Multi-objective design optimization of a mobile-bearing total disc arthroplasty considering spinal kinematics, facet joint loads, and metal-on-polyethylene contact mechanics

Total disc arthroplasty (TDA) is a motion-preserving surgical technique used to treat spinal disorders, when more conservative medical therapies fail. Unfortunately, a high incidence of revision surgery exists due to postoperative complications including abnormal kinematics, facet joint arthritis, and implant failures. However, TDA is still an attractive option, since an optimally designed artificial disc is expected to reproduce native segmental biomechanics. Correspondingly, it would mitigate the development of adjacent segment diseases (a major concern of spinal fusion) caused by altered segmental biomechanics. Design optimization is a process of finding the best design parameters for a component/system to satisfy one/multiple design requirements using optimization algorithms. The shape of a candidate design is parametrized using computer-aided design, such that design parameters are manipulated to minimize one/multiple objective functions subject to performance constraints and design space bounds. Optimization algorithms typically require the gradients of the objective/constraint functions with respect to each design variable. In the traditional design optimization, due to the high computational cost to calculate the gradients by performing finite element analysis in each optimization iteration, it often results in a slow process to seek the optimal solution. To address the problem, an artificial neural network (ANN) was implemented to derive the analytical expressions of the objective/constraint function and their gradients. By incorporating analytical gradients, we successfully developed a multiobjective optimization (MOO) framework considering three performance metrics simultaneously. Furthermore, a new mobile-bearing TDA design concept featuring a biconcave polyethylene (PE) core was proposed, to strengthen the PE rim, where a high risk of fracture exists. It was hypothesized that there is a trade-off relationship among postoperative performance metrics in terms of spinal kinematics, facet joint loading, and metal-on-polyethylene contact mechanics. We tested this hypothesis by refining the new TDA to match normal segmental biomechanics and alleviate PE core stress. After performing MOO, the best-trade-off TDA design was determined by the solved three-dimensional Pareto frontier. The novel MOO framework can be also used to improve existing TDA designs, as well as to push the cutting edge of surgical techniques for the treatment of spinal disorders

Whole body vibration in the defence maritime environment: analysis and simulation of vertebral cancellous bone

Whole-body vibration has been shown to increase the risk of low back pain, especially during extreme exposures such as on marine craft which can reach peak loads comparable to ejection seats at 20G during “slamming”. Wedge fractures and trabecular damage of vertebrae have been noted at these high acceleration events. There is a need of a quantitative link between whole-body vibration and spinal damage, with possible tools for prediction. There is currently little known about the role trabecular damage plays under damage from Whole-body vibration. Developing a fatigue model was done in four steps: Fatigue testing of porcine vertebral cores; validation of a novel element material method; fatigue simulation of a porcine core to select the failure method; prediction using the validated material mapping model with the best failure method on human vertebral cubes. The fatigue tests were carried out on porcine trabecular cores loaded at 2Hz with varying normalised stress values until fatigue failure. Signal analysis was used to examine the vibrational statistics as per ISO 2631-1. This was done to both compare the statistical approaches used in measuring vibration and quantifying a link with in-vivo damage. VDVexp was found to be the best predictor of failure within these tests. Its 4th order averaging accounted for minute differences in acceleration that RMS could not, even at the low frequency tested. Fatigue of porcine bone has not been extensively examined in the literature and results from this chapter indicate that there are significant differences in its fatigue behaviour. Currently there is a need to calibrate the material models used in finite element simulations to achieve parity with experimental testing. In the next chapter a novel greyscale mapping technique which does not require calibration was validated. This was done on human trabecular cores taken at different orientations, with both experimental and finite element simulations. With these ii tissue material properties the simulations showed good agreement in terms of mechanical response in all three directions. Fatigue was calculated using finite element analysis on a porcine core which was validated against the experimental results. Three methods were tested for this: A stress based model which varies failure in respect to the load step; a model which calculates failure by the specific element stress and a strain model which fails elements based upon total element strain. This was conducted using a direct iterative approach using linear isotropic material properties with failure calculated after each load step, keeping down computational costs. All methods took roughly the same amount of time for a load step. Failure was predicted much sooner in comparison to the experimental with the specific element stress and strain models. The method which varies failure based on cycle count was selected as it was the most accurate. As porcine fatigue testing has not been-LANCEREAU examined the results were difficult to compare and differed from previous experiments on human and bovine tissues. Using the validated material model and the best performing fatigue method this was then applied to Human trabecular specimens to estimate the fatigue life. The cubes were then loaded in the main physiological direction from in-vivo loading. This predicted most of the expected mechanical behaviour during fatigue including a linear relationship between damage fraction and modulus reduction. It also highlights the importance of angular orientation in regards to trabecular fatigue life. Although it tended to underestimate the fatigue life of bone, it was in good agreement with the literature over the normalised stress range tested. The differences in simulated fatigue behaviour and the literature, seen previously with porcine tissue, were not apparent here. With further study and validation this model has the potential to improve the understanding of human fatigu

Image-based biomechanical models of the musculoskeletal system

Finite element modeling is a precious tool for the investigation of the biomechanics of the musculoskeletal system. A key element for the development of anatomically accurate, state-of-the art finite element models is medical imaging. Indeed, the workflow for the generation of a finite element model includes steps which require the availability of medical images of the subject of interest: segmentation, which is the assignment of each voxel of the images to a specific material such as bone and cartilage, allowing for a three-dimensional reconstruction of the anatomy; meshing, which is the creation of the computational mesh necessary for the approximation of the equations describing the physics of the problem; assignment of the material properties to the various parts of the model, which can be estimated for example from quantitative computed tomography for the bone tissue and with other techniques (elastography, T1rho, and T2 mapping from magnetic resonance imaging) for soft tissues. This paper presents a brief overview of the techniques used for image segmentation, meshing, and assessing the mechanical properties of biological tissues, with focus on finite element models of the musculoskeletal system. Both consolidated methods and recent advances such as those based on artificial intelligence are described

A shape analysis approach to prediction of bone stiffness using FEXI

The preferred method of assessing the risk of an osteoporosis related fracture is currently a measure of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA). However, other factors contribute to the overall risk of fracture, including anatomical geometry and the spatial distribution of bone. Finite element analysis can be performed in both two and three dimensions, and predicts the deformation or induced stress when a load is applied to a structure (such as a bone) of defined material composition and shape. The simulation of a mechanical compression test provides a measure of whole bone stiffness (N mm−1). A simulation system was developed to study the sensitivity of BMD, 3D and 2D finite element analysis to variations in geometric parameters of a virtual proximal femur model. This study demonstrated that 3D FE and 2D FE (FEXI) were significantly more sensitive to the anatomical shape and composition of the proximal femur than conventional BMD. The simulation approach helped to analyse and understand how variations in geometric parameters affect the stiffness and hence strength of a bone susceptible to osteoporotic fracture. Originally, the FEXI technique modelled the femur as a thin plate model of an assumed constant depth for finite element analysis (FEA). A better prediction of tissue depth across the bone, based on its geometry, was required to provide a more accurate model for FEA. A shape template was developed for the proximal femur to provide this information for the 3D FE analysis. Geometric morphometric techniques were used to procure and analyse shape information from a set of CT scans of excised human femora. Generalized Procrustes Analysis and Thin Plate Splines were employed to analyse the data and generate a shape template for the proximal femur. 2D Offset and Depth maps generated from the training set data were then combined to model the three-dimensional shape of the bone. The template was used to predict the three-dimensional bone shape from a 2D image of the proximal femur procured through a DXA scan. The error in the predicted 3D shape was measured as the difference in predicted and actual depths at each pixel. The mean error in predicted depths was found to be 1.7mm compared to an average bone depth of 34mm. 3D FEXI analysis on the predicted 3D bone along with 2D FEXI for a stance loading condition and BMD measurement were performed based on 2D radiographic projections of the CT scans and compared to bone stiffness results obtained from finite element analysis of the original 3D CT scans. 3D FEXI provided a significantly higher correlation (R2 = 0.85) with conventional CT derived 3D finite element analysis than achieved with both BMD (R2 = 0.52) and 2D FEXI (R2 = 0.44)

Fear avoidance beliefs are associated with reduced lumbar spine flexion during object lifting in pain-free adults

There is a long-held belief that physical activities such as lifting with a flexed spine is generally harmful for the back and can cause low back pain (LBP), potentially reinforcing fear avoidance beliefs underlying pain-related fear. In chronic LBP patients, pain-related fear has been shown to be associated with reduced lumbar range of motion during lifting, suggesting a protective response to pain. However, despite short term beneficial effects for tissue health, recent evidence suggests that maintaining a protective trunk movement strategy may also pose a risk for (persistent) LBP due to possible pro-nociceptive consequences of altered spinal motion, potentially leading to increased loading on lumbar tissues. Yet, it is unknown if similar protective movement strategies already exist in pain-free individuals which would yield potential insights into the role of fear avoidance beliefs in motor behavior in the absence of pain. Therefore, the aim of this study is to test whether fear avoidance beliefs influence spinal motion during lifting in a healthy cohort of pain-free adults without a history of chronic pain. The study subjects (N=57) filled out several pain-related fear questionnaires and were asked to perform a lifting task (5kg-box). High-resolution spinal kinematics were assessed using an optical motion capturing system. Time-sensitive analyses were performed based on statistical parametric mapping. The results demonstrated time-specific and negative relationships between self-report measures of pain-related fear and lumbar spine flexion angles during lifting, indicating potential unfavorable interactions between psychological factors and spinal motion during lifting in pain-free subjects

Methodology For Performing Whole Body Pmhs Underbody Blast Impact Testing, And The Corresponding Response Of The Hybrid Iii Dummy And The Finite Element Dummy Model Under Similar Loading Condition

In recent wars, the use of improvised explosive devices and landmines has dramatically increased as a tactical measure to counter armored vehicles. These weapons not only deform and damage the vehicle structure but also produce serious vertical deceleration injuries to mounted occupants. The reported injury patterns largely differ from those in an automotive crash and are often more severe than those in other vertical loading scenarios such as pilot seat ejection, helicopter crash, parachute landing and fall from height. High kinetic energy predominately along the principal vertical (Z-axis) over a short duration makes the underbody blast (UBB) loading conditions unique compared to other vertical and blunt impacts. With the lack of biomechanical response corridors (BRCs), the non-biofidelic nature of the automotive dummies to Z-axis loading and the lack of a finite element dummy model designed for vertical loading make it difficult to evaluate occupant response and develop mitigation strategies for UBB impact conditions. An introduction to the development of the BRCs this study provides a detailed methodology to perform whole body cadaver testing under a laboratory setup. Two whole body PMHS UBB impact tests were conducted using a sled system. An overview of pre-impact parameters such as bone mineral density, instrumentation technique, and vertical impulse generation is presented. Post-test CT scans, response data, and possible injury mechanisms were investigated. In addition, to PMHS testing, the responses of the Hybrid III dummy to short-duration large magnitude vertical acceleration in a laboratory setup were analyzed. Two unique test conditions were investigated using a horizontal sled system to simulate the UBB loading conditions. The biomechanical response in terms of the pelvis acceleration, chest acceleration, lumbar spine force, head accelerations and neck forces were measured during the tests. Subsequently, a series of finite element analyses (FEA) were performed to simulate the physical tests. The material parameters of various components as well as the mesh size were updated based on the high strain rate loading conditions obtained from Zhu et.al (2015) study. The correlation between the Hybrid III test and numerical model was evaluated using the CORA version 3.6.1. The Cora score for WSU FE model was determined to be 0.878 and 0.790 for loading conditions 1 and 2, respectively, in which 1.0 indicated a perfect correlation between the experiment and simulation response. The original LSTC model simulated under the current loading condition became numerically unstable after 12 ms. With repetitive vertical impacts, the Hybrid III dummy pelvis showed a significant increase in the peak acceleration accompanied by rupture of the pelvis foam and flesh. The revised WSU Hybrid III model indicated high stress concentrations at the same location where the pelvis foam and flesh in the actual ATD showed rupture. The stress contour under the ischial tuberosities in the finite element model provides a possible explanation for the material failure in the actual Hybrid III tests

VISCOELASTIC CHARACTERIZATION OF RABBIT NUCLEUS PULPOSUS TISSUE IN TORSIONAL CREEP

Recently, molecular therapy approaches have been shown to favorably alter the course of intervertebral disc degeneration (IDD) in a rabbit model. Typical experimental outcome measures for the rabbit model of IDD include MRI, x-ray, histology, and gene expression. Biomechanical function is another desirable parameter through which to compare treatments, although this is difficult due to limited availability of data for small animal models. In the current study, nucleus pulposus tissue was taken from the healthy rabbit intervertebral disc and tested in torsional creep to establish a database of healthy tissue behavior for future use in assessing the functional efficacy of molecular therapy treatments of IDD. Nucleus pulposus tissue was excised from the L5-L6 intervertebral disc, mounted between the cone and plate of an AR1000 Rheometer, and various torsional creep experiments were performed. Several creep models were fit to the data and modeling analyses were conducted. Of the models compared, the Andrade creep model provides the most reliable data extrapolation. It appears that the tissue is nonlinearly viscoelastic since it does not adhere to the Boltzmann superposition principle. A nonlinear viscoelastic constitutive model, derived for Andrade creep and used to predict the strain behavior obtained at higher levels of stress, provides consistent prediction results. The application of this model to degenerated rabbit NP tissue is expected to result in altered model parameters - thus providing quantifiable, functional benchmarks of success for molecular therapy approaches to the treatment of IDD

Machine Learning towards General Medical Image Segmentation

The quality of patient care associated with diagnostic radiology is proportionate to a physician\u27s workload. Segmentation is a fundamental limiting precursor to diagnostic and therapeutic procedures. Advances in machine learning aims to increase diagnostic efficiency to replace single applications with generalized algorithms. We approached segmentation as a multitask shape regression problem, simultaneously predicting coordinates on an object\u27s contour while jointly capturing global shape information. Shape regression models inherent point correlations to recover ambiguous boundaries not supported by clear edges and region homogeneity. Its capabilities was investigated using multi-output support vector regression (MSVR) on head and neck (HaN) CT images. Subsequently, we incorporated multiplane and multimodality spinal images and presented the first deep learning multiapplication framework for shape regression, the holistic multitask regression network (HMR-Net). MSVR and HMR-Net\u27s performance were comparable or superior to state-of-the-art algorithms. Multiapplication frameworks bridges any technical knowledge gaps and increases workflow efficiency