Time-of-Flight MRA of Intracranial Aneurysms with Interval Surveillance, Clinical Segmentation and Annotations.

Intracranial aneurysms (IAs) are present in 2-6% of the global population and can be catastrophic upon rupture with a mortality rate of 30-50%. IAs are commonly detected through time-of-flight magnetic resonance angiography (TOF-MRA), however, this data is rarely available for research and training purposes. The provision of imaging resources such as TOF-MRA images is imperative to develop new strategies for IA detection, rupture prediction, and surgical training. To support efforts in addressing data availability bottlenecks, we provide an open-access TOF-MRA dataset comprising 63 patients, of which 24 underwent interval surveillance imaging by TOF-MRA. Patient scans were evaluated by a neuroradiologist, providing aneurysm and vessel segmentations, clinical annotations, 3D models, in addition to 3D Slicer software environments containing all this data for each patient. This dataset is the first to provide interval surveillance imaging for supporting the understanding of IA growth and stability. This dataset will support computational and experimental research into IA dynamics and assist surgical and radiology training in IA treatment.

An automated parametric ear model to improve frugal 3D scanning methods for the advanced manufacturing of high-quality prosthetic ears.

Ear prostheses are commonly used for restoring aesthetics to those suffering missing or malformed external ears. Traditional fabrication of these prostheses is labour intensive and requires expert skill from a prosthetist. Advanced manufacturing including 3D scanning, modelling and 3D printing has the potential to improve this process, although more work is required before it is ready for routine clinical use. In this paper, we introduce a parametric modelling technique capable of producing high quality 3D models of the human ear from low-fidelity, frugal, patient scans; significantly reducing time, complexity and cost. Our ear model can be tuned to fit the frugal low-fidelity 3D scan through; (a) manual tuning, or (b) our automated particle filter approach. This potentially enables low-cost smartphone photogrammetry-based 3D scanning for high quality personalised 3D printed ear prosthesis. In comparison to standard photogrammetry, our parametric model improves completeness, from (81 ± 5)% to (87 ± 4)%, with only a modest reduction in accuracy, with root mean square error (RMSE) increasing from (1.0 ± 0.2) mm to (1.5 ± 0.2) mm (relative to metrology rated reference 3D scans, n = 14). Despite this reduction in the RMS accuracy, our parametric model improves the overall quality, realism, and smoothness. Our automated particle filter method differs only modestly compared to manual adjustments. Overall, our parametric ear model can significantly improve quality, smoothness and completeness of 3D models produced from 30-photograph photogrammetry. This enables frugal high-quality 3D ear models to be produced for use in the advanced manufacturing of ear prostheses.

Corrigendum: The effects of COVID-19 on the placenta during pregnancy.

[This corrects the article DOI: 10.3389/fimmu.2021.743022.].

3D Plotting of Calcium Phosphate Cement and Melt Electrowriting of Polycaprolactone Microfibers in One Scaffold: A Hybrid Additive Manufacturing Process.

The fabrication of patient-specific scaffolds for bone substitutes is possible through extrusion-based 3D printing of calcium phosphate cements (CPC) which allows the generation of structures with a high degree of customization and interconnected porosity. Given the brittleness of this clinically approved material, the stability of open-porous scaffolds cannot always be secured. Herein, a multi-technological approach allowed the simultaneous combination of CPC printing with melt electrowriting (MEW) of polycaprolactone (PCL) microfibers in an alternating, tunable design in one automated fabrication process. The hybrid CPC+PCL scaffolds with varying CPC strand distance (800-2000 µm) and integrated PCL fibers featured a strong CPC to PCL interface. While no adverse effect on mechanical stiffness was detected by the PCL-supported scaffold design; the microfiber integration led to an improved integrity. The pore distance between CPC strands was gradually increased to identify at which critical CPC porosity the microfibers would have a significant impact on pore bridging behavior and growth of seeded cells. At a CPC strand distance of 1600 µm, after 2 weeks of cultivation, the incorporation of PCL fibers led to pore coverage by a human mesenchymal stem cell line and an elevated proliferation level of murine pre-osteoblasts. The integrated fabrication approach allows versatile design adjustments on different levels.

Personalized Volumetric Tissue Generation by Enhancing Multiscale Mass Transport through 3D Printed Scaffolds in Perfused Bioreactors.

Engineered tissues provide an alternative to graft material, circumventing the use of donor tissue such as autografts or allografts and non-physiological synthetic implants. However, their lack of vasculature limits the growth of volumetric tissue more than several millimeters thick which limits their success post-implantation. Perfused bioreactors enhance nutrient mass transport inside lab-grown tissue but remain poorly customizable to support the culture of personalized implants. Here, a multiscale framework of computational fluid dynamics (CFD), additive manufacturing, and a perfusion bioreactor system are presented to engineer personalized volumetric tissue in the laboratory. First, microscale 3D printed scaffold pore geometries are designed and 3D printed to characterize media perfusion through CFD and experimental fluid testing rigs. Then, perfusion bioreactors are custom-designed to combine 3D printed scaffolds with flow-focusing inserts in patient-specific shapes as simulated using macroscale CFD. Finally, these computationally optimized bioreactor-scaffold assemblies are additively manufactured and cultured with pre-osteoblast cells for 7, 20, and 24 days to achieve tissue growth in the shape of human calcaneus bones of 13 mL volume and 1 cm thickness. This framework enables an intelligent model-based design of 3D printed scaffolds and perfusion bioreactors which enhances nutrient transport for long-term volumetric tissue growth in personalized implant shapes. The novel methods described here are readily applicable for use with different cell types, biomaterials, and scaffold microstructures to research therapeutic solutions for a wide range of tissues.

Image analyses for engineering advanced tissue biomanufacturing processes.

Industrial cell culture processes are inherently expensive, time-consuming, and variable. These limitations have become a critical bottleneck for the industrial translation of human cell and tissue biomanufacturing, as few human cell culture products deliver sufficient benefit, value, and consistency to offset their high manufacturing costs and produce useful clinical or biomedical solutions. Recent advances in biomedical image analysis and computational modelling can enhance the design and operation of high-efficiency tissue biomanufacturing platforms, as well as the high-content characterisation and monitoring of culture performance, to enable bioprocess control, optimisation, and automation. These computational technologies aim to maximize culture outcomes while minimizing variability and process development expense. In this review, we outline current resources and approaches which harness biomedical imaging and image-based computational models to design and operate efficient and robust human tissue biomanufacturing platforms.

Soft pneumatic actuators for mimicking multi-axial femoropopliteal artery mechanobiology.

Tissue biomanufacturing aims to produce lab-grown stem cell grafts and biomimetic drug testing platforms but remains limited in its ability to recapitulate native tissue mechanics. The emerging field of soft robotics aims to emulate dynamic physiological locomotion, representing an ideal approach to recapitulate physiologically complex mechanical stimuli and enhance patient-specific tissue maturation. The kneecap's femoropopliteal artery (FPA) represents a highly flexible tissue across multiple axes during blood flow, walking, standing, and crouching positions, and these complex biomechanics are implicated in the FPA's frequent presentation of peripheral artery disease. We developed a soft pneumatically actuated (SPA) cell culture platform to investigate how patient-specific FPA mechanics affect lab-grown arterial tissues. Silicone hyperelastomers were screened for flexibility and biocompatibility, then additively manufactured into SPAs using a simulation-based design workflow to mimic normal and diseased FPA extensions in radial, angular, and longitudinal dimensions. SPA culture platforms were seeded with mesenchymal stem cells, connected to a pneumatic controller, and provided with 24 h multi-axial exercise schedules to demonstrate the effect of dynamic conditioning on cell alignment, collagen production, and muscle differentiation without additional growth factors. Soft robotic bioreactors are promising platforms for recapitulating patient-, disease-, and lifestyle-specific mechanobiology for understanding disease, treatment simulations, and lab-grown tissue grafts.

Ultrasound Imaging Offers Promising Alternative to Create 3-D Models for Personalised Auricular Implants.

Three-dimensional imaging and advanced manufacturing are being applied in health care research to create novel diagnostic and surgical planning methods, as well as personalised treatments and implants. For ear reconstruction, where a cartilage-shaped implant is embedded underneath the skin to re-create shape and form, volumetric imaging and segmentation processing to capture patient anatomy are particularly challenging. Here, we introduce 3-D ultrasound (US) as an available option for imaging the external ear and underlying auricular cartilage structure, and compare it with computed tomography (CT) and magnetic resonance imaging (MRI) against micro-CT (µCT) as a high-resolution reference (gold standard). US images were segmented to create 3-D models of the auricular cartilage and compared against models generated from µCT to assess accuracy. We found that CT was significantly less accurate than the other methods (root mean square [RMS]: 1.30 ± 0.5 mm) and had the least contrast between tissues. There was no significant difference between MRI (RMS: 0.69 ± 0.2 mm) and US (0.55 ± 0.1 mm). US was also the least expensive imaging method at half the cost of MRI. These results unveil a novel use of ultrasound imaging that has not been presented before, as well as support its more widespread use in biofabrication as a low-cost imaging technique to create patient-specific 3D models and implants.

A Spatiotemporal Microenvironment Model to Improve Design of a Three-Dimensional Bioreactor for Red Cell Production.

Cellular microenvironments provide stimuli, including paracrine and autocrine growth factors and physicochemical cues, which support efficient in vivo cell production unmatched by current in vitro biomanufacturing platforms. While three-dimensional (3D) culture systems aim to recapitulate niche architecture and function of the target tissue/organ, they are limited in accessing spatiotemporal information to evaluate and optimize in situ cell/tissue process development. Herein, a mathematical modeling framework is parameterized by single-cell phenotypic imaging and multiplexed biochemical assays to simulate the nonuniform tissue distribution of nutrients/metabolites and growth factors in cell niche environments. This model is applied to a bone marrow mimicry 3D perfusion bioreactor containing dense stromal and hematopoietic tissue with limited red blood cell (RBC) egress. The model characterized an imbalance between endogenous cytokine production and nutrient starvation within the microenvironmental niches and recommended increased cell inoculum density and enhanced medium exchange, guiding the development of a miniaturized prototype bioreactor. The second-generation prototype improved the distribution of nutrients and growth factors and supported a 50-fold increase in RBC production efficiency. This image-informed bioprocess modeling framework leverages spatiotemporal niche information to enhance biochemical factor utilization and improve cell manufacturing in 3D systems. Impact statement Three-dimensional (3D) culture systems are becoming increasingly important because they recapitulate the architecture and, consequently, physiological function of the target tissue/organ. Design and optimization of these 3D biomanufacturing platforms require evaluation of in situ spatiotemporal information. We have developed an integrated experimental-computational framework that captures the spatiotemporal distribution of cells, nutrients, and cytokines within a marrow biomimicry perfusion bioreactor. The model simulated biochemical factor utilization and guided the design of an improved second-generation bioreactor that achieved 50-fold increase in RBC production with improved cost efficiency. Such a modeling framework provides an essential platform for the optimization of 3D biomanufacturing systems.

The Effects of COVID-19 on the Placenta During Pregnancy.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. The virus primarily affects the lungs where it induces respiratory distress syndrome ranging from mild to acute, however, there is a growing body of evidence supporting its negative effects on other system organs that also carry the ACE2 receptor, such as the placenta. The majority of newborns delivered from SARS-CoV-2 positive mothers test negative following delivery, suggesting that there are protective mechanisms within the placenta. There appears to be a higher incidence of pregnancy-related complications in SARS-CoV-2 positive mothers, such as miscarriage, restricted fetal growth, or still-birth. In this review, we discuss the pathobiology of COVID-19 maternal infection and the potential adverse effects associated with viral infection, and the possibility of transplacental transmission.

A quantitative analysis of cell bridging kinetics on a scaffold using computer vision algorithms.

Tissue engineering involves the seeding of cells into a structural scaffolding to regenerate the architecture of damaged or diseased tissue. To effectively design a scaffold, an understanding of how cells collectively sense and react to the geometry of their local environment is needed. Advances in the development of melt electro-writing have allowed micron and submicron polymeric fibres to be accurately printed into porous, complex and three-dimensional structures. By using melt electrowriting, we created a geometrically relevant in vitro scaffold model to study cellular spatial-temporal kinetics. These scaffolds were paired with custom computer vision algorithms to investigate cell nuclei, cell membrane actin and scaffold fibres over different pore sizes (200-600 µm) and time points (28 days). We find that cells proliferated much faster in the smaller (200 µm) pores which halved the time until confluence versus larger (500 and 600 µm) pores. Our analysis of stained actin fibres revealed that cells were highly aligned to the fibres and the leading edge of the pore filling front, and we found that cells behind the leading edge were not aligned in any particular direction. This study provides a systematic understanding of cellular spatial temporal kinetics within a 3D in vitro model to inform the design of more effective synthetic tissue engineering scaffolds for tissue regeneration. STATEMENT OF SIGNIFICANCE: Advances in the development of melt electro-writing have allowed micron and submicron polymeric fibres to be accurately printed into porous, complex and three-dimensional structures. By using melt electrowriting, we created a geometrically relevant in vitro model to study cellular spatial-temporal kinetics to provide a systematic understanding of cellular spatial temporal kinetics within a 3D in vitro model. The insights presented in this work help to inform the design of more effective synthetic tissue engineering scaffolds by reducing cell culture time; which is valuable information for the implant or lab-grown-meat industries.

Model-based data analysis of tissue growth in thin 3D printed scaffolds.

Tissue growth in three-dimensional (3D) printed scaffolds enables exploration and control of cell behaviour in more biologically realistic geometries than that allowed by traditional 2D cell culture. Cell proliferation and migration in these experiments have yet to be explicitly characterised, limiting the ability of experimentalists to determine the effects of various experimental conditions, such as scaffold geometry, on cell behaviour. We consider tissue growth by osteoblastic cells in melt electro-written scaffolds that comprise thin square pores with sizes that were deliberately increased between experiments. We collect highly detailed temporal measurements of the average cell density, tissue coverage, and tissue geometry. To quantify tissue growth in terms of the underlying cell proliferation and migration processes, we introduce and calibrate a mechanistic mathematical model based on the Porous-Fisher reaction-diffusion equation. Parameter estimates and uncertainty quantification through profile likelihood analysis reveal consistency in the rate of cell proliferation and steady-state cell density between pore sizes. This analysis also serves as an important model verification tool: while the use of reaction-diffusion models in biology is widespread, the appropriateness of these models to describe tissue growth in 3D scaffolds has yet to be explored. We find that the Porous-Fisher model is able to capture features relating to the cell density and tissue coverage, but is not able to capture geometric features relating to the circularity of the tissue interface. Our analysis identifies two distinct stages of tissue growth, suggests several areas for model refinement, and provides guidance for future experimental work that explores tissue growth in 3D printed scaffolds.

A deep learning method for automatic segmentation of the bony orbit in MRI and CT images.

This paper proposes a fully automatic method to segment the inner boundary of the bony orbit in two different image modalities: magnetic resonance imaging (MRI) and computed tomography (CT). The method, based on a deep learning architecture, uses two fully convolutional neural networks in series followed by a graph-search method to generate a boundary for the orbit. When compared to human performance for segmentation of both CT and MRI data, the proposed method achieves high Dice coefficients on both orbit and background, with scores of 0.813 and 0.975 in CT images and 0.930 and 0.995 in MRI images, showing a high degree of agreement with a manual segmentation by a human expert. Given the volumetric characteristics of these imaging modalities and the complexity and time-consuming nature of the segmentation of the orbital region in the human skull, it is often impractical to manually segment these images. Thus, the proposed method provides a valid clinical and research tool that performs similarly to the human observer.

Frugal 3D scanning using smartphones provides an accessible framework for capturing the external ear.

Three-dimensional (3D) scanning technologies, such as medical imaging and surface scanning, have important applications for capturing patient anatomy to create personalised prosthetics. Digital approaches for capturing anatomical detail as opposed to traditional, invasive impression techniques significantly reduces turnaround times and lower production costs while still maintaining the high aesthetic quality of the end product. While previous case studies utilise expensive 3D scanning and modelling frameworks, their clinical translation is limited due to high equipment costs. In this study, we develop and validate a low-cost framework for clinical 3D scanning of the external ear using photogrammetry and a smartphone camera. We recruited five novice operators who watched an instructional video before scanning 20 healthy adult participant ears who did not have microtia. Our results show that the smartphone-based photogrammetry methodology produces 3D scans of the external ear that were accurate to (1.5 ± 0.4) mm and were (71 ± 14) % complete compared with those from a gold standard reference scanner, with no significant difference observed between operators. A moderate to strong interrater reliability was determined for all novice operators, suggesting that all novice operators were able to capture repeatable scans. The development of this smartphone photogrammetry approach has the potential to provide a non-invasive, inexpensive and accessible means to capture patient morphology for use in clinical assessment and personalised device manufacture, specifically for ear prostheses. We also demonstrate that inexperienced operators can rapidly learn and apply smartphone photogrammetry for accurate and reliable scans of the external ear with important applications for future clinical translation.

Detection of clustered anomalies in single-voxel morphometry as a rapid automated method for identifying intracranial aneurysms.

Unruptured intracranial aneurysms (UIAs) are prevalent neurovascular anomalies which, in rare circumstances, rupture to cause a catastrophic subarachnoid haemorrhage. Although surgical management can reduce rupture risk, the majority of UIAs exist undiscovered until rupture. Current clinical practice in the detection of UIAs relies heavily on manual radiological review of standard imaging modalities. Recent computer-aided UIA diagnoses can sensitively detect and measure UIAs within cranial angiograms but remain limited to low specificities whose output also requires considerable radiologist interpretation not amenable to broad screening efforts. To address these limitations, we have developed a novel automatic pipeline algorithm which inputs medical images and outputs detected UIAs by characterising single-voxel morphometry of segmented neurovasculature. Once neurovascular anatomy of a specified resolution is segmented, correlations between voxel-specific morphometries are estimated and spatially-clustered outliers are identified as UIA candidates. Our automated solution detects UIAs within magnetic resonance angiograms (MRA) at unmatched 86% specificity and 81% sensitivity using 3 min on a conventional laptop. Our approach does not rely on interpatient comparisons or training datasets which could be difficult to amass and process for rare incidentally discovered UIAs within large MRA files, and in doing so, is versatile to user-defined segmentation quality, to detection sensitivity, and across a range of imaging resolutions and modalities. We propose this method as a unique tool to aid UIA screening, characterisation of abnormal vasculature in at-risk patients, morphometry-based rupture risk prediction, and identification of other vascular abnormalities.

An advanced prosthetic manufacturing framework for economic personalised ear prostheses.

Craniofacial prostheses are commonly used to restore aesthetics for those suffering from malformed, damaged, or missing tissue. Traditional fabrication is costly, uncomfortable for the patient, and laborious; involving several hours of hand-crafting by a prosthetist, with the results highly dependent on their skill level. In this paper, we present an advanced manufacturing framework employing three-dimensional scanning, computer-aided design, and computer-aided manufacturing to efficiently fabricate patient-specific ear prostheses. Three-dimensional scans were taken of ears of six participants using a structured light scanner. These were processed using software to model the prostheses and 3-part negative moulds, which were fabricated on a low-cost desktop 3D printer, and cast with silicone to produce ear prostheses. The average cost was approximately $3 for consumables and $116 for 2 h of labour. An injection method with smoothed 3D printed ABS moulds was also developed at a cost of approximately $155 for consumables and labour. This contrasts with traditional hand-crafted prostheses which range from $2,000 to $7,000 and take around 14 to 15 h of labour. This advanced manufacturing framework provides potential for non-invasive, low cost, and high-accuracy alternative to current techniques, is easily translatable to other prostheses, and has potential for further cost reduction.

Cell proliferation and migration explain pore bridging dynamics in 3D printed scaffolds of different pore size.

Tissue growth in bioscaffolds is influenced significantly by pore geometry, but how this geometric dependence emerges from dynamic cellular processes such as cell proliferation and cell migration remains poorly understood. Here we investigate the influence of pore size on the time required to bridge pores in thin 3D-printed scaffolds. Experimentally, new tissue infills the pores continually from their perimeter under strong curvature control, which leads the tissue front to round off with time. Despite the varied shapes assumed by the tissue during this evolution, we find that time to bridge a pore simply increases linearly with the overall pore size. To disentangle the biological influence of cell behaviour and the mechanistic influence of geometry in this experimental observation, we propose a simple reaction-diffusion model of tissue growth based on Porous-Fisher invasion of cells into the pores. First, this model provides a good qualitative representation of the evolution of the tissue; new tissue in the model grows at an effective rate that depends on the local curvature of the tissue substrate. Second, the model suggests that a linear dependence of bridging time with pore size arises due to geometric reasons alone, not to differences in cell behaviours across pores of different sizes. Our analysis suggests that tissue growth dynamics in these experimental constructs is dominated by mechanistic crowding effects that influence collective cell proliferation and migration processes, and that can be predicted by simple reaction-diffusion models of cells that have robust, consistent behaviours.

Design tools for patient specific and highly controlled melt electrowritten scaffolds.

Melt electrowriting (MEW) has grown in popularity in biofabrication research due to its ability to fabricate complex, high-precision networks of fibres. These fibres can mimic the morphology of a natural extracellular matrix, enabling tissue analogues for transplantation or personalised drug screening. To date, MEW has employed two different collector-plate modalities for the fabrication of constructs. Flat collector plates, typical of traditional 3D printing methods, allow for the layer-by-layer fabrication of 2D structures into complex 3D structures. Alternatively, rotating mandrels can be used for the creation of tubular scaffolds. However, unlike other additive manufacturing techniques that can immediately start and stop the extrusion of material during printing, MEW instead requires a continuous flow of polymer. Consequently, conventional g-code control software packages are unsuitable. To overcome this challenge, a suite of customised pattern generation software tools have been developed to enable the design of MEW scaffolds with highly-controlled geometry, including crosshatch, gradient porosity, tubular, and patient-specific configurations. The high level of design control using this approach enables the production of scaffolds with highly adaptable mechanical properties, as well as the potential to influence biological properties for cell attachment and proliferation.

Engineering inkjet bioprinting processes toward translational therapies.

Bioprinting is the assembly of three-dimensional (3D) tissue constructs by layering cell-laden biomaterials using additive manufacturing techniques, offering great potential for tissue engineering and regenerative medicine. Such a process can be performed with high resolution and control by personalized or commercially available inkjet printers. However, bioprinting's clinical translation is significantly limited due to process engineering challenges. Upstream challenges include synthesis, cellular incorporation, and functionalization of "bioinks," and extrusion of print geometries. Downstream challenges address sterilization, culture, implantation, and degradation. In the long run, bioinks must provide a microenvironment to support cell growth, development, and maturation and must interact and integrate with the surrounding tissues after implantation. Additionally, a robust, scaleable manufacturing process must pass regulatory scrutiny from regulatory bodies such as U.S. Food and Drug Administration, European Medicines Agency, or Australian Therapeutic Goods Administration for bioprinting to have a real clinical impact. In this review, recent advances in inkjet-based 3D bioprinting will be presented, emphasizing on biomaterials available, their properties, and the process to generate bioprinted constructs with application in medicine. Current challenges and the future path of bioprinting and bioinks will be addressed, with emphasis in mass production aspects and the regulatory framework bioink-based products must comply to translate this technology from the bench to the clinic.