Patient-Specific Modeling of Total Knee Arthroplasty

描述(由申请人提供)：这项工作的目的是开发和验证一种创建针对患者的全膝关节置换术(TKA)的过程，在手术时测量假体对齐和初始软组织平衡。全膝关节置换术是一种常见的外科手术，用于治疗退行性关节疾病，如骨关节炎。2006年，美国估计进行了500,000次TKA，预计到2030年，每年将进行大约348万次手术。虽然TKA在缓解关节疼痛方面大致上是成功的，但一些接受TKA的人无法进行基本的日常生活活动，如在家中舒适地爬楼梯，许多人发现自己无法恢复他们喜欢的活动，如远足、打高尔夫球或打网球。全膝关节置换术的成功取决于许多因素，包括术前膝关节状况、假体对齐、膝关节周围软组织的处理(或“平衡”)以及术后康复。尽管许多外科医生在手术中手动操作膝关节时，已经熟练地形成了膝关节稳定性的定性“感觉”，但膝关节的“感觉”如何从未被记录在案，也不存在关于手术后可接受的稳定性的客观定义。对TKA术后即刻膝关节的计算机模拟有可能为了解假体对位和膝关节稳定性如何影响患者术后执行重要功能任务的能力提供有价值的见解。然而，目前这些模拟依赖于基于身体标本测量的关节通用描述，或者模拟受到膝关节周围韧带特性的严重影响，这些特性通常是使用文献中的档案数据来建模的。由于骨关节炎膝关节的韧带特性和运动学与健康膝关节不同，在全膝关节置换术后可能仍然不同，这些假设使得无法预测特定患者的术后功能。计算机模拟表征了个体患者特定的假体排列、运动学和韧带特性，代表了朝着建立“平衡”膝关节的客观定义和改善术后功能结果迈出的重要一步。该项目将开发新的针对患者的TKA正向动态模拟。Aim 1将开发一种新的方法，通过在手术导航系统和可以测量关节稳定性的定制设备的帮助下，在身体标本上进行一系列TKA，创建针对患者的计算机模拟。我们将使用这些记录的数据来开发针对患者的前向动态模拟，通过优化例程确定韧带属性，并将探索韧带长度、韧带材料属性和建模元素数量在优化中的影响。然后，我们将模拟实验仰卧位被动活动范围测试，在我们的定制设备中进行膝关节稳定性的实验表征，两者都使用不同的试验胫骨插入物执行，并模拟主动膝关节伸展。该方法的成功将基于模拟的能力，以匹配相同运动的实验测量的胫股接触力、膝关节运动学和韧带力。在目标2中，我们将比较目标1中开发的特定于对象的模拟的准确性与其他3种已建立的肌肉骨骼建模技术的结果，这些技术使用文献中的通用参数来规定关节运动学和/或韧带属性。将4种不同建模方法产生的膝关节运动学模拟值、接触力和韧带力的结果与被动和模拟主动膝关节伸展试验和稳定装置中的运动试验记录的相同值进行比较。这项全面而严谨的研究为开发基于组件对齐和软组织平衡的TKA患者的特定患者模拟创造了一个过程。这种建模方法可以用来客观地参数化手术技术，特别是组件对齐和初始软组织平衡，并可以结合到未来几代手术导航系统中，根据术中测量来预测手术后的结果。来自这种针对患者的模拟的数据将提供可量化的指导方针，使外科医生能够做出更好的术中决定，帮助物理治疗师为特定的患者量身定做康复计划，并给患者对自己特定结果的更现实的期望。 公共卫生相关性：2006年，美国总共进行了大约50万例膝关节置换手术，以治疗骨关节炎等疾病的疼痛和残疾，预计到2030年，这一数字将飙升至每年约348万例。虽然手术在恢复功能和改善生活质量方面总体上是成功的，但那些不能在家中舒适地爬楼梯等基本日常生活活动的人，与那些可以重新开始他们喜欢的活动，如徒步旅行、打高尔夫球或打网球的人，仍然存在很大的差距。这项工作的目的是开发新的针对患者的全膝关节置换的计算机模拟，以确定外科技术，特别是初始软组织平衡和假体对齐，如何与患者的全膝关节置换术后的活动相关。

DESCRIPTION (provided by applicant): The purpose of this work is to develop and validate a process for creating patient-specific simulations of total knee arthroplasty (TKA) with measurements of component alignment and initial soft tissue balance taken at the time of surgery. TKA is a common surgical procedure used to treat degenerative joint diseases such as osteoarthritis. An estimated 500,000 TKAs were performed in the United States in 2006, and approximately 3.48 million annual procedures are expected by the year 2030. While TKA is generally successful at relieving joint pain, some TKA recipients cannot perform basic activities of daily living such as comfortably climbing the stairs in their homes, and many find themselves unable to resume activities they love such as hiking, golfing, or playing tennis. The success of TKA depends on many factors including the pre-operative condition of the knee, alignment of the prosthetic components, management (or "balancing") of soft tissues around the knee, and post-operative rehabilitation. Even though many surgeons have become skilled in developing a qualitative "feel" for knee stability as they manually manipulate the knee during surgery, how the knee "feels" is never documented, and an objective definition as to what constitutes acceptable post-operative stability does not exist. Computer simulations of the knee immediately following TKA have the potential to provide valuable insight into how component alignment and knee stability could affect a patient's ability to perform important functional tasks post-operatively. However, these simulations currently rely on generic descriptions of joints based on measurements made in cadaver specimens, or the simulations are heavily influenced by the properties of the ligaments that surround the knee, which are typically are modeled using archival data from the literature. Since the ligament properties and kinematics in an osteoarthritic knee are different from those of a healthy knee and may remain different following TKA, these assumptions make it impossible to predict the post-operative function of a given patient. Computer simulations which characterize the subject-specific component alignment, kinematics, and ligamentous properties of an individual patient represent an important step toward establishing an objective definition of a "balanced" knee and improving post-operative functional outcomes. This project will develop new patient-specific forward dynamic simulations of TKA. Aim 1 will develop a novel approach for creating patient-specific computer simulations through a series of TKAs on cadaver specimens with the assistance of a surgical navigation system and a custom device that can measure joint stability. We will use these recorded data to develop patient-specific forward dynamic simulations that determine ligament properties through an optimization routine and will explore the effect of ligament lengths, ligament material properties, and number of modeling elements in our optimization. We will then simulate an experimental supine passive range of motion test, the experimental characterizations of knee stability in our custom device, both performed with different trial tibial inserts, and a simulated active knee extension. The success of the approach will be based on the ability of the simulations to match experimentally measured tibiofemoral contact force, knee kinematics, and ligament forces of the same motions. In Aim 2, we will compare the accuracy of the subject-specific simulations developed in Aim 1 against the results of 3 other types of established musculoskeletal modeling techniques that prescribe joint kinematics and/or ligament properties with generic parameters from the literature. The results of the simulated values of knee kinematics, and contact and ligament forces that are generated from the 4 different modeling approaches will be compared against the same values that are recorded experimentally for the tests of passive and simulated active knee extension and the motions in the stability device. This comprehensive and rigorous study creates a process for developing patient-specific simulations of TKA patients based on component alignment and soft tissue balancing. This modeling approach can then be used to objectively parameterize surgical technique, specifically component alignment and initial soft tissue balance, and can be incorporated into future generations of surgical navigation systems to predict post- operative outcome from intra-operative measurements. Data from such patient-specific simulations will provide quantifiable guidelines that will enable surgeons to make better intra-operative decisions, help physical therapists to tailor rehabilitation programs to specific patients, and give patients more realistic expectations for their own specific outcomes. PUBLIC HEALTH RELEVANCE: Approximately 500,000 total knee replacements were performed in the United States in 2006 to treat the pain and disability of diseases like osteoarthritis, and number is expected to skyrocket to approximately 3.48 million annual procedures by the year 2030. While the surgery is generally successful at restoring function and improving quality of life, a wide gap still separates those who cannot perform basic activities of daily living like comfortably climbing the stairs within their homes to those who can go back to activities they love such as hiking, golfing, or playing tennis. The purpose of this work is to develop new patient-specific computer simulations of total knee replacement for determining how surgical technique, specifically initial soft tissue balance and component alignment, relate to a patient's activities following total knee replacement.