Innovative Tools for In Vivo Computational Prediction of Lumbar Stresses

肌肉骨骼研究中心（CMR）是橡树岭国家实验室（ORNL）和田纳西大学（UT）的联合项目。在Richard D.作为主要研究者（PI）的Komistek博士，CMR的研究人员提出开发准确的计算模型，最终可用于预测下背部椎体和骶骨的关节面界面（椎间盘和关节面）的体内接触应力，并评估融合或椎间盘置换手术后疼痛减轻方面的手术结局。该提案的主要目标是开发一种精确的计算方法，其包括：1）使用X射线荧光透视、用于骨建模的CT扫描和用于软组织评估的腰椎MRI作为我们的数学模型的输入来推导和实现体内运动学; 2）使用数学模型计算脊柱界面处的力; 3）计算正常和退变椎间盘条件下椎间盘的变形和应力（手术前阶段）; 4）开发腰椎结构的体内计算建模能力;以及5）开发将计算数据和临床数据相关联的方法。该模型最终可用于预测在体内接触应力的轴承表面接口，韧带力，提供约束，和肌肉力量（和肌腱）的椎体的下背部。该模型将使我们能够评估融合或椎间盘置换手术后疼痛减轻方面的手术结局，并可用于未来脊柱假体的设计和验证。我们将与范德比尔特大学的临床医生合作，将临床和计算数据关联起来并进行验证。据估计，80-90%的美国人在一生中的某个时候会经历下背痛。它是美国最常见的与工作有关的医疗问题，也是仅次于普通感冒的第二大最常见的就医原因。下背痛是19-45岁人群残疾的主要原因，也是错过工作日的主要原因。慢性背痛患者占工人赔偿要求中治疗费用的80%。寿命的延长和中老年人比例的增加使下背痛成为一个日益严重的问题。治疗和错过工作的费用每年高达数十亿美元。从骨科的角度来看，脊柱是市场增长最快的部分。新的治疗方法，包括全椎间盘置换术和小关节置换术，将提供融合的替代方案，但需要进行更多的生物力学研究，并开发适当的工具来开发预测模型，评估器械的安全性，并将这些知识和工具提供给骨科社区。

DESCRIPTION (provided by applicant): The Center for Musculoskeletal Research (CMR) is a joint program between Oak Ridge National Laboratory (ORNL) and the University of Tennessee (UT). Under the leadership of Richard D. Komistek, PhD as the Principal Investigator (PI), researchers in the CMR propose to develop accurate computational models that could eventually be used to predict in vivo contact stresses at the bearing surface interface (disc and facets) of the vertebral bodies and sacrum of the lower back and assess surgical outcomes in terms of reduction of pain after fusion or disk replacement surgery. The main goal of the proposal is to develop an accurate computational methodology that involves: 1) deriving and implementing in vivo kinematics using X- ray fluoroscopy, CT scans for bone modeling and MRIs of the lumbar spine for soft-tissue evaluation as input to our mathematical models; 2) computing the forces at the spine interfaces using a mathematical model; 3) computing the deformation and stresses in the intervertebral discs under normal and degenerative disc conditions (pre-surgery stage); 4) developing an in vivo computational modeling capability for the lumbar spine structure; and 5) developing a methodology to correlate the computational and clinical data. The model could eventually be used to predict in vivo contact stresses at the bearing surface interfaces, ligament forces that provide constraint, and muscle forces (and tendons) of the vertebral bodies of the lower back. This model would allow us to assess surgical outcomes in terms of reduction of pain after fusion or disk replacement surgery, and could be used in the future design and validation of spinal prostheses. We will team with clinicians at Vanderbilt University to correlate and validate the clinical and computational data. It is estimated that 80-90% of the U.S. population will experience lower back pain at some point in their lifetime. It is the most common work-related medical problem in the United States, and the second most common reason for doctor visits behind the common cold. Lower back pain is the leading cause of disability among people ages 19-45 and is the leading cause of missed work days. People with chronic back pain account for 80% of the cost of treatment in workers compensation claims. Longer life-spans and an increasing proportion of middle aged and elderly people make lower back pain an increasingly significant problem. The cost in terms of treatments and missed work is billions of dollars annually. From an orthopedic perspective, the spine is the fastest growing segment of the market. New treatments, including total disk replacement, and facet arthroplasty, will provide alternatives to fusion, but there is a need to do more biomechanical research and develop appropriate tools to develop predictive models, assess safety of the devices, and make this knowledge and the tools available to the orthopedic community.