisms of ACL Load in Female Athletes
针对女运动员 ACL 负荷机制的神经肌肉干预
  • 批准号:
    8123294
  • 财政年份:
    2008
  • 资助金额:
    $ 62.78万
  • 项目类别:
Neuromuscular Intervention Targeted to Mechanisms of ACL Load in Female Athletes
针对女运动员 ACL 负荷机制的神经肌肉干预
  • 批准号:
    7665088
  • 财政年份:
    2008
  • 资助金额:
    $ 62.78万
  • 项目类别:
Neuromuscular Intervention Targeted to Mechanisms of ACL Load in Female Athletes
针对女运动员 ACL 负荷机制的神经肌肉干预
  • 批准号:
    8309809
  • 财政年份:
    2008
  • 资助金额:
    $ 62.78万
  • 项目类别:
Neuromuscular Intervention Targeted to Mechanisms of ACL Load in Female Athletes
针对女运动员 ACL 负荷机制的神经肌肉干预
  • 批准号:
    7528929
  • 财政年份:
    2008
  • 资助金额:
    $ 62.78万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 62.78万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了