The Effect of High Tibial Osteotomy Correction Angle on Cartilage and Meniscus Loading Using Finite Element Analysis

Medial opening wedge high tibial osteotomy (MOWHTO) is a popular clinical method for curing the osteoarthritis (OA) caused by varus deformity. However, the ideal alignment to maximize osteotomy successful rate and post-operative knee function remains controversial to date. Moreover, the between-patient variability of knee joint biomechanics, particularly during functional tasks, signifies critical importance of conducting patient-specific planning. For this reason, this study introduces a subject-specific modeling procedure to determine the biomechanical effects of simulated different alignments of MOWHTO on tibiofemoral cartilage stress distribution. A 3D finite element (FE) knee model was developed from MRI images of a healthy living subject and used to simulate different alignments following MOWHTO (i.e. 0.2°, 2.7°, 3.9° and 6.6° valgus). Loading and boundary conditions were assigned based on the subject-specific kinematic and kinetic data recorded during gait tests. The compressive and shear stress distributions in the femoral cartilage and tibia cartilage were quantified. It was found that when the loading axis shifted laterally, the peak stresses in the medial compartment decreased, but increased in the lateral compartment. The findings suggest that equal loading between two compartments can be successfully achieved by performing MOWHTO with a HKA angle around 3.9 to 6.6° valgus. More importantly, this patient-specific non-invasive analysis of stress distribution that provided a quantitative insight to evaluate the mechanical responses of the soft tissue within knee joint as a result of adjusting the loading axis, may be used as a preoperative assessment tool to predict the consequential mechanical loading information for surgeon to decide the patient specific optimal angle

Individualised Modelling for Preoperative Planning of Total Knee Replacement Surgery

Total knee replacement (TKR) surgery is routinely prescribed for patients with severe knee osteoarthritis to alleviate the pain and restore the kinematics. Although this procedure was proven to be successful in reducing the joint pain, the number of failures and the low patients’ satisfaction suggest that while the number of reoperations is small, the surgery frequently fail to restore the function in full. The main cause are surgical techniques which inadequately address the problem of balancing the knee soft tissues. The preoperative planning technique allows to manufacture subject-specific cutting guides that improves the placement of the prosthesis, however the knee soft tissue is ignored. The objective of this dissertation was to create an optimized preplanning procedure to compute the soft tissue balance along with the placement of the prosthesis to ensure mechanical stability. The dissertation comprises the development of CT based static and quasi-static knee models able to estimate the postoperative length of the collateral lateral ligaments using a dataset of seven TKR patients; In addition, a subject-specific dynamic musculoskeletal model of the lower limb was created using in vivo knee contact forces to perform the same analysis during walking. The models were evaluated by their ability to predict the postoperative elongation using a threshold based on the 10 % of the preoperative length, through which the model detected whether an elongation was acceptable. The results showed that the subject-specific static model is the best solution to be included in the optimized, subject-specific, preoperative planning framework; full order musculoskeletal model allowed to estimate the postoperative length of the ligaments during walking, and at least in principle while performing any other activity. Unlike the current methodology used in clinic this optimized preoperative planning framework might help the surgeon to understand how the position of the TKR affects the knee soft tissue

Towards Functional Preoperative Planning in Orthopaedic Surgery

Las cirugíıas del aparato locomotor suponen más de 20 millones de intervencionesanuales para la corrección de lesiones que afectan a músculos, articulaciones,ligamentos, tendones, huesos o nervios; elementos que conforman el sistema musculoesquelético. Este tipo de afecciones de la biomecánica pueden tener diversos orígenes; siendo los principales los traumatismos, las lesiones degenerativas en huesos y tejidos blandos, los malos hábitos posturales o motores, y los de origen congénito.El uso de las tecnologías actuales en los procesos de corrección de estas afecciones forma parte del día a día en los quirófanos y en la monitorización de los pacientes.Sin embargo, el uso de técnicas computacionales que permitan la preparación de las intervenciones quirúrgicas antes de proceder con la cirugía están todavía lejos de formar parte del proceso de evaluación preoperatoria en este tipo de lesiones. Por este motivo, el objetivo principal de esta tesis consiste en demostrar la viabilidad del uso de herramientas computacionales en la planificación preoperatoria de diferentes cirugías ortopédicas.Entre los tipos de cirugías más comunes, la mayor parte de ellas se centran en las articulaciones del tren inferior de la anatomía humana. Por este motivo, este trabajo se centraría en el análisis de diferentes cirugías cuya finalidad es solucionar lesiones en las principales articulaciones del tren inferior: región sacrolumbar, cadera, rodilla y tobillo.Para poder realizar el análisis de estas cirugías se hizo uso de algunas de lasherramientas computacionales más usadas habitualmente y cuya capacidad en diversos ámbitos ha sido comprobada. Se ha utilizado la reconstrucción 3D para la obtención de modelos anatómicos sobre los que comprobar la viabilidad de las cirugías. Estas reconstrucciones se basan en las imágenes médicas obtenidas mediante Tomografia Axial Computerizada (TAC) o Resonancia Magnética (RM). Las imágenes procedentes de RM permiten diferenciar todos los tejidos de la anatomía, incluyendo los blandos tales como tendones o cartílagos; mientras que los TAC facilitan la diferenciación de los huesos. Esta última es la prueba más habitual en los diagnósticos.Para su análisis y reconstrucción se hizo uso de los software Mimics v 20.0 y3-matic 11.0 (Materialise NV, Leuven, Belgium). Como alternativa para la generación de los modelos cuando no se dispone de las imágenes necesarias para realizar la reconstrucción o cuando se requiere dotar de flexibilidad a estos modelos, se recurrió al modelado en el software de análisis por elementos finitos Abaqus/CAE v.6.14 (Dassault Syst`emes, Suresnes, France). Dicho software fue además utilizado para la simulación del efecto de las diferentes cirugías sobre la región de interés. Para resalizar las simulaciones, se incluyeron en los modelos aquellos parámetros, elementos y condiciones necesarios para poder representar las caraterísticas propias de cada cirugía. Finalmente, para aquellas situaciones que requerían del análisis de datos se hizo uso de tecnologías de machine learning. La solución seleccionada para estos casos fueron las redes neuronales artificiales (ANN). Dichas redes se desarrollaronhaciendo uso del software MATLAB R2018b (MathWorks, Massachusetts, USA).El estudio de la rodilla se centra en uno de los ligamentos clave en la estabilidad de la rótula y que, sin embargo, es uno de los menos analizados hasta ahora, el ligamento medial patelofemoral. La reconstrucción de este ligamento es la principal solución clínica para solventar esta inestabilidad y diferentes cirugías utilizadas para dicho fin han sido analizadas mediante el desarrollo de un modelo paramétrico en elementos finitos que permita su simulación. En este modelo es posible adaptar la geometría de la rodilla de forma que se puedan simular diferentes condiciones que pueden afectar a la estabilidad de la rótula, tales como la displasia troclear y la patella alta.El estudio de la región sacrolumbar se centra en el análisis de diferentes posibles configuraciones para las cirugías de fusión vertebral. El análisis se centró en la fijación con tornillos y la influencia del Polimetimetacrilato (PMMA) como elemento de fijación en las vértebras. Para ello, se reconstruyó el modelo óseo de diferentes pacientes que necesitaron este tipo de intervención. Sobre estos modelos se simularon mediante elementos finitos las diferentes configuraciones consideradas de forma que se pudiera comparar su comportamiento en diferentes casos.En el caso de la cadera, el estudio se centra en el análisis de la artroplastia total de cadera, que implica el reemplazo de la articulación anatómica por una prótesis habitualmente de titanio. Cuando este tipo de cirugías es realizado, es común que surjan posteriormente problemas derivados de la disposición de la prótesis y que pueden llevar al pinzamiento entre sus componentes y, en algunas ocasiones, su dislocación.Esto ocurre cuando el rango de movimiento de la articulación es reducido. Este tipo de sucesos son más comunes cuando se realizan los movimientos de extensión externa (EE) o de rotación interna (RI) de la extremidad. El estudio se desarrolló con el objetivo de elaborar una herramienta computacional capaz de predecir este choque y dislocación basándose en el diámetro de la cabeza del femur y de los ángulos de abducción y anteversión. Para ello, se recurrió al uso de redes neuronales artificales(ANN). Se configuró una red independiente para cada movimiento (EE y RI) y cada posible evento (pinzamiento y dislocación), de forma que se obtuvieron cuatro redes completamente independientes. Para el entrenamiento y primer testeo de las redes se recurrió a un modelo paramétrico en elementos finitos de la prótesis con el que se realizaron diferentes simulaciones determinando el rango de movimiento para cada caso. Finalmente, las redes fueron de nuevo validadas con el uso de datos procedentes de pacientes que sufrieron dislocación tras ser sometidos a este tipo de cirugías.Finalmente, el estudio de la región del tobillo se centró en la lesión de la sindesmosis del tobillo. Este tipo de lesiones implica la rotura de algunos de los ligamentos que unen los principales huesos de esta articulación (tibia, peroné y astrágalo) junto con parte de la membrana intraósea, que se extiende a lo largo de la tibia y el peroné ligando ambos huesos. Cuando se produce este tipo de lesiones, es necesario recurrir a la inclusión de elementos que fijen la articulación y prevengan la separación de los huesos. Los métodos más comunes y que centran este análisis comprenden la fijación con tornillos y la fijación mediante botón de sutura. Para poder realizar un análisis que permita comparar la efectividad y incidencia de este tipo de cirugías se recurrióa la reconstruccción 3D de la articulación de un paciente que sufrió este tipo de lesión. Con este modelo geométrico, se procedió al desarrollo de diferentes modelos en elementos finitos que incluyeran cada una de las alternativas consideradas. Las simulaciones de estos modelos junto a las situaciones anatómicas y lesionadas, permitió hacer una aproximación sobre la solución quirúrgica que mejor restablece el estado incial sano de la región afectada.Locomotor system surgeries represents more the 20 million interventions per year for the correction of injuries that affect muscles, joints, ligaments, tendons, bones or nerves; elements that form themusculoskeletal system. This kind of biomechanical affections may have several sources, being the main ones traumas, bones and soft tissues degenerative injuries, poor postural or motor habits and those of congenital source. The use of current technologies in the correction process for these injuries is part of the day-to-day in the operating rooms and the monitoring of patients. However, the use of computational tools that allow preoperative planning is still far from being part of the preoperative evaluation process in this kind of injuries. For this reason, the main goal of this thesis consists in demonstrating the viability of the use of computational tools in the preoperative planning of different orthopaedic surgeries. Among the most common surgeries, most of them focus in the lower body joints of the human anatomy. For this reason, this work will focus in the analysis of different surgeries whose purpose is to solve injuries in the main joints of the lower body: lumbosacral region, hip, knee and ankle. Some of the most commonly used computational tools, and whose capability in different fields has been widely proven, were used in order to be able of performing the analysis of these surgeries. 3D reconstruction has been used for obtaining anatomical models in which the viability of the surgeries could be verified. These reconstructions are based on the medical images obtained through Computerized Tomography (CT) or Magnetic Resonance Imaging (RMI). Images from RMI allow differentiating all the tissues of the anatomy, including soft ones such as tendons and cartilages; while CT scans make easier the bones differentiation. This last procedure is the most commonly used in diagnoses. For their analysis and reconstruction software Mimics v 20.0 and 3-Matic 11.0 (Materialise NV, Leuven, Belgium) were used. As alternative for the models generation when the necessary images for the reconstruction are not available or when flexibility is required for these models, modelling in the Finite Element Analysis software Abaqus/CAE v.6.14 (Dassault Syst‘emes, Suresnes, France) was used. This software was also used for the simulation of the effects of the different surgeries in the interest region. In order to perform the simulations, those parameters, elements and conditions necessary to represent the characteristics of each surgery were included. Finally, for those situations requiring data analysis, machine learning technologies were used. The selected solution for these cases were Artificial Neural Networks (ANN). These networks were developed using the software MATLAB R2018b (MathWorks, Massachusetts, USA). The study of the knee joint focuses in one of the key ligaments for the patellar stability and which, however, is one of the least analysed so far, the medial patellofemoral ligament. The reconstruction of this ligament is the main clinical solution for solving this instability and different surgeries used for that purpose have been analysed through the development of a finite element parametric model that allows their simulation. In this model adapting knee geometry is possible so that those conditions that can affect the stability of the patella, such as trochlear dysplasia or patella alta, can be simulated. The study of the lumbosacral region focuses in the analysis of different possible configurations for spine fusion surgeries. The analyses focused in the pedicle screws fixation and the influence of polymethyl methacrylate (PMMA) as fixation element in the vertebrae. To do this, osseous models for different patients that required this kind of intervention were reconstructed. The different configurations considered were simulated on these models through finite element analysis comparing their behaviour. In the case of the hip, the study focuses in the analysis of the total hip arthroplasty, which implies replacing the anatomical joint by a prosthesis, usually made of titanium. When this kind of surgery is performed, it is common for later issues arising from the arrangement of the prosthesis and which can lead to impingement between its components and, on some occasions, their dislocation. This happens when the range of movement of the joint is limited. This kind of events are more common when the external extension (EE) or internal rotation (IR) movements of the leg are performed. The study was developed with the goal of elaborating a computational tool able to predict the impingement and dislocation based on the diameter of the head of the femur and the anteversion and abduction angles. To do this, artificial neural networks (ANN) were used. An independent network was configured for each movement (EE and IR) and for each possible event (impingement and dislocation), so that four completely independent networks. For the training and the first testing of the networks, a parametric finite element model of the hip was used; with which different simulations were performed determining the range of movement for each case. Finally, the networks were validated again with the use of data proceeding from patients that suffered dislocation after going through this kind of surgery. Finally, the study of the ankle region focused in the ankle syndesmosis injury. This kind of injuries implies the tear of some ligaments that connect the main bones of the joint (tibia, fibula and talus) together with part of the intraosseous membrane, which extends along the tibia and fibula linking both bones. When this kind of injuries happens, it is necessary to resort to the inclusion of elements that fix the joint and prevent the bones distance. The most common methods, which focus this analysis, include the screws fixation and the suture button fixation. In order to carry out an analysis that allows comparing the effectiveness and incidence of this kind of surgeries, a 3D reconstruction of the joint from a patient that suffered this kind of injury was used. With this geometrical model, different finite element models including each of the considered alternatives were developed. The simulations of these models, together with the injured and anatomical situations, allowed an approximation of the surgical solution that better restores the initial healthy state of the affected region.<br /

Studies on Spinal Fusion from Computational Modelling to ‘Smart’ Implants

Low back pain, the worldwide leading cause of disability, is commonly treated with lumbar interbody fusion surgery to address degeneration, instability, deformity, and trauma of the spine. Following fusion surgery, nearly 20% experience complications requiring reoperation while 1 in 3 do not experience a meaningful improvement in pain. Implant subsidence and pseudarthrosis in particular present a multifaceted challenge in the management of a patient’s painful symptoms. Given the diversity of fusion approaches, materials, and instrumentation, further inputs are required across the treatment spectrum to prevent and manage complications. This thesis comprises biomechanical studies on lumbar spinal fusion that provide new insights into spinal fusion surgery from preoperative planning to postoperative monitoring. A computational model, using the finite element method, is developed to quantify the biomechanical impact of temporal ossification on the spine, examining how the fusion mass stiffness affects loads on the implant and subsequent subsidence risk, while bony growth into the endplates affects load-distribution among the surrounding spinal structures. The computational modelling approach is extended to provide biomechanical inputs to surgical decisions regarding posterior fixation. Where a patient is not clinically pre-disposed to subsidence or pseudarthrosis, the results suggest unilateral fixation is a more economical choice than bilateral fixation to stabilise the joint. While finite element modelling can inform pre-surgical planning, effective postoperative monitoring currently remains a clinical challenge. Periodic radiological follow-up to assess bony fusion is subjective and unreliable. This thesis describes the development of a ‘smart’ interbody cage capable of taking direct measurements from the implant for monitoring fusion progression and complication risk. Biomechanical testing of the ‘smart’ implant demonstrated its ability to distinguish between graft and endplate stiffness states. The device is prepared for wireless actualisation by investigating sensor optimisation and telemetry. The results show that near-field communication is a feasible approach for wireless power and data transfer in this setting, notwithstanding further architectural optimisation required, while a combination of strain and pressure sensors will be more mechanically and clinically informative. Further work in computational modelling of the spine and ‘smart’ implants will enable personalised healthcare for low back pain, and the results presented in this thesis are a step in this direction

Personalized Hip and Knee Joint Replacement

This open access book describes and illustrates the surgical techniques, implants, and technologies used for the purpose of personalized implantation of hip and knee components. This new and flourishing treatment philosophy offers important benefits over conventional systematic techniques, including component positioning appropriate to individual anatomy, improved surgical reproducibility and prosthetic performance, and a reduction in complications. The techniques described in the book aim to reproduce patients’ native anatomy and physiological joint laxity, thereby improving the prosthetic hip/knee kinematics and functional outcomes in the quest of the forgotten joint. They include kinematically aligned total knee/total hip arthroplasty, partial knee replacement, and hip resurfacing. The relevance of available and emerging technological tools for these personalized approaches is also explained, with coverage of, for example, robotics, computer-assisted surgery, and augmented reality. Contributions from surgeons who are considered world leaders in diverse fields of this novel surgical philosophy make this open access book will invaluable to a wide readership, from trainees at all levels to consultants practicing lower limb surger

Development and Implementation of a Computational Surgical Planning Model for Pre-Operative Planning and Post-Operative Assessment and Analysis of Total Hip Arthroplasty

Total hip arthroplasty (THA) is most often used to treat osteoarthritis of the hip joint. Due to lack of a better alternative, newer designs are evaluated experimentally using mechanical simulators and cadavers. These evaluation techniques, though necessary, are costly and time-consuming, limiting testing on a broader population. Due to the advancement in technology, the current focus has been to develop patient-specific solutions. The hip joint can be approximated as encompassing a bone socket geometry, and therefore the shapes of the implant are well constrained. The variability of performance after the surgery is mostly driven by surgical procedures. It is believed that placing the acetabular component within the “safe zone” will commonly lead to successful surgical outcomes [1]. Unfortunately, recent research has revealed problems with the safe zone concept, and there is a need for a better tool which can aid surgeons in planning for surgery.With the advancement of computational power, more recent focus has been applied to the development of simulation tools that can predict implant performances. In this endeavor, a virtual hip simulator is being developed at the University of Tennessee Knoxville to provide designers and surgeons alike instant feedback about the performance of the hip implants. The mathematical framework behind this tool has been developed.In this dissertation, the primary focus is to further expand the capabilities of the existing hip model and develop the front-end that can replicate a total hip arthroplasty surgery procedure pre-operatively, intra-operatively, and post-operatively. This new computer-assisted orthopaedic surgical tool will allow surgeons to simulate surgery, then predict, compare, and optimize post-operative THA outcomes based on component placement, sizing choices, reaming and cutting locations, and surgical methods. This more advanced mathematical model can also reveal more information pre-operatively, allowing a surgeon to gain ample information before surgery, especially with difficult and revision cases. Moreover, this tool could also help during the implant development design process as designers can instantly simulate the performance of their new designs, under various surgical, simulated in vivo conditions

Patient Specific Alignment, Anatomy, Recovery and Outcome in Total Knee Arthroplasty

Total knee arthroplasty (TKA), despite being an otherwise highly successful medical operation, has a recurrent problem of dissatisfaction and recurrent pain rates in the 15-20% range. A variety of factors contribute to this incidence of dissatisfaction which can broadly be considered to fall into one of three groups: factors driven by the surgical outcome, pre-existing factors relating to the patients psychology, appropriateness for surgery or expectation level, and factors driven by the patient’s recovery and their management during that recovery process. With consideration to the extensive variation between patients, it is reasonable to posit that addressing patient specific factors in selection for surgery, alignment of components during surgery and post-operative management may reduce the instance of post-operative dissatisfaction. The first goal of this thesis was to understand the variation of patient anatomy as it relates to standard practice in TKA. Following the finding of extensive variation, a bio-mechanical rigid body dynamics simulation of the knee joint was developed to determine the degree to which this variation was reflected in the kinematic behaviour of the implanted knees. Later studies showed extensive kinematic variation that was responsive to variation in the alignment of the components as well as well as significantly related to patient reported outcome. Later studies further investigated how outcome related to patient selection for surgery and recovery of the patient as measured with simple activity monitoring. From this work, a pre-operative simulation assessment tool has been developed, the Dynamic Knee Score (DKS), and paired with selection and recovery management tools forms the basis of 360 Knee Systems surgical planning and patient management, which has been used in over 3,000 primary TKA’s to date

Development and Implementation of a Computational Modeling Tool for Evaluation of THA Component Position

The human body is a complicated structure with muscles, ligaments, bones, and joints. Modeling human body with computational tools are becoming a trend [1]. More importantly, using computational tools to evaluate human body is a non-invasive technique that could help surgeons and researchers evaluate implant products [2]. Therefore, the development of a model which can analyze both implant sizing suggestion and kinematics of subject specific data could prove valuable. For total hip arthroplasty, one common complication is in vivo separation and dislocation of the femoral head within the acetabular cup [3] [4]. Developing a successful computational tool to address this issue includes developing a dynamic model of hip joint, implementing implant sizing suggestion algorithms and computing component alignments. Due to advancement in technology, the current focus has been to develop patient-specific solutions, a combined program of both hip model and implant suggestion model has been developed. In this dissertation, the primary objective is to develop a fully functional hip analysis software that not only can suggestion and template the implant sizing and position, but the software can also utilize the patient specific data to run simulation with different activities. The second objective of this dissertation is to conduct hip analysis studies using hip analysis software. Overall, the results in this dissertation discuss the effect of different stem positions and surgeon preferences on the outcome of the Total Hip Arthroplasty

An Improved Polynomial Chaos Expansion Based Response Surface Method And Its Applications On Frame And Spring Engineering Based Structures

In engineering fields, computational models provide a tool that can simulate a real world response and enhance our understanding of physical phenomenas. However, such models are often computationally expensive with multiple sources of uncertainty related to the model’s input/assumptions. For example, the literature indicates that ligament’s material properties and its insertion site locations have a significant effect on the performance of knee joint models, which makes addressing uncertainty related to them a crucial step to make the computational model more representative of reality. However, previous sensitivity studies were limited due to the computational expense of the models. The high computational expense of sensitivity analysis can be addressed by performing the analysis with a reduced number of model runs or by creating an inexpensive surrogate model. Both approaches are addressed in this work by the use of Polynomial chaos expansion (PCE)-based surrogate models and design of experiments (DoE). Therefore, the objectives of this dissertation were: 1- provide guidelines for the use of PCE-based models and investigate their efficiency in case of non-linear problems. 2- utilize PCE and DoE-based tools to introduce efficient sensitivity analysis approaches to the field of knee mechanics. To achieve these objectives, a frame structure was used for the first aim, and a rigid body computational model for two knee specimens was used for the second aim. Our results showed that, for PCE-based surrogate models, once the recommended number of samples is used, increasing the PCE order produced more accurate surrogate models. This conclusion was reflected in the R2 values realized for three highly non-linear functions ( 0.9998, 0.9996 and 0.9125, respectively). Our results also showed that the use of PCE and DoE-based sensitivity analyses resulted in practically identical results with significant savings in the computational cost of sensitivity analysis when compared to a traditional quasi-Monte Carlo (MC) approach (95% and 98% reductions in model evaluations for analyses with 10 and 6 uncertain variables, respectively). Finally, the use of D-optimal DoE resulted in a reduction in the number of samples required to perform sensitivity analysis by 64.4%, which reduced the computational burden by 1018 hours