Mechanobiologische Optimierung von Gerüsten für große Knochendefekte

Bone has the remarkable capability to regenerate without forming any scar tissue upon a given injury. However, this intrinsic healing capacity can be impaired in some critical cases, such as large bone defects where a large piece of bone is missing. The current gold standard treatment for such defects is autologous bone grafting, where bone material is taken from another location in the patient and put into the defect to support it mechanically and biologically. Nevertheless, this treatment has several drawbacks, in particular the need for an additional surgery associated with donor site morbidities and a limited availability of bone material. An alternative treatment strategy is the use of 3D-printed bone scaffolds. Such implants are produced synthetically before the chirurgical intervention, can be made of metal, polymer or ceramic, and implanted into various defects to support their regeneration. However, how such scaffolds interact with the bone regeneration process has remained poorly understood so far, preventing scaffolds to become clinical routine practice in large bone defect treatment. In addition, scaffold design has mainly relied on trial-and-error approaches, requiring long, costly and ethically questionable experiments to assess the scaffold healing potential. This critical clinical issue was the starting point of this project. The aim of the thesis was therefore to propose an in silico methodology to design scaffolds for large bone defect regeneration that would be optimised for their ability to support the endogenous bone healing process. To do so, specific mechanisms of scaffold-supported large bone defect regeneration were investigated by means of a predictive computer model for bone regeneration. Next, the effect of individual scaffold design parameters were studied. In addition, the dynamics of the bone healing process was investigated by comparing healing outcome predictions at different healing time points. Lastly, a computational framework for bone scaffold optimisation was developed with the objective of maximising the amount of regenerated bone. The in silico investigation of scaffold-supported large bone defect regeneration used a coupled finite element analysis and agent-based model to simulate various experimental studies. The comparison between in silico predictions and experimental results revealed specific features of the regeneration process: (1) the lack of biological stimulation in large bone defects, that can be compensated by specific scaffold material or the addition of bone graft and (2) guidance provided by the scaffold surfaces on the cellular migration and tissue deposition processes. Specific scaffold designs were varied by changing the pore size, strut size or material properties. Overall, porous stiff scaffolds or more bulky softer scaffolds were found to be most beneficial for bone regeneration. However, precise pore or strut size recommendations depended largely on the underlying scaffold architecture, suggesting that a "one-fits-them-all" approach cannot be used to design optimal scaffolds. In addition, the modelling of different time horizons (initial mechanics and bone regeneration simulation) highlighted the dynamics of the bone regeneration process. Conclusions based on different time horizons contradicted each other: several scaffold designs seemed very favourable initially but were actually not predicted to support bone regeneration well. These observations emphasised the need for a dynamic optimisation process that would take the regeneration process into account. Lastly, a computational framework for bone scaffold design optimisation was developed. Its objective was defined as to maximise regenerated bone volume according to the mechanobiological bone regeneration model; scaffold designs were parametrised with a few variables (e.g. pore sizes or material properties). A surrogate optimisation approach was chosen to deal with the computationally demanding regeneration simulations: a simplified input-output relationship was derived from a set of initial simulations and used for the optimisation process to avoid too many demanding simulation runs. The results presented in the thesis proved the feasibility of the approach on a simplified cubic scaffold and a more realistic cylindrical scaffold. These results suggested that the initial design and its parametrisation should be carefully chosen to improve the optimisation outcome. Future work should further validate the computer model for scaffold-supported bone regeneration. A particular emphasis should be put on improving the computational efficiency of such models for their use in optimisation purposes. Next, more realistic, clinically-based scaffold designs should be employed in the optimisation framework, in combination with experiments. In that way, knowledge on scaffold healing potential and informed scaffold design for experiments could be improved iteratively.Knochen hat die bemerkenswerte Fähigkeit, sich nach einer Verletzung ohne Narbenbildung zu regenerieren. Allerdings kann diese inhärente Fähigkeit in bestimmten kritischen Fällen beeinträchtigt werden, zum Beispiel im Fall von großen Knochendefekten, bei denen ein großes Knochenstück fehlt. Die derzeitige Standardbehandlung für solche Defekte beinhaltet den Einsatz von autologem Knochenmaterial, wobei Knochenmaterial des Patienten aus einer defektfernen Stelle entnommen und in den Defekt implementiert wird, um ihn mechanisch und biologisch zu unterstützen. Diese Behandlungsmethode hat jedoch mehrere wesentliche Nachteile wie beispielsweise den zusätzlich erforderlichen chirurgischen Eingriff, der mit Morbidität an der Entnahmestelle verbunden ist, und die begrenzte Verfügbarkeit des Knochenmaterials. Eine alternative Behandlungsstrategie besteht darin, 3D-gedruckte Knochengerüste zu benutzen. Solche Implantate, bestehend aus Metall, Polymer oder Keramik, werden synthetisch vor dem chirurgischen Eingriff hergestellt und finden Anwendung in unterschiedlichen Defekten, um deren Regeneration zu unterstützen. Bislang bleibt unklar, wie genau solche Gerüste den Knochenregenerationsprozess beeinflussen, was deren alltägliche klinische Anwendung für die Behandlung von großen Knochendefekten unterbunden hat. Zur Bewertung des klinischen Potenzials eines Gerüstes wurde vor allem die Versuch-und-Irrtum-Methode herangezogen, welche langwierige, teure und mitunter ethisch fragwürdige Experimente erfordert. Dieses wichtige klinische Problem galt als Ausgangspunkt dieses Projekts. Ziel der Doktorarbeit war es also, eine in silico Methode zu entwickeln, um Gerüste für die Regeneration großer Knochendefekte zu konzipieren, die den endogenen Knochenheilungsprozess optimal unterstützen. Dazu wurden spezifische Mechanismen der gerüstgestützten Regeneration großer Knochendefekte anhand eines prädiktiven Computermodells für Knochenregeneration untersucht. Anschließend wurde der Effekt individueller Gerüstparameter studiert. Hierbei wurde die Dynamik des Knochenregenerationsprozesses erforscht, indem Heilungsvorhersagen nach bestimmten Heilungszeitpunkten miteinander verglichen wurden. Letztens wurde ein Computer-Framework für die Optimierung der Knochengerüste mit dem Ziel entwickelt, das Volumen regenerierten Knochens zu maximieren. Die in silico Untersuchung der gerüstgestützten Regeneration großer Knochendefekte baute auf einer gekoppelten Finite-Elemente-Analyse und agentenbasierte Modellierung auf, um verschiedene Experimente zu simulieren. Der Vergleich zwischen den in silico Vorhersagen und den experimentellen Ergebnissen lieferte mechanistische Einblicke in den Regenerationsprozess: (1) der Mangel an biologischer Stimulation in großen Knochendefekten, der durch den Einsatz von Gerüstmaterial oder Knochenmaterial kompensiert werden kann, und (2) der Einfluss der Gerüstflächen auf die Prozesse von Zellmigration und Gewebeanlagerung. Unterschiedliche Gerüste wurden simuliert, indem die Porengröße, die Stützengröße oder die Materialeigenschaften verändert wurden. Generell zeigte sich, dass poröse steife Gerüste oder voluminösere weichere Gerüste die Knochenregeneration am vorteilhaftesten unterstützen. Allerdings hingen die optimalen Poren- oder Stützengrößen größtenteils von der zugrunde liegenden Gerüstarchitektur ab, was darauf hinweist, dass eine allgemeingültige Empfehlung nicht angewendet werden kann, um optimale Gerüste zu konzipieren. Darüber hinaus zeigte die Modellierung von verschiedenen Zeitintervallen (initiale Mechanik und Simulation der Knochenregeneration) die Dynamik des Knochenregenerationsprozesses. Ergebnisse aus verschiedenen Zeitintervallen standen nämlich im Widerspruch zueinander: mehrere Gerüste schienen initial sehr vorteilhaft aber der Modellvorhersagen zufolge wurde die Knochenregeneration dann nicht gut unterstützt. Diese Feststellung bestätigte den Bedarf eines dynamischen Optimierungsprozesses, der auch den Regenerationsprozess berücksichtigen würde. Letztens wurde ein Computer-Framework für die Optimierung von Knochengerüsten entwickelt. Als Ziel wurde die Maximierung des Volumens des regenerierten Knochens nach dem mechanobiologischen Knochenregenerationsmodell gesetzt. Gerüste wurden anhand einiger Variablen (etwa Porengröße oder Materialeigenschaften) parametrisiert. Eine Surrogat-Optimierungsvorgehensweise wurde wegen der rechenintensiven Regenerationssimulationen gewählt: ein vereinfachtes Input-Output-Verhältnis wurde von einer Gruppe von initialen Simulationsläufen abgeleitet und für den Optimierungsprozess benutzt, um zu viele rechenintensive Simulationsläufe zu vermeiden. Die Ergebnisse dieser Doktorarbeit beweisen das Anwendungspotenzial dieser Methode für ein vereinfachtes kubisches Gerüst und ein realistischeres zylindrisches Gerüst. Diese Ergebnisse zeigen, dass das initiale Design des Gerüsts und dessen Parametrierung bedacht ausgesucht werden sollten, um den Optimierungsausgang zu verbessern. Zukünftige Forschungsarbeit sollte die Validierung des Computermodells für die gerüstgestützte Regeneration großer Knochendefekte fortsetzen. Insbesondere ist darauf zu achten, die rechnerische Effizienz dieser Modelle für deren Anwendung für Optimierungszwecke zu verbessern. Zusätzlich sollten realistischere, klinisch-basierte Gerüste für das Optimierungsverfahren mit komplementären Experimenten benutzt werden. Auf dieser Weise kann ein grundlegendes Verständnis für das Heilungspotenzial des Gerüstes geschaffen und ein fundiertes Design von experimentellen Gerüsten iterativ verbessert werden

Initial mechanical conditions within an optimized bone scaffold do not ensure bone regeneration – an in silico analysis

Large bone defects remain a clinical challenge because they do not heal spontaneously. 3-D printed scaffolds are a promising treatment option for such critical defects. Recent scaffold design strategies have made use of computer modelling techniques to optimize scaffold design. In particular, scaffold geometries have been optimized to avoid mechanical failure and recently also to provide a distinct mechanical stimulation to cells within the scaffold pores. This way, mechanical strain levels are optimized to favour the bone tissue formation. However, bone regeneration is a highly dynamic process where the mechanical conditions immediately after surgery might not ensure optimal regeneration throughout healing. Here, we investigated in silico whether scaffolds presenting optimal mechanical conditions for bone regeneration immediately after surgery also present an optimal design for the full regeneration process. A computer framework, combining an automatic parametric scaffold design generation with a mechano-biological bone regeneration model, was developed to predict the level of regenerated bone volume for a large range of scaffold designs and to compare it with the scaffold pore volume fraction under favourable mechanical stimuli immediately after surgery. We found that many scaffold designs could be considered as highly beneficial for bone healing immediately after surgery; however, most of them did not show optimal bone formation in later regenerative phases. This study allowed to gain a more thorough understanding of the effect of scaffold geometry changes on bone regeneration and how to maximize regenerated bone volume in the long term

Mechano-Biological Computer Model of Scaffold-Supported Bone Regeneration: Effect of Bone Graft and Scaffold Structure on Large Bone Defect Tissue Patterning

Large segmental bone defects represent a clinical challenge for which current treatment procedures have many drawbacks. 3D-printed scaffolds may help to support healing, but their design process relies mainly on trial and error due to a lack of understanding of which scaffold features support bone regeneration. The aim of this study was to investigate whether existing mechano-biological rules of bone regeneration can also explain scaffold-supported bone defect healing. In addition, we examined the distinct roles of bone grafting and scaffold structure on the regeneration process. To that end, scaffold-surface guided migration and tissue deposition as well as bone graft stimulatory effects were included in an in silico model and predictions were compared to in vivo data. We found graft osteoconductive properties and scaffold-surface guided extracellular matrix deposition to be essential features driving bone defect filling in a 3D-printed honeycomb titanium structure. This knowledge paves the way for the design of more effective 3D scaffold structures and their pre-clinical optimization, prior to their application in scaffold-based bone defect regeneration

A 3D in Silico Multi-Tissue Evolution Model Highlights the Relevance of Local Strain Accumulation in Bone Fracture Remodeling

Since 5–10% of all bone fractures result in non-healing situations, a thorough understanding of the various bone fracture healing phases is necessary to propose adequate therapeutic strategies. In silico models have greatly contributed to the understanding of the influence of mechanics on tissue formation and resorption during the soft and hard callus phases. However, the late-stage remodeling phase has not been investigated from a mechanobiological viewpoint so far. Here, we propose an in silico multi-tissue evolution model based on mechanical strain accumulation to investigate the mechanobiological regulation of bone remodeling during the late phase of healing. Computer model predictions are compared to histological data of two different pre-clinical studies of bone healing. The model predicted the bone marrow cavity re-opening and the resorption of the external callus. Our results suggest that the local strain accumulation can explain the fracture remodeling process and that this mechanobiological response is conserved among different mammal species. Our study paves the way for further understanding of non-healing situations that could help adapting therapeutic strategies to foster bone healing

A 3D in Silico Multi-Tissue Evolution Model Highlights the Relevance of Local Strain Accumulation in Bone Fracture Remodeling

International audienceSince 5–10% of all bone fractures result in non-healing situations, a thorough understanding of the various bone fracture healing phases is necessary to propose adequate therapeutic strategies. In silico models have greatly contributed to the understanding of the influence of mechanics on tissue formation and resorption during the soft and hard callus phases. However, the late-stage remodeling phase has not been investigated from a mechanobiological viewpoint so far. Here, we propose an in silico multi-tissue evolution model based on mechanical strain accumulation to investigate the mechanobiological regulation of bone remodeling during the late phase of healing. Computer model predictions are compared to histological data of two different pre-clinical studies of bone healing. The model predicted the bone marrow cavity re-opening and the resorption of the external callus. Our results suggest that the local strain accumulation can explain the fracture remodeling process and that this mechanobiological response is conserved among different mammal species. Our study paves the way for further understanding of non-healing situations that could help adapting therapeutic strategies to foster bone healing

An in silico model predicts the impact of scaffold design in large bone defect regeneration

Large bone defects represent a clinical challenge for which the implantation of scaffolds appears as a promising strategy. However, their use in clinical routine is limited, in part due to a lack of understanding of how scaffolds should be designed to support regeneration. Here, we use the power of computer modeling to investigate mechano-biological principles behind scaffold-guided bone regeneration and the influence of scaffold design on the regeneration process. Computer model predictions are compared to experimental data of large bone defect regeneration in sheep. We identified two main key players in scaffold-guided regeneration: (1) the scaffold surface guidance of cellular migration and tissue formation processes and (2) the stimulation of progenitor cell activity by the scaffold material composition. In addition, lower scaffold surface-area-to-volume ratio was found to be beneficial for bone regeneration due to enhanced cellular migration. To a lesser extent, a reduced scaffold Young's modulus favored bone formation. STATEMENT OF SIGNIFICANCE: 3D-printed scaffolds offer promising treatment strategies for large bone defects but their broader clinical use requires a more thorough understanding of their interaction with the bone regeneration process. The predictions of our in silico model compared to two experimental set-ups highlighted the importance of (1) the scaffold surface guidance of cellular migration and tissue formation processes and (2) the scaffold material stimulation of progenitor cell activity. In addition, the model was used to investigate the effect on the bone regeneration process of (1) the scaffold surface-area-to-volume ratio, with lower ratios favoring more bone growth, and (2) the scaffold material properties, with stiffer scaffold materials yielding a lower bone growth.</p