Construction of Physics-based brain atlas and its application

Ph.DDOCTOR OF PHILOSOPH

On modelling the constitutive and damage behaviour of highly non-linear bio-composites - Mesh sensitivity of the viscoplastic-damage law computations

The large strain fracture of non-linear complex solids concerns a wide range of applications, such as material forming, food oral processing, surgical instrumental penetration as well as more recently, the design of biodegradable composites for packaging and bio-medical use. Although simulations are a powerful tool towards understanding and designing such processes, modelling ductile fracture in materials such as soft natural composites imposes a new challenge, particularly when the fracture patterns cannot be pre-defined. Here we bring to light new information on these aspects of benefit to the multidisciplinary community, by characterising and modelling the deformation and fracture of short cellulose fibre starch extruded composites. Hyperviscoelastic-Mullins damage laws show merits in modelling such complex systems. Yet they are inferior to a viscoplastic-damage law able to capture exactly their highly non-linear, rate dependent and pressure dependent pseudo-plastic stress-strain response. The viscoplastic-damage law also predicts fracture based on experimental toughness values without pre-specifying the crack path in a Finite Element (FE) model, displaying superiority over the conventional cohesive zone approach. Yet, despite using a toughness parameter to drive crack propagation, spurious mesh dependency is still observed while other previously unreported sources of error imposed by the finite element aspect ratio are also highlighted. The latter is rectified by developing a novel numerical strategy for calculating the characteristic element length used in the damage computations. Inherent mesh dependency suggests that non-local damage models may be essential to model this newly investigated class of natural composites

Determining the Biomechanical Behavior of the Liver Using Medical Image Analysis and Evolutionary Computation

Modeling the liver deformation forms the basis for the development of new clinical applications that improve the diagnosis, planning and guidance in liver surgery. However, the patient-specific modeling of this organ and its validation are still a challenge in Biomechanics. The reason is the difficulty to measure the mechanical response of the in vivo liver tissue. The current approach consist of performing minimally invasive or open surgery aimed at estimating the elastic constant of the proposed biomechanical models. This dissertation presents how the use of medical image analysis and evolutionary computation allows the characterization of the biomechanical behavior of the liver, avoiding the use of these minimally invasive techniques. In particular, the use of similarity coefficients commonly used in medical image analysis has permitted, on one hand, to estimate the patient-specific biomechanical model of the liver avoiding the invasive measurement of its mechanical response. On the other hand, these coefficients have also permitted to validate the proposed biomechanical models. Jaccard coefficient and Hausdorff distance have been used to validate the models proposed to simulate the behavior of ex vivo lamb livers, calculating the error between the volume of the experimentally deformed samples of the livers and the volume from biomechanical simulations of these deformations. These coefficients has provided information, such as the shape of the samples and the error distribution along their volume. For this reason, both coefficients have also been used to formulate a novel function, the Geometric Similarity Function (GSF). This function has permitted to establish a methodology to estimate the elastic constants of the models proposed for the human liver using evolutionary computation. Several optimization strategies, using GSF as cost function, have been developed aimed at estimating the patient-specific elastic constants of the biomechanical models proposed for the human liver. Finally, this methodology has been used to define and validate a biomechanical model proposed for an in vitro human liver.Martínez Martínez, F. (2014). Determining the Biomechanical Behavior of the Liver Using Medical Image Analysis and Evolutionary Computation [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39337TESI

Computational analysis of the remodeling in biological tissue

Aquest treball documenta una implementació d'un model de reorientació de fibres, o remodelació, a partir d'un material hiperelàstic anisòtrop. Es consideren dos models per a la deformació mecànica de les fibres: exponencial i Worm-Like Chain (WLC). El comportament de la fibra es va portar a una resposta a macroescala mitjançant l'enfocament de la microesfera. Les fibres estan incrustades en una matriu isotròpica modelada per una funció d'energia de deformació NeoHookean.Este trabajo documenta la implementación de un modelo de reorientación de fibras, o remodelado, sobre la base de un material hiperelástico anisotrópico. Se consideran dos modelos para la deformación mecánica de las fibras: exponencial y Worm-Like Chain (WLC). El comportamiento de la fibra se trasladó a una respuesta a macroescala mediante el enfoque de microesferas. Las fibras están incrustadas en una matriz isotrópica modelada por una función de energía de deformación neohookeana.This work documents an implementation of a fibre reorientation model, or remodelling, on the basis of an anisotropic hyperelastic material. Two models are considered for the mechanical deformation of the fibres: exponential and Worm-Like Chain (WLC). The fibre behaviour was carried along to a macro-scale response by the microsphere approach. The fibres are embedded in a isotropic matrix modelled by a NeoHookean strain energy function

Supramolecular assembly and mechanical properties of dermis

The present work is a part of a wider research project which aims at the in vitro tissues and biohybrid generation. The process of generating biological tissues requires benchmarks in order to define the optimal set of design and performance parameters for the tissue of interest. As a consequence of that, my efforts have been devoted to the study of natural tissue. In particular I have focused my attention to their composition, microstructure and macroscopic properties. The first part of the thesis reviews recent studies concerning the assembly and spatial arrangement of some biological macromolecules of interest, which compose the extracellular matrix. The extracellular matrix is indeed largely responsible for the macroscopic physical properties of connective tissues. Skin has been chosen as model of connective tissue to study. This choice is motivated by the fact that skin is a more general model rather then tendons, which are mainly subjected to uniaxal tension, and the osmosis-supported cartilage. An experimental campaign has been designed in order to gather information on dermal composition and structure, and how these characteristics can affect the macroscopic behaviour of the tissue. The results of this experimental campaign are shown in the second part of the work. At last two constitutive equations are presented. Both of them are developed within the framework of continuum mechanics. The first one is a full three dimensional model able to capture the elastic behaviour of dermis at large deformations. The second model is able to predict the viscoelastic behaviour. Both model accounts for the anisotropy of the native tissue and are structural model, since they contain parameters on the underlying histology. The development of these models provide noteworthy information on the performance of tissue-engineered constructs whose properties have been designed ab initio. In particular, since the mechanical properties of biohybrids can be on-line monitored during culturing in bioreactors. Thus constitutive models can provide cues on the evolution of the mechanical properties, giving the chance to investigate on the complex relationship between mechanical stimulus and tissue remodelling

A systematic study of Brain Tissue microstructure: from composition to biomechanics and modelling of White Matter

This thesis aims to shed light on the biomechanical knowledge of the brain, in particular of its white matter (WM). An extensive, multidisciplinary and bottom-up research has been carried out to understand its micromechanical response focusing on three areas: Corpus Callosum, Corona Radiata and Fornix. Axons and the surrounding matrix with its accessory cells, the two main components of the tissue, have been analysed via Focused Ion Beam Scanning Electron Microscopy (FIB-SEM). Tissue volumes have been sampled, stained, embedded and imaged to finally be 3D-reconstructed, appearing as unidirectional composite materials. They have been geometrically characterised, creating a location-specific database of: cross-sectional area, diameter, ellipticity and tortuosity of the axons, together with the volume fraction of the volumes. The AFM-enabled nanoindentations investigated the mechanical response of WM. Stress-relaxation experiments have been performed on samples with axons running either parallel or perpendicular to the testing plane. The tissue showed linear viscoelasticity and slight anisotropy at the investigated level. The perpendicular samples showed a higher initial stiffness than parallel samples while the relative change in stiffness after relaxation was higher for the parallel samples than for the perpendicular ones. Finally, micromechanical modelling of the areas was performed. Location-speci c Representative Volume Elements have been created with the geometrical info obtained via FIB-SEM. Via an inverse-modelling approach, using the AFM data, material parameters of the axons and the matrix, the tissue components, have been obtained. The predicted stress-relaxation curves simulated by the finite element analysis showed good agreement with the experimental curves. The acquired knowledge of the microenvironment is fundamental for a comprehensive microscopical characterisation of the white matter. It provides important information to reduce axonal damage during neurosurgery, by predicting the local mechanical response and planning accordingly, and to improve the efficacy and therapeutic reach of Convection Enhanced Delivery, by exploiting the cytoarchitecture, leading to minimal side effects and maximal efficacy of the treatments.Open Acces

Computational Modeling of the Cervical Spinal Cord: Integration into a Human Body Model to Investigate Response to Impact

Acute spinal cord injuries (SCI) have a global annual occurrence rate of 14 to 40 per million population with considerable societal cost. The primary mechanism of injury involves physical damage to the nervous tissues, such as spinal cord compression resulting from fracture or dislocation of the vertebra. However, experimental findings have indicated that neurological sequela can occur without radiographic abnormalities of the neural tissues. In addition, studies have suggested that the cerebrospinal fluid (CSF) layer may play a protective role for the spinal cord during impact. Yet, there are significant limitations to examining SCI experimentally, resulting in large gaps in understanding. Computational Human Body Models (HBM) are an alternative and potentially important tool to investigate the risk of SCI. A key challenge in applying contemporary HBM to study SCI is the need for a biofidelic model of the spinal cord, which accurately predicts the loading and response of the cervical neural tissues in relevant impact scenarios. This thesis developed and validated a finite element model of the cervical spinal cord and associated tissues and integrated this model within a contemporary HBM to achieve two aims: (1) to provide a tool for the assessment of spinal cord response in impact scenarios; and (2) to create an improved physical boundary condition for the brain and brain stem, which is a limitation of current HBM. The geometry of the cervical neural tissues was defined using subject-specific magnetic resonance imaging and literature data. The salient mechanical properties of cervical neural tissues were identified, and experimental data were used to fit appropriate constitutive material models for each tissue. Experimental pellet impact tests and indentation tests on the spinal cord were simulated to validate the tissue mechanical properties, verify finite element mesh refinement and assess numerical representation of the CSF. The developed material models and meshes of the cervical neural tissues were integrated into a contemporary HBM. Lastly, the contemporary HBM with implemented cervical neural tissues was simulated in frontal, lateral, rear, and oblique impact scenarios. A comprehensive assessment of the spinal cord influence on brain tissue deformation was undertaken. In general, the presence of the spinal cord in the HBM model increased the strains observed in the brain tissue. The brain stem tissue observed the largest average increase of 17% in strain. Results from this work provided the first validated finite element model of the cervical neural tissues and cerebrospinal fluid layer integrated into a state-of-the-art full-body HBM for transient impact simulations. This model enabled the prediction of spinal cord response for impact scenarios, improved anatomic boundary conditions for connection to the brain tissue, and ultimately will assist in assessing safety systems to mitigate catastrophic human injuries

THE INFLUENCE OF ANISOTROPY AND HETEROGENEITY ON THE MECHANICS OF MILD TRAUMATIC BRAIN INJURY

Traumatic Brain Injury (TBI) has been intensively studied for several decades. Much attention has been directed towards mild TBI (mTBI) due to the increased rates of occurrence compared to other types of TBI especially in military and sports. There are two general approaches to study mTBI: computational and experimental, and each approach complements the other. The experimental direction provides observations of injury as well as the necessary material behavior for the computational models, while the computational models can simulate injury-inducing events which cannot be performed experimentally (in humans). In this work, we use the computational approach to examine how heterogeneities in the human brain affect the mechanical response and/or the deformation of the brain tissue in mTBI. We focus on white matter, the vasculature network and gray matter. Constitutive models for white matter have evolved from linear elastic to isotropic hyperelastic and finally to transversely isotropic hyperelastic material. Although experimental evidence points to anisotropy of white matter in both tension and shear, prior models have accounted for anisotropy in tension but not in shear. We investigate the effects of shear anisotropy in mTBI by comparing two models: one that captures anisotropy in both tension and shear to another model that captures only tension anisotropy. With respect to vasculature, there is very limited literature that studies the effects of the vasculature on the mechanics of mTBI. In this work, we build two models (with and without vasculature) to investigate vasculature effects on the likelihood of injury. Finally, we investigate the effects of gray matter heterogeneity by building two models, one with homogeneous gray matter and another with heterogeneous gray matter. To our knowledge, the effect of gray matter heterogeneity has not been investigated in computational models although recent experiments provide evidence of heterogeneity in gray matter. Since the most commonly used injury criteria in recent literature are strain-based, we compare the strains predicted by the two models to address the main questions we raised about heterogeneity (how white matter shear anisotropy, vasculature network and gray matter heterogeneity affect the mechanics of mTBI). Our results show that two heterogeneity sources, white matter shear anisotropy and the vasculature, significantly influence the brain deformation and subsequently the predicted injury

Soft Embedded Sensors with Learning-based Calibration for Soft Robotics

In this thesis, a new class of soft embedded sensors was conceptualized and three novel sensors were designed, fabricated, and tested for small force range soft robotic applications. The proposed soft sensors were consisted of a gelatin-graphite composite with piezoresistive characteristics. Principally, the sensing elements of the proposed class of soft sensors were moldable into any shape and size; thus, were embeddable and scalable. The sensing elements were directly molded into soft flexural structures so as to be embedded in the flexures. For each sensor, first a mechano-electrical phenomenological model for the exhibited piezoresistivity was proposed and validated experimentally. Afterwards, the sensors were subjected to a series of external forces to obtain calibration data. Given the complexity of the piezoresistivity and intrinsic large deformation of the soft bodies and sensing element, learning-based calibration approach were investigated. To compensate for ratedependency and hysteresis effects on sensor readings in calibration, rate-dependent features were selected for learning-based calibrations. Consequently, the first sensor of this research, i.e., one degree-of-freedom (1-DoF) force sensor, exhibited a force range of 0.035-0.82 N force measurement range with a mean-absolute-error (MAE) of 3.7% and a resolution of 4% of full-range. The second sensor, i.e., 3-DoF had a measurement range of up to 0.3 N with an MAE of 0.005 N and a resolution of 0.003 N. The third sensor, 6-DoF force-torque sensor, had a force range of up to 110 mN with an MAE of 7.4±6.5 mN and resolution of 1 mN and a torque range of 6.8 mNm with an MAE of 0.24 mNm. Comparison with the state-of-the-art and functional requirements of intraluminal procedures showed that the the proposed sensors were fairly compatible with the requirement and showed improvement of the state of the art. The major contribution of this research was to propose a scalable sensing principle that could adapt its shape to the shape of the host body, e.g., flexural robots. Moreover, this research showed nonlinear learning-based calibration is a fitting solution to overcome limitations of the state-of-the-art in using soft elastomeric sensors

Assessment of head injury risk caused by impact using finite element models

[ES] Las cargas de impacto son la fuente primaria de lesiones en la cabeza y pueden resultar en un rango de traumatismo desde leve hasta severo. Debido a la existencia de múltiples entornos en los que se pueden desencadenar lesiones por impacto (accidentes automovilísticos, deportes, caídas accidentales, violencia), éstas pueden afectar potencialmente a toda la población independientemente de su estado de salud. Pese al creciente esfuerzo en investigación para comprender la biomecánica de las lesiones por traumatismo en la cabeza, todavía no es del todo posible realizar predicciones precisas ni prevenir estos eventos. En esta Tesis, se han estudiado algunos aspectos del comportamiento ante impacto de los diferentes tejidos biológicos involucrados mediante el desarrollo de un modelo numérico de cabeza humana a partir de imágenes de tomografía computerizada (TAC). Se han realizado simulaciones en elementos finitos (EF) de ensayos experimentales de la literatura con el fin de validar el modelo numérico desarrollado, estableciendo unas propiedades mecánicas adecuadas para cada uno de sus constituyentes. De esta manera se puede adquirir una predicción adecuada del riesgo de sufrir daños. Parte de esta Tesis se centra en el entorno balístico, específicamente en cascos de combate antibalas, los cuales son susceptibles de causar traumatismo craneoencefálico debido a la elevada deformación que sufren durante el impacto. Previamente al estudio de estos fenómenos de alta velocidad, se han realizado ensayos experimentales y numéricos para caracterizar la respuesta mecánica de algunos materiales compuestos ante impacto de baja velocidad. Al principio de esta Tesis se ha realizado una revisión del estado del arte acerca de los criterios existentes para cuantificar el trauma craneoencefálico.Este es un aspecto clave para las simulaciones numéricas, ya que la idoneidad de algunos de estos criterios para la predicción de lesiones cerebrales todavía es un debate abierto. Mediante EF se han realizado simulaciones de impactos balísticos en una cabeza protegida con un casco de combate. Mediante la posterior aplicación de diferentes criterios de daño sobre los resultados obtenidos se ha evaluado el nivel de protección que aseguran los protocolos de aceptación de cascos de combate, así como las estrategias para determinar su tallaje. Se ha demostrado que las normativas existentes para cascos de combate son capaces de mitigar algunos mecanismos de trauma pero no logran prevenir otros como los gradientes de presión intracraneales. Además, se ha demostrado que algunas de las estrategias de tallaje más comúnmente adoptadas por los fabricantes, como producir un solo tamaño de calota, deberían ser reconsideradas ya que existe un mayor riesgo de traumatismo cuando la distancia entre la cabeza y la calota del casco no es suficiente. Siguiendo la línea de protecciones personales, algunos de los materiales compuestos comúnmente empleados en la industria armamentística se han combinado para crear distintas configuraciones de calota para optimizar la relación entre peso del casco y protección para la cabeza. Materiales ligeros como el UHMWPE han resultado en un comportamiento menos eficiente que el de los apilados de tejido de aramida a la hora de limitar la BFD (deformación máxima en la calota del casco en la zona de impacto). Hacia el final de la Tesis se presenta un modelo numérico de cabeza humana detallado, que incluye treinta y tres de las estructuras anatómicas principales. Dicho modelo se ha desarrollado para la simulación de un accidente ecuestre en el que aparecen múltiples lesiones craneoencefálicas. Principalmente, se pretende establecer un criterio mecánico para predecir el hematoma subdural (HS) basado en la ruptura de los vasos sanguíneos intracraneales. Se ha propuesto un valor umbral de ruptura en tensiones de 3.5 MPa, pero tanto este límite como la localización del vaso dañado son altamen[CA] Les càrregues d'impacte son la font primària de lesions al cap i poden resultar en un rang de severitat des de lleu a greu. Degut als múltiples entorns en que poden desencadenar-se lesions per impacte (accidents automobilístics, esports, caigudes accidentals, violència), aquestes poden afectar potencialment a tota la població independentment del seu estat de salut. Malgrat el creixent esforç en investigació per comprendre la biomecànica de les lesions per traumatisme al cap, encara no és del tot possible realitzar prediccions precises ni prevenir aquestos esdeveniments. En aquesta Tesi, s'han estudiat alguns aspectes del comportament a impacte dels diferents teixits biològics involucrats mitjançant el desenvolupament d'un model numèric de cap humà a partir d'imatges de tomografia computeritzada (TAC). S'han realitzat simulacions en elements finits (EF) d'assajos experimentals de la literatura amb la finalitat de validar el model numèric desenvolupat, establint unes propietats mecàniques adequades per a cadascun dels seus constituents. D'aquesta manera es pot aconseguir una predicció del risc de sofrir danys traumàtics. Part d'aquesta Tesi es centra en l'entorn balístic, específicament en cascs de combat antibales, els quals són susceptibles de causar traumatisme degut a l'elevada deformació que sofrixen durant l'impacte. Previament a l'estudi d'aquests fenòmens d'alta velocitat, s'han realitzat assajos experimentals i numèrics per a caracteritzar la resposta mecànica d'alguns materials compostos en condicions d'impacte a baixa velocitat. Al començament d'aquesta Tesi s'ha realitzat una revisió de l'estat de l'art sobre els criteris existents per quantificar el trauma cranioencefàlic. Aquest és un aspecte clau per a les simulacions numèriques, ja que l'utilitat d'alguns d'aquestos criteris per a la predicció de lesions cerebrals és encara un debat obert. Mitjançant EF s'han realitzat simulacions numèriques d'impactes balístics en un cap protegit amb un casc de combat. Gràcies a la posterior aplicació de diferents criteris de dany sobre els resultats obtinguts s'ha evaluat el nivell de protecció que asseguren els protocols d'acceptació de cascs de combat, així com les estratègies per a determinar les seues talles. S'ha demostrat que les normatives existents són capaces de mitigar alguns mecanismes de trauma però no aconseguixen prevenir altres com els gradients de pressions intracranials. A més, s'ha demostrat que algunes estratègies per determinar les talles més comunament adoptades pels fabricants (com produir només un tamany de calota i adaptar el gruix de les escumes interiors a les diferents dimensions dels subjectes) haurien de ser reconsiderades ja que existeix un major risc de traumatisme quan la distància entre el cap i la calota del casc no és suficient. Seguint la línia de proteccions personals, alguns dels materials compostos comunament utilitzats en la indústria de l'armament s'han combinat per a crear distintes possibles configuracions de calota amb la finalitat d'optimitzar la relació entre pes i protecció. Materials lleugers com l'UHMWPE han resultat en un comportament menys eficient que el d'apilats de teixit d'aramida a l'hora de limitar la BFD (deformació màxima a la calota del casc a la zona d'impacte). Cap al final de la Tesi es presenta un model numèric detallat de cap humà, que inclou trenta-tres de les estructures anatòmiques principals. Aquest model s'ha desenvolupat per a la simulació d'un accident eqüestre en el qual apareixen múltiples lesions cranioencefàliques. Principalment, es pretén establir un criteri mecànic per a la predicció de l'hematoma subdural (HS) basat en la ruptura dels vasos sanguinis intracranials. S'ha proposat un valor umbral de ruptura en tensions de 3.5 MPa, pero tant aquest límit com la ubicació del vas danyat són altament dependents de l'anatomia específica de cada subjecte.[EN] Impact loading is the primary source of head injuries and can result in a range of trauma from mild to severe. Because of the multiple environments in which impact-related injuries can take place (automotive accidents, sports, accidental falls, violence), they can potentially affect the entire population regardless of their health conditions. Despite the increasing research effort on the understanding of head impact biomechanics, accurate prediction and prevention of traumatic injuries has not been completely achieved. In this Thesis, some aspects of the impact behaviour of the different biological tissues involved have been analysed through the development of a numerical human head model from Computed Tomography (CT) images. FE simulations of experimental tests from the literature have been performed and enhanced the validation of the head model through the establishment of proper material laws for its constituents, which enable adequate prediction of injury risks. Part of this Thesis focuses on the ballistic environment, especifically in bulletproof composite helmets, which are susceptible to cause blunt injuries to the head because of their large deformation during impact. Prior to the study of these high-speed impacts, experimental tests and finite element (FE) models have been performed to characterise the mechanical response of composite materials subjected to low velocity impact. The implementation of a continuum damage mechanics approach coupled to a Hashin failure criterion and surface-to-surface cohesive relations to the numerical model provided a good matching with the impact behaviour obtained experimentally, capturing the principal damage mechanisms. A review of the head injury criteria currently available in the literature has been performed at the beginning of this Thesis. This is a key issue for the numerical simulations, as the suitability of some criteria to predict head injuries is still an open question. Numerical simulation of ballistic impacts on a human head protected with a combat helmet has been conducted employing explicit FE analysis. The level of protection ensured by helmet acceptance protocols as well as their sizing strategies have been studied and discussed by means of the application of different mechanical-based head injury criteria. It has been demonstrated that current helmet testing standards do mitigate some specific forms of head trauma but fail to prevent other injury mechanisms such as the intracranial pressure gradients within the skull. Furthermore, it has been demonstrated that some well-established helmet sizing policies like manufacturing one single composite shell and adapting the thickness of the interior pads to the different head dimensions should be reconsidered, as there is a great risk of head injury when the distance between the head and the helmet shell (stand-off distance) is not sufficient. Following the line of personal protections, some composite materials commonly employed in the soft body armour industry have been combined into different helmet shells configurations to optimise the ratio of weight-to-head protection. Light materials like UHMWPE appear to be less efficient than integral woven-aramid lay-ups in the limitation of the backface deformation (BFD), the maximum deformation sustained by the helmet at the impact site. A detailed head numerical model including thirty-three of its main anatomical structures has been developed for the simulation of an equestrian accident that resulted in many head injuries. Above all, the establishment of a mechanical criterion for the prediction of subdural hematona (SDH) based on the rupture of the head blood vessels is intended. A stress threshold for vein rupture has been set on 3.5 MPa, but both this limit and the location of vessel failure are highly dependent on the specific anatomy of the subject's vascularity.Palomar Toledano, M. (2019). Assessment of head injury risk caused by impact using finite element models [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/135254TESI