References of "Geris, Liesbet"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailCombinatorial Analysis of Growth Factors Reveals the Contribution of Bone Morphogenetic Proteins to Chondrogenic Differentiation of Human Periosteal Cells.
Mendes, Luis Filipe; Tam, Wai Long; Chai, Yoke Chin et al

in Tissue Engineering. Part C, Methods (2016), 22(5), 473-86

Successful application of cell-based strategies in cartilage and bone tissue engineering has been hampered by the lack of robust protocols to efficiently differentiate mesenchymal stem cells into the ... [more ▼]

Successful application of cell-based strategies in cartilage and bone tissue engineering has been hampered by the lack of robust protocols to efficiently differentiate mesenchymal stem cells into the chondrogenic lineage. The development of chemically defined culture media supplemented with growth factors (GFs) has been proposed as a way to overcome this limitation. In this work, we applied a fractional design of experiment (DoE) strategy to screen the effect of multiple GFs (BMP2, BMP6, GDF5, TGF-beta1, and FGF2) on chondrogenic differentiation of human periosteum-derived mesenchymal stem cells (hPDCs) in vitro. In a micromass culture (muMass) system, BMP2 had a positive effect on glycosaminoglycan deposition at day 7 (p < 0.001), which in combination with BMP6 synergistically enhanced cartilage-like tissue formation that displayed in vitro mineralization capacity at day 14 (p < 0.001). Gene expression of muMasses cultured for 7 days with a medium formulation supplemented with 100 ng/mL of BMP2 and BMP6 and a low concentration of GDF5, TGF-beta1, and FGF2 showed increased expression of Sox9 (1.7-fold) and the matrix molecules aggrecan (7-fold increase) and COL2A1 (40-fold increase) compared to nonstimulated control muMasses. The DoE analysis indicated that in GF combinations, BMP2 was the strongest effector for chondrogenic differentiation of hPDCs. When transplanted ectopically in nude mice, the in vitro-differentiated muMasses showed maintenance of the cartilaginous phenotype after 4 weeks in vivo. This study indicates the power of using the DoE approach for the creation of new medium formulations for skeletal tissue engineering approaches. [less ▲]

Detailed reference viewed: 33 (0 ULiège)
Full Text
Peer Reviewed
See detailCoupling curvature-dependent and shear stress-stimulated neotissue growth in dynamic bioreactor cultures: a 3D computational model of a complete scaffold.
Guyot, Y.; Papantoniou, I.; Luyten, F. P. et al

in Biomechanics & Modeling in Mechanobiology (2016), 15(1), 169-80

The main challenge in tissue engineering consists in understanding and controlling the growth process of in vitro cultured neotissues toward obtaining functional tissues. Computational models can provide ... [more ▼]

The main challenge in tissue engineering consists in understanding and controlling the growth process of in vitro cultured neotissues toward obtaining functional tissues. Computational models can provide crucial information on appropriate bioreactor and scaffold design but also on the bioprocess environment and culture conditions. In this study, the development of a 3D model using the level set method to capture the growth of a microporous neotissue domain in a dynamic culture environment (perfusion bioreactor) was pursued. In our model, neotissue growth velocity was influenced by scaffold geometry as well as by flow- induced shear stresses. The neotissue was modeled as a homogenous porous medium with a given permeability, and the Brinkman equation was used to calculate the flow profile in both neotissue and void space. Neotissue growth was modeled until the scaffold void volume was filled, thus capturing already established experimental observations, in particular the differences between scaffold filling under different flow regimes. This tool is envisaged as a scaffold shape and bioprocess optimization tool with predictive capacities. It will allow controlling fluid flow during long-term culture, whereby neotissue growth alters flow patterns, in order to provide shear stress profiles and magnitudes across the whole scaffold volume influencing, in turn, the neotissue growth. [less ▲]

Detailed reference viewed: 47 (2 ULiège)
Full Text
Peer Reviewed
See detailCombining microCT-based characterization with empirical modelling as a robust screening approach for the design of optimized CaP-containing scaffolds for progenitor cell-mediated bone formation.
Kerckhofs, G.; Chai, Y. C.; Luyten, F. P. et al

in Acta Biomaterialia (2016), 35

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely ... [more ▼]

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely variable material characteristics and patient-specificities, however, current bone TE strategies still suffer from low repeatability and lack of robustness, which hamper clinical translation. Hence, optimal TE construct (i.e. cells and scaffold) characteristics are still under debate. This study aimed to reduce the material-specific variability for cell-based construct design, avoiding trial-and-error, by combining microCT characterization and empirical modelling as an innovative and robust screening approach. Via microCT characterization we have built a quantitative construct library of morphological and compositional properties of six CE approved CaP-based scaffolds (CopiOs(R), BioOss, Integra Mozaik, chronOS Vivify, MBCP and ReproBone), and of their bone forming capacity and in vivo scaffold degradation when combined with human periosteal derived cells (hPDCs). The empirical model, based on the construct library, allowed identification of the construct characteristics driving optimized bone formation, i.e. (a) the percentage of beta-TCP and dibasic calcium phosphate, (b) the concavity of the CaP structure, (c) the average CaP structure thickness and (d) the seeded cell amount (taking into account the seeding efficiency). Additionally, the model allowed to quantitatively predict the bone forming response of different hPDC-CaP scaffold combinations, thus providing input for a more robust design of optimized constructs and avoiding trial-and error. This could improve and facilitate clinical translation. STATEMENT OF SIGNIFICANCE: Biomaterials that support regenerative processes are a key ingredient for successful bone tissue engineering (TE). However, the optimal scaffold structure is still under debate. In this study, we have provided a useful innovative approach for robust screening of potential biomaterials or constructs (i.e. scaffolds seeded with cells and/or growth factors) by combining microCT characterization with empirical modelling. This novel approach leads to a better insight in the scaffold parameters influencing progenitor cell-mediated bone formation. Additionally, it serves as input for more controlled and robust design of optimized CaP-containing bone TE scaffolds. Hence, this novel approach could improve and facilitate clinical translation. [less ▲]

Detailed reference viewed: 37 (4 ULiège)
Full Text
Peer Reviewed
See detailIn silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.
Geris, Liesbet ULiege; Guyot, Y.; Schrooten, J. et al

in Interface focus (2016), 6(2), 20150105

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as ... [more ▼]

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design. [less ▲]

Detailed reference viewed: 38 (6 ULiège)
Full Text
See detailA reduced model developed for describing neotissue growth during dynamic bioreactor culture
Mehrian, Mohammad ULiege; Guyot, Yann; Geris, Liesbet ULiege

Scientific conference (2015, November 26)

Detailed reference viewed: 19 (6 ULiège)
Full Text
See detailUncertainty in biology: a computational modeling approach
Geris, Liesbet ULiege; Gomez-Cabrero, David

Book published by Springer (2015)

Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies. Computational modeling ... [more ▼]

Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies. Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: 1. Modeling establishment under uncertainty 2. Model selection and parameter fitting 3. Sensitivity analysis and model adaptation 4. Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate students and researchers active in the field of computational modeling of biomedical processes who seek to acquaint themselves with the different ways in which to study the parameter space of their model as well as its overall behavior. [less ▲]

Detailed reference viewed: 134 (8 ULiège)
Full Text
Peer Reviewed
See detailA semiquantitative framework for gene regulatory networks: increasing the time and quantitative resolution of Boolean networks
Kerkhofs, Johan ULiege; Geris, Liesbet ULiege

in PLoS ONE (2015), 10(6), 0130033

Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic ... [more ▼]

Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour. [less ▲]

Detailed reference viewed: 43 (4 ULiège)
Full Text
See detailIn silico screening to predict chondrocyte hypertrophy using a semiquantitative gene network model
Kerkhofs, Johan ULiege; Leijten, Jeroen; Luyten, Frank et al

Poster (2015, April 30)

PURPOSE: In development, chondrocyte hypertrophy is a crucial and well-studied step in endochondral ossification. Hypertrophy may also play a role in pathophysiological processes, including osteoarthritis ... [more ▼]

PURPOSE: In development, chondrocyte hypertrophy is a crucial and well-studied step in endochondral ossification. Hypertrophy may also play a role in pathophysiological processes, including osteoarthritis. We employ a computational approach to estimate the effect of individual factors in this complex process. METHODS: We have combined information gleaned from a high number of publications on chondrocyte differentiation into a gene regulatory network of 46 factors and over 150 interactions. This network can estimate the stability of proliferative chondrocytes/permanent cartilage (stable state with SOX9 activity) and hypertrophic chondrocytes (stable state with RUNX2 activity) by employing 2 measures. A first measure is a Monte Carlo analysis that assesses stability in the face of random initial conditions, the second modifies stable states to estimate the sensitivity to perturbation. RESULTS: For each factor, these qualitative measures are calculated in silico under knockout and overexpression conditions and compared to the wild type situation. This enables screening of the effects of all incorporated factors on cartilage homeostasis, differentiation and pathogenesis via the initiation of hypertrophy. Indeed, our gene network analysis indicated multiple candidate genes for the development of osteoarthritis. Factors that amplify the SOX9 attractor basin include TGFβ, PPR, IGF-I, and PKA. The presence of RAS, IHH, GLI2 and FGF is required for the Runx2 stable state. Using a literature study, we corroborated several of the proposed factors. CONCLUSIONS: In silico screening of overexpression and knockout presents a novel strategy to improve bone and cartilage tissue engineering approaches, and can be used to propose a list of putative therapeutic targets for e.g. osteoarthritis. [less ▲]

Detailed reference viewed: 32 (2 ULiège)
Full Text
Peer Reviewed
See detailComputational modeling of bone fracture non-unions: four clinically relevant case studies.
Carlier, Aurelie; Lammens, Johan; Van Oosterwyck, Hans et al

in In Silico Cell and Tissue Science (2015), 2

The human skeleton has a remarkable regeneration capacity. Nevertheless, 5-10 % of the bone fractures fails to heal and develops into a non-union which is a challenging orthopedic complication requiring ... [more ▼]

The human skeleton has a remarkable regeneration capacity. Nevertheless, 5-10 % of the bone fractures fails to heal and develops into a non-union which is a challenging orthopedic complication requiring complex and expensive treatment. This review paper will discuss four different computational models, each capturing a particular clinical case of non-union: non-union induced by reaming of the marrow canal and periosteal stripping, non-union due to a large interfragmentary gap, non-union due to a genetic disorder [i.e. NF1 related congenital pseudoarthrosis of the tibia (CPT)] and non-union due to mechanical overload. Together, the four computational models are able to capture the etiology of a wide range of fracture non-union types and design novel treatment strategies thereof. Further research is required to corroborate the computational models in both animal and human settings and translate them from bench to bed side. [less ▲]

Detailed reference viewed: 13 (0 ULiège)
Full Text
Peer Reviewed
See detailA mechano-regulatory model for bone healing predictions under the influence of ultrasound.
Vavva, Maria G.; Grivas, Konstantinos N.; Carlier, Aurelie et al

in Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference (2015), 2015

The bone healing process involves a sequence of cellular action and interaction, regulated by biochemical and mechanical signals. Experimental studies have shown that ultrasound accelerates bone ... [more ▼]

The bone healing process involves a sequence of cellular action and interaction, regulated by biochemical and mechanical signals. Experimental studies have shown that ultrasound accelerates bone solidification and enhances the underlying healing mechanisms. An integrated computational model is presented for deriving predictions of bone healing under the presence of ultrasound. [less ▲]

Detailed reference viewed: 15 (0 ULiège)
Full Text
Peer Reviewed
See detailA Three-Dimensional Computational Fluid Dynamics Model Of Shear Stress Distribution During Neotissue Growth In A Perfusion Bioreactor.
Guyot, Yann ULiege; Luyten, F. P.; Schrooten, J. et al

in Biotechnology and bioengineering (2015)

Bone tissue engineering strategies use flow through perfusion bioreactors to apply mechanical stimuli to cells seeded on porous scaffolds. Cells grow on the scaffold surface but also by bridging the ... [more ▼]

Bone tissue engineering strategies use flow through perfusion bioreactors to apply mechanical stimuli to cells seeded on porous scaffolds. Cells grow on the scaffold surface but also by bridging the scaffold pores leading a fully filled scaffold following the scaffold's geometric characteristics. Current computational fluid dynamic approaches for tissue engineering bioreactor systems have been mostly carried out for empty scaffolds. The effect of 3D cell growth and extracellular matrix formation (termed in this study as neotissue growth), on its surrounding fluid flow field is a challenge yet to be tackled. In this work a combined approach was followed linking curvature driven cell growth to fluid dynamics modeling. The level-set method (LSM) was employed to capture neotissue growth driven by curvature, while the Stokes and Darcy equations, combined in the Brinkman equation, provided information regarding the distribution of the shear stress profile at the neotissue/medium interface and within the neotissue itself during growth. The neotissue was assumed to be micro-porous allowing flow through its structure while at the same time allowing the simulation of complete scaffold filling without numerical convergence issues. The results show a significant difference in the amplitude of shear stress for cells located within the micro-porous neo-tissue or at the neotissue/medium interface, demonstrating the importance of taking along the neotissue in the calculation of the mechanical stimulation of cells during culture.The presented computational framework is used on different scaffold pore geometries demonstrating its potential to be used a design as tool for scaffold architecture taking into account the growing neotissue. This article is protected by copyright. All rights reserved. [less ▲]

Detailed reference viewed: 63 (12 ULiège)
Full Text
Peer Reviewed
See detailCell based advanced therapeutic medicinal products for bone repair: Keep it simple?
Leijten, J.; Chai, Y. C.; Papantoniou, I. et al

in Advanced drug delivery reviews (2015), 84

The development of cell based advanced therapeutic medicinal products (ATMPs) for bone repair has been expected to revolutionize the health care system for the clinical treatment of bone defects. Despite ... [more ▼]

The development of cell based advanced therapeutic medicinal products (ATMPs) for bone repair has been expected to revolutionize the health care system for the clinical treatment of bone defects. Despite this great promise, the clinical outcomes of the few cell based ATMPs that have been translated into clinical treatments have been far from impressive. In part, the clinical outcomes have been hampered because of the simplicity of the first wave of products. In response the field has set-out and amassed a plethora of complexities to alleviate the simplicity induced limitations. Many of these potential second wave products have remained "stuck" in the development pipeline. This is due to a number of reasons including the lack of a regulatory framework that has been evolving in the last years and the shortage of enabling technologies for industrial manufacturing to deal with these novel complexities. In this review, we reflect on the current ATMPs and give special attention to novel approaches that are able to provide complexity to ATMPs in a straightforward manner. Moreover, we discuss the potential tools able to produce or predict 'goldilocks' ATMPs, which are neither too simple nor too complex. [less ▲]

Detailed reference viewed: 17 (2 ULiège)
Full Text
Peer Reviewed
See detailComputational modeling under uncertainty: challenges and opportunities
Gomez-Cabrero, David; Geris, Liesbet ULiege

in Modeling under uncertainty: a computational modeling approach (2015)

Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and ... [more ▼]

Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and mechanistic understanding of biological processes underpinning diseases. While in the present book, we have reviewed the necessary background and existing novel methodologies that set the basis for dealing with uncertainty, there are still many “grey”, or less well-defined, areas of investigations offering both challenges and opportunities. This final chapter in the book provides some reflections on those areas, namely: (1) the need for novel robust mathematical and statistical methodologies to generate hypothesis under uncertainty; (2) the challenge of aligning those methodologies in a context that requires larger computational resources; (3) the accessibility of modeling tools for less mathematical literate researchers; and (4) the integration of models with –omics data and its application in clinical environments. [less ▲]

Detailed reference viewed: 46 (0 ULiège)
Full Text
Peer Reviewed
See detailAn introduction to uncertainty in the development of computational models of biological processes
Geris, Liesbet ULiege; Gomez-Cabrero, David

in Modeling under uncertainty: a computational modeling approach (2015)

This chapter aims to provide an introduction to the different ways in which uncertainty can be dealt with computational modelling of biological processes. The first step is model establishment under ... [more ▼]

This chapter aims to provide an introduction to the different ways in which uncertainty can be dealt with computational modelling of biological processes. The first step is model establishment under uncertainty. Once models have been established, data can further be used to select which of the proposed models best meets the predefined criteria. Subsequently, parameter values can be optimized for a specific model configuration. Sensitivity analyses allow to assess the influence of the previous choices on the model output. Additionally, model adaptation permits to focus on specific aspects of the model without losing its global predictive capacity. Finally, predictions with the established models should also consider the effect of uncertainty in the model development process. [less ▲]

Detailed reference viewed: 33 (0 ULiège)
Full Text
Peer Reviewed
See detailOxygen as a critical determinant of bone fracture healing-a multiscale model.
Carlier, Aurelie; Geris, Liesbet ULiege; Gastel, Nick Van et al

in Journal of theoretical biology (2015), 365

A timely restoration of the ruptured blood vessel network in order to deliver oxygen and nutrients to the fracture zone is crucial for successful bone healing. Indeed, oxygen plays a key role in the ... [more ▼]

A timely restoration of the ruptured blood vessel network in order to deliver oxygen and nutrients to the fracture zone is crucial for successful bone healing. Indeed, oxygen plays a key role in the aerobic metabolism of cells, in the activity of a myriad of enzymes as well as in the regulation of several (angiogenic) genes. In this paper, a previously developed model of bone fracture healing is further improved with a detailed description of the influence of oxygen on various cellular processes that occur during bone fracture healing. Oxygen ranges of the cell-specific oxygen-dependent processes were established based on the state-of-the art experimental knowledge through a rigorous literature study. The newly developed oxygen model is compared with previously published experimental and in silico results. An extensive sensitivity analysis was also performed on the newly introduced oxygen thresholds, indicating the robustness of the oxygen model. Finally, the oxygen model was applied to the challenging clinical case of a critical sized defect (3mm) where it predicted the formation of a fracture non-union. Further model analyses showed that the harsh hypoxic conditions in the central region of the callus resulted in cell death and disrupted bone healing thereby indicating the importance of a timely vascularization for the successful healing of a large bone defect. In conclusion, this work demonstrates that the oxygen model is a powerful tool to further unravel the complex spatiotemporal interplay of oxygen delivery, diffusion and consumption with the several healing steps, each occurring at distinct, optimal oxygen tensions during the bone repair process. [less ▲]

Detailed reference viewed: 74 (2 ULiège)
Full Text
Peer Reviewed
See detailBringing computational models of bone regeneration to the clinic.
Carlier, Aurelie; Geris, Liesbet ULiege; Lammens, Johan et al

in Wiley interdisciplinary reviews. Systems biology and medicine (2015), 7(4), 183-94

Although the field of bone regeneration has experienced great advancements in the last decades, integrating all the relevant, patient-specific information into a personalized diagnosis and optimal ... [more ▼]

Although the field of bone regeneration has experienced great advancements in the last decades, integrating all the relevant, patient-specific information into a personalized diagnosis and optimal treatment remains a challenging task due to the large number of variables that affect bone regeneration. Computational models have the potential to cope with this complexity and to improve the fundamental understanding of the bone regeneration processes as well as to predict and optimize the patient-specific treatment strategies. However, the current use of computational models in daily orthopedic practice is very limited or inexistent. We have identified three key hurdles that limit the translation of computational models of bone regeneration from bench to bed side. First, there exists a clear mismatch between the scope of the existing and the clinically required models. Second, most computational models are confronted with limited quantitative information of insufficient quality thereby hampering the determination of patient-specific parameter values. Third, current computational models are only corroborated with animal models, whereas a thorough (retrospective and prospective) assessment of the computational model will be crucial to convince the health care providers of the capabilities thereof. These challenges must be addressed so that computational models of bone regeneration can reach their true potential, resulting in the advancement of individualized care and reduction of the associated health care costs. WIREs Syst Biol Med 2015, 7:183-194. doi: 10.1002/wsbm.1299 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. [less ▲]

Detailed reference viewed: 47 (3 ULiège)
Full Text
Peer Reviewed
See detailMultifactorial Optimization of Contrast-Enhanced Nanofocus Computed Tomography for Quantitative Analysis of Neo-Tissue Formation in Tissue Engineering Constructs.
Sonnaert, Maarten; Kerckhofs, Greet; Papantoniou, Ioannis et al

in PloS one (2015), 10(6), 0130227

To progress the fields of tissue engineering (TE) and regenerative medicine, development of quantitative methods for non-invasive three dimensional characterization of engineered constructs (i.e. cells ... [more ▼]

To progress the fields of tissue engineering (TE) and regenerative medicine, development of quantitative methods for non-invasive three dimensional characterization of engineered constructs (i.e. cells/tissue combined with scaffolds) becomes essential. In this study, we have defined the most optimal staining conditions for contrast-enhanced nanofocus computed tomography for three dimensional visualization and quantitative analysis of in vitro engineered neo-tissue (i.e. extracellular matrix containing cells) in perfusion bioreactor-developed Ti6Al4V constructs. A fractional factorial 'design of experiments' approach was used to elucidate the influence of the staining time and concentration of two contrast agents (Hexabrix and phosphotungstic acid) and the neo-tissue volume on the image contrast and dataset quality. Additionally, the neo-tissue shrinkage that was induced by phosphotungstic acid staining was quantified to determine the operating window within which this contrast agent can be accurately applied. For Hexabrix the staining concentration was the main parameter influencing image contrast and dataset quality. Using phosphotungstic acid the staining concentration had a significant influence on the image contrast while both staining concentration and neo-tissue volume had an influence on the dataset quality. The use of high concentrations of phosphotungstic acid did however introduce significant shrinkage of the neo-tissue indicating that, despite sub-optimal image contrast, low concentrations of this staining agent should be used to enable quantitative analysis. To conclude, design of experiments allowed us to define the most optimal staining conditions for contrast-enhanced nanofocus computed tomography to be used as a routine screening tool of neo-tissue formation in Ti6Al4V constructs, transforming it into a robust three dimensional quality control methodology. [less ▲]

Detailed reference viewed: 20 (3 ULiège)