CAD-Based Porous Scaffold Design of Intervertebral Discs in Tissue Engineering

With the development and maturity of three-dimensional (3D) printing technology over the past decade, 3D printing has been widely investigated and applied in the field of tissue engineering to repair damaged tissues or organs, such as muscles, skin, and bones, Although a number of automated fabrication methods have been developed to create superior bio-scaffolds with specific surface properties and porosity, the major challenges still focus on how to fabricate 3D natural biodegradable scaffolds that have tailor properties such as intricate architecture, porosity, and interconnectivity in order to provide the needed structural integrity, strength, transport, and ideal microenvironment for cell- and tissue-growth. In this dissertation, a robust pipeline of fabricating bio-functional porous scaffolds of intervertebral discs based on different innovative porous design methodologies is illustrated. Firstly, a triply periodic minimal surface (TPMS) based parameterization method, which has overcome the integrity problem of traditional TPMS method, is presented in Chapter 3. Then, an implicit surface modeling (ISM) approach using tetrahedral implicit surface (TIS) is demonstrated and compared with the TPMS method in Chapter 4. In Chapter 5, we present an advanced porous design method with higher flexibility using anisotropic radial basis function (ARBF) and volumetric meshes. Based on all these advanced porous design methods, the 3D model of a bio-functional porous intervertebral disc scaffold can be easily designed and its physical model can also be manufactured through 3D printing. However, due to the unique shape of each intervertebral disc and the intricate topological relationship between the intervertebral discs and the spine, the accurate localization and segmentation of dysfunctional discs are regarded as another obstacle to fabricating porous 3D disc models. To that end, we discuss in Chapter 6 a segmentation technique of intervertebral discs from CT-scanned medical images by using deep convolutional neural networks. Additionally, some examples of applying different porous designs on the segmented intervertebral disc models are demonstrated in Chapter 6

High Fidelity Bioelectric Modelling of the Implanted Cochlea

Cochlear implants are medical devices that can restore sound perception in individuals with sensorineural hearing loss (SHL). Since their inception, improvements in performance have largely been driven by advances in signal processing, but progress has plateaued for almost a decade. This suggests that there is a bottleneck at the electrode-tissue interface, which is responsible for enacting the biophysical changes that govern neuronal recruitment. Understanding this interface is difficult because the cochlea is small, intricate, and difficult to access. As such, researchers have turned to modelling techniques to provide new insights. The state-of-the-art involves calculating the electric field using a volume conduction model of the implanted cochlea and coupling it with a neural excitation model to predict the response. However, many models are unable to predict patient outcomes consistently. This thesis aims to improve the reliability of these models by creating high fidelity reconstructions of the inner ear and critically assessing the validity of the underlying and hitherto untested assumptions. Regarding boundary conditions, the evidence suggests that the unmodelled monopolar return path should be accounted for, perhaps by applying a voltage offset at a boundary surface. Regarding vasculature, the models show that large modiolar vessels like the vein of the scala tympani have a strong local effect near the stimulating electrode. Finally, it appears that the oft-cited quasi-static assumption is not valid due to the high permittivity of neural tissue. It is hoped that the study improves the trustworthiness of all bioelectric models of the cochlea, either by validating the claims of existing models, or by prompting improvements in future work. Developing our understanding of the underlying physics will pave the way for advancing future electrode array designs as well as patient-specific simulations, ultimately improving the quality of life for those with SHL

Finite Element-Based Machine Learning Model for Predicting the Mechanical Properties of Composite Hydrogels

In this study, a finite element (FE)-based machine learning model was developed to predict the mechanical properties of bioglass (BG)-collagen (COL) composite hydrogels. Based on the experimental observation of BG-COL composite hydrogels with scanning electron microscope, 2000 microstructural images with randomly distributed BG particles were created. The BG particles have diameters ranging from 0.5 μm to 1.5 μm and a volume fraction from 17% to 59%. FE simulations of tensile testing were performed for calculating the Young’s modulus and Poisson’s ratio of 2000 microstructures. The microstructural images and the calculated Young’s modulus and Poisson’s ratio by FE simulation were used for training and testing a convolutional neural network regression model. Results showed that the network developed in this work can effectively predict the mechanical properties of the composite hydrogels. The R-squared values were 95% and 83% for Young’s modulus and Poisson’s ratio, respectively. This work provides a surrogate model of finite element analysis to predict mechanical properties of BG-COL hydrogel using microstructure images, which could be further utilized for characterizing heterogeneous materials in big data-driven material designs

Numerical modelling of additive manufacturing process for stainless steel tension testing samples

Nowadays additive manufacturing (AM) technologies including 3D printing grow rapidly and they are expected to replace conventional subtractive manufacturing technologies to some extents. During a selective laser melting (SLM) process as one of popular AM technologies for metals, large amount of heats is required to melt metal powders, and this leads to distortions and/or shrinkages of additively manufactured parts. It is useful to predict the 3D printed parts to control unwanted distortions and shrinkages before their 3D printing. This study develops a two-phase numerical modelling and simulation process of AM process for 17-4PH stainless steel and it considers the importance of post-processing and the need for calibration to achieve a high-quality printing at the end. By using this proposed AM modelling and simulation process, optimal process parameters, material properties, and topology can be obtained to ensure a part 3D printed successfully

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

Validation of Subject Specific Computed Tomography-based Finite Element Models of the Human Proximal Tibia using Full-field Experimental Displacement Measurements from Digital Volume Correlation

Quantitative computed tomography-based finite element (QCT-FE) modeling is a computational tool for predicting bone’s response to applied load, and is used by musculoskeletal researchers to better understand bone mechanics and their role in joint health. Decisions made at the modeling stage, such as the method for assigning material properties, can dictate model accuracy. Predictions of surface strains/stiffness from QCT-FE models of the proximal tibia have been validated against experiment, yet it is unclear whether these models accurately predict internal bone mechanics (displacement). Digital volume correlation (DVC) can measure internal bone displacements and has been used to validate FE models of bone; though, its use has been limited to small specimens. The objectives of this study were to 1) establish a methodology for high-resolution peripheral QCT (HR-pQCT) scan acquisition and image processing resulting in low DVC displacement measurement error in long human bones, and 2) apply different density-modulus relationships and material models from the literature to QCT-FE models of the proximal tibia and identify those approaches which best predicted experimentally measured internal bone displacements and related external reaction forces, with highest explained variance and least error. Using a modified protocol for HR-pQCT, DVC displacement errors for large scan volumes were less than 19μm (0.5 voxels). Specific trabecular and cortical models from the literature were identified which resulted in the most accurate QCT-FE predictions of internal displacements (RMSE%=3.9%, R2>0.98) and reaction forces (RMSE%=12.2%, R2=0.78). This study is the first study to quantify experimental displacements inside a long human bone using DVC. It is also the first study to assess the accuracy of QCT-FE predicted internal displacements in the tibia. Our results indicate that QCT-FE models of the tibia offer reasonably accurate predictions of internal bone displacements and reaction forces for use in studying bone mechanics and joint health

Qualitative effect of tissue heterogeneity and modiolus porosity on the transmembrane potential of type-1 spiral ganglion neurons in the human cochlea: a simulation study

Electric stimulation of auditory nerve by cochlear implants has been a successful clinical intervention to treat the sensorineural deafness. However, various micro-anatomical factors have not been considered in the state of the art models while studying the interaction between the applied electric field and the auditory nerve. The present finite element modeling study suggests that the modiolus porosity and tissue heterogeneity significantly alter the electric field distribution in the Rosenthal’s canal and thereby affect the cochlear implant functionality

Pluripotency state affects the mechanical phenotype of the embryonic stem cell nucleus

PhDThe thesis aims at investigating the connection between nucleus mechanical characteristics with pluripotency state and differentiation associated with altered cell gene expression levels. The project investigates the deformation characteristics of the cell nucleus during unconfined compression in a 3D cell-seeded agarose constructs. The studies report modification in the mechanical behaviour of the nucleus in different embryonic stem cell phenotypes based on various pluripotent states (naïve or primed states) or following triggering of early differentiation. A multi-scale model is also presented to simulate dynamic details of mechanical perturbation to cells during compression. The first chapter presents a review of the relevant literature to introduce current progress in the related research field and the second chapter describes the general methods used in the thesis including cell culture, agarose construct preparation, construct compression and microscopy recording. The third chapter presents findings of studies involving the application of compression to embryonic stem cells in naïve and primed sate within agarose scaffolds. A range of parameters relating to the relative cell/nucleus morphological modifications are recorded with analysis and discussion. Chapter four presents studies that investigate the early differentiation of embryonic stem cells from either the naïve and primed pluripotency, achieved by altering cell culture condition, and further reveals the nuclear mechanical characteristic changes. The fifth chapter describes a multi-scale model developed to simulating the 3D cell-seeded agarose compression reported in previous chapters. This model is also used to estimate cell mechanical parameters and show accurate deformation detail in different locations within the construct. A final discussion of the thesis is provided in chapter 6 with a plan for future work.China Scholarship Counci