To date, the combination of histological sectioning, staining, and microscopic assessment of the 2D sections is still the golden standard for structural and compositional analysis of biological tissues. X-ray microfocus computed tomography (microCT) is an emerging 3D imaging technique with high potential for 3D structural analysis of biological tissues with a complex and heterogeneous 3D structure, such as the trabecular bone. However, its use has been mostly limited to mineralized tissues because of the inherently low X-ray absorption of soft tissues. To achieve sufficient X-ray attenuation, chemical compounds containing high atomic number elements that bind to soft tissues have been recently adopted as contrast agents (CAs) for contrast-enhanced microCT (CE-CT); this novel technique is very promising for quantitative “virtual” 3D anatomical pathology of both mineralized and soft biological tissues. In this paper, we provided a review of the advances in CE-CT since the very first reports on the technology to date. Perfusion CAs for in vivo imaging have not been discussed, as the focus of this review was on CAs that bind to the tissue of interest and that are, thus, used for ex vivo imaging of biological tissues. As CE-CT has mostly been applied for the characterization of musculoskeletal tissues, we have put specific emphasis on these tissues. Advantages and limitations of multiple CAs for different musculoskeletal tissues have been highlighted, and their reproducibility has been discussed. Additionally, the advantages of the “full” 3D CE-CT information have been pinpointed, and its importance for more detailed structural, spatial, and functional characterization of the tissues of interest has been shown. Finally, the remaining challenges that are still hampering a broader adoption of CE-CT have been highlighted, and suggestions have been made to move the field of CE-CT imaging one step further towards a standard accepted tool for quantitative virtual 3D anatomical pathology.
Bioreactors are crucial tools for the manufacturing of living cell‐based tissue engineered products. However, to reach the market successfully, higher degrees of automation, as well as a decreased footprint still need to be reached. In this study, the use of a benchtop bioreactor for in vitro perfusion culture of scaffold‐based tissue engineering constructs is assessed. A low‐footprint benchtop bioreactor system is designed, comprising a single‐use fluidic components and a bioreactor housing. The bioreactor is operated using an in‐house developed program and the culture environment is monitored by specifically designed sensor ports. A gas‐exchange module is incorporated allowing for heat and mass transfers. Titanium‐based scaffolds are seeded with human periosteum‐derived cells and cultured up to 3 weeks. The benchtop bioreactor constructs are compared to benchmark perfusion systems. Live/Dead stainings, DNA quantifications, glucose consumption, and lactate production assays confirm that the constructs cultured in the benchtop bioreactor grew similarly to the benchmark systems. Manual regulation of the system set points enabled efficient alteration of the culture environment in terms of temperature, pH, and dissolved oxygen. This study provides the necessary basis for the development of low‐footprint, automated, benchtop perfusion bioreactors and enables the implementation of active environment control.
In the field of regenerative medicine, microcarriers are used as support matrix for the growth of adherent cells. They are increasingly recognised as promising biomaterials for large scale, cost-effective cell expansion bioreactor processes. However, their individual morphologies can be highly heterogeneous which increases bioprocesses’ variability. Additionally, only limited information is available on the microcarriers’ 3D morphology and how it affects cell proliferation. Most imaging modalities do not provide sufficient 3D information or have a too limited field of view to appropriately study the 3D morphology. While microfocus X-ray computed tomography (microCT) could be appropriate, many microcarriers are hydrated before in-vitro use. This wet state makes them swell, changing considerably their morphology and making them indistinguishable from the culture solution in regular microCT images due to their physical density close to water. The use of contrast-enhanced microCT (CE-CT) has been recently reported for 3D imaging of soft materials. In this study, we selected a range of commercially available microcarrier types and used a combination of microCT and CE-CT for full 3D morphological characterization of large numbers of microcarriers, both in their dry and wet state. With in-house developed image processing and analysis tools, morphometrics of individual microcarriers were collected. Also, the morphology in wet state was assessed and related to accessible attachment surface area as a function of cell size. The morphological information on all microcarriers was collected in a publicly available database. This work provides a quantitative basis for optimization and modelling of microcarrier based cell expansion processes.
Mechanical ventilation is a widely used breathing support for patients in intensive care. Its effects on the respiratory and cardiovascular systems are complex and difficult to predict. This work first presents a minimal mathematical model representing the mechanics of both systems and their interaction, in terms of flows, pressures and volumes. The aim of this model is to get insight on the two systems status when mechanical ventilation settings, such as positive end-expiratory pressure, are changing. The parameters of the model represent cardiac elastances and vessel compliances and resistances. As a second step, these parameters are estimated from 16 experimental datasets. The data come from three pig experiments reproducing intensive care conditions, where a large range of positive end-expiratory pressures was imposed by the mechanical ventilator. The data used for parameter estimation is limited to information available in the intensive care unit, such as stroke volume, central venous pressure and systemic arterial pressure. The model is able to satisfactorily reproduce this experimental data, with mean relative errors ranging from 1 to 26 %. The model also reproduces the dynamics of the cardio-vascular and respiratory systems, and their interaction. By looking at the estimated parameter values, one can quantitatively track how the two coupled systems mechanically react to changes in external conditions imposed by the ventilator. This work thus allows real-time, model-based management of ventilator settings.
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