Multi-faceted Approach to Modeling ACL Injury Mechanisms

描述（由申请人提供）：前交叉韧带（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，全球ACL损伤发生率在很大程度上仍未受到影响。在父母的资助下，我们确定了不伴有内侧副韧带（MCL）损伤的前交叉韧带损伤的合理外翻塌陷机制。我们在基金资助下开发的一种新型尸体测试装置显示了近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）、胫骨前剪切力（ATS）和胫骨内旋转力矩（ITR）的联合作用在前交叉韧带中产生的应变明显大于中交叉韧带，并且再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增加前交叉韧带劳损和潜在的损伤风险，但它们对前交叉韧带生物力学的综合影响尚未得到很好的理解。在这个竞争性的更新应用中，我们将开发一个具有高度影响力和独特的ACL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、综合的体内、体外和硅（in sim）方法来开发。具体目标是：1)开发并验证基于动态ACL应变预测ACL损伤风险的多平面ACL损伤风险评估算法；2)整合体内、体外和计算机方法，建立“风险连续体”，解释KAM、ITR和ATS对ACL破裂的相对贡献。两个Aims之间的关键区别在于生物力学背景：Aim I将确定在实验室或临床环境中进行的非损伤性筛查任务中ACL是如何拉伤的。Aim II将建立高应变运动模式和前交叉韧带损伤机制之间的直接联系。我们假设：I)当在体外和计算机中再现着陆生物力学时，来自体内数据的KAM、ITR和ATS的峰值输入值将准确预测ACL应变峰值；II)从“高风险”的体内措施中按比例增加KAM、ITR和ATS的增量将导致ACL在体外和计算机中破裂。在Specific Aim I中，多平面运动学和动力学将直接用作我们验证的、性别特异性的、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、基于临床的预测指标，以最大限度地提高该方案的临床适用性。在Aim II中，我们将直接检查KAM， ITR和胫骨前切变对ACL破裂可能性的作用。体内KAM、ATS和ITR的高风险值将逐渐增加，直到在尸体中实现组织衰竭，或在FE模型中达到ACL衰竭株。此外，在Aim II中，我们将通过验证一种方法来优化我们的有限元建模方法，以定制考虑解剖学和组织力学变化的模型。本研究将显著提高研究人员和临床医生有效筛查运动员ACL损伤风险的能力，并将增加ACL损伤预防项目的报名人数和疗效。

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.