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.

Whole transcriptome profiling of placental pathobiology in SARS-CoV-2 pregnancies identifies placental dysfunction signatures.

Objectives: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a 'preeclampsia-like syndrome'. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection. Methods: We utilised whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n = 7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n = 9). Results: Through comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified SARS-CoV-2 to promote signatures associated with hypoxia and placental dysfunction. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15, CRH) and preeclampsia (FLT1, EGFR, KISS1, PAPPA2) were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension and inflammation were also enriched in SARS-CoV-2 samples compared to uninfected controls. Conclusions: Our findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.

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.

Reproducibility of the computational fluid dynamic analysis of a cerebral aneurysm monitored over a decade.

Computational fluid dynamics (CFD) simulations are increasingly utilised to evaluate intracranial aneurysm (IA) haemodynamics to aid in the prediction of morphological changes and rupture risk. However, these models vary and differences in published results warrant the investigation of IA-CFD reproducibility. This study aims to explore sources of intra-team variability and determine its impact on the aneurysm morphology and CFD parameters. A team of four operators were given six sets of magnetic resonance angiography data spanning a decade from one patient with a middle cerebral aneurysm. All operators were given the same protocol and software for model reconstruction and numerical analysis. The morphology and haemodynamics of the operator models were then compared. The segmentation, smoothing factor, inlet and outflow branch lengths were found to cause intra-team variability. There was 80% reproducibility in the time-averaged wall shear stress distribution among operators with the major difference attributed to the level of smoothing. Based on these findings, it was concluded that the clinical applicability of CFD simulations may be feasible if a standardised segmentation protocol is developed. Moreover, when analysing the aneurysm shape change over a decade, it was noted that the co-existence of positive and negative values of the wall shear stress divergence (WSSD) contributed to the growth of a daughter sac.

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.

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.

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.

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 impact of plasma 25-hydroxyvitamin D on pulmonary function and exercise physiology in cystic fibrosis: A multicentre retrospective study.

BACKGROUND: A 25-hydroxyvitamin D (25OHD) may exert immunomodulatory effects on respiratory health, which may translate to improvements in exercise physiology. Thus, we aimed to investigate whether plasma 25OHD is associated with lung function and aerobic fitness in people with cystic fibrosis (pwCF). METHODS: A multicentre retrospective review of pwCF (> 9 years old) attending the Royal Hospital for Sick Children (Edinburgh) or Wessex CF-Unit (Southampton) was performed between July 2017 and October 2019. Demographic and clinical data were collected. Plasma 25OHD measured closest in time to clinical cardiopulmonary exercise testing and/or spirometry [forced expiratory volume (FEV1 )% predicted] was recorded. Pancreatic insufficiency was diagnosed based on faecal elastase of < 100 µg g-1 . We performed multiple-regression analysis with aerobic fitness outcomes [peak oxygen uptake (VO2 peak )] and FEV1 % predicted as primary outcomes. RESULTS: Ninety pwCF [mean ± SD age: 19.1 ± 8.6 years, 54 (60%) children, 48 (53%) males and 88 (98%) Caucasian] were included. 25OHD deficiency and insufficiency was 15 (17%) and 44 (49%), respectively. 25OHD deficiency and insufficiency was significantly associated with pancreatic insufficiency (χ2  = 4.8, p = 0.02). Plasma 25OHD was not significantly associated with FEV1 % predicted (r2  = 0.06, p = 0.42, 95% CI = -0.09 to 0.19) or VO2 peak (r2  = 0.04, p = 0.07, 95% CI = -011 to 0.005) in all pwCF. However, 25OHD was significantly associated with both FEV1 % (r2  = 0.15, p = 0.02, 95% CI = 1.99-2.64) and VO2 peak (r2  = 0.13, p = 0.05, 95% CI = -0.26 to -0.005) in the paediatric cohort. CONCLUSIONS: We showed that 25OHD is associated with improved lung function and aerobic fitness in children and adolescents with CF. Mechanistic and high-quality prospective studies including both lung function and aerobic fitness as primary outcomes are now warranted.

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.

Using a learning health system to understand the mismatch between medicines supply and actual medicines use among adults with cystic fibrosis.

BACKGROUND: Studies in separate cohorts suggest possible discrepancies between inhaled medicines supplied (median 50-60%) and medicines used (median 30-40%). We performed the first study that directly compares CF medicine supply against use to identify the cost of excess medicines supply. METHODS: This cross-sectional study included participants from 12 UK adult centres with ≥1 year of continuous adherence data from data-logging nebulisers. Medicine supply was measured as medication possession ratio (MPR) for a 1-year period from the first suitable supply date. Medicine use was measured as electronic data capture (EDC) adherence over the same period. The cost of excess medicines was calculated as whole excess box(es) supplied after accounting for the discrepancy between EDC adherence and MPR with 20% contingency. RESULTS: Among 275 participants, 133 (48.4%) were females and mean age was 30 years (95% CI 29-31 years). Median EDC adherence was 57% (IQR 23-86%), median MPR was 74% (IQR 46-96%) and the discrepancy between measures was median 14% (IQR 2-29%). Even with 20% contingency, mean potential cost of excess medicines was £1,124 (95% CI £855-1,394), ranging from £183 (95% CI £29-338) for EDC adherence ≥80% to £2,017 (95% CI £1,507-2,526) for EDC adherence <50%. CONCLUSIONS: This study provides a conservative estimate of excess inhaled medicines supply cost among adults with CF in the UK. The excess supply cost was highest among those with lowest EDC adherence, highlighting the importance of adherence support and supplying medicine according to actual use. MPR provides information about medicine supply but over-estimates actual medicine use.

Prospectively predicting Pseudomonas aeruginosa infection/s using routine data from the UK cystic fibrosis register.

RATIONALE AND AIMS: Lung health of people with cystic fibrosis (PwCF) can be preserved by daily use of inhaled therapy. Adherence to inhaled therapy, therefore, provides an important process measure to understand the success of care and can be used as a quality indicator. Defining adherence is problematic, however, since the number of prescribed treatments varies considerably between PwCF. The problem is less pronounced among those with Pseudomonas aeruginosa (PA), for whom at least three daily doses of nebulized therapy should be prescribed and who thus constitute a more homogeneous group. The UK CF Registry provides routine data on PA status, but data are only available 12 months after collection. In this study, we aim to prospectively identify contemporary PA status from historic registry data. METHOD: UK CF Registry data from 2011 to 2015 for PwCF aged ≥16 was used to determine a pragmatic prediction rule for identifying contemporary PA status using historic registry data. Accuracy of three different prediction rules was assessed using the positive predictive value (PPV). The number and proportion of adults predicted to have PA infection were determined overall and per center for the selected prediction rule. Known characteristics linked to PA status were explored to ensure the robustness of the prediction rule. RESULTS: Having CF Registry defined chronic PA status in the two previous years is the selected definition to predict a patient will have PA infection within the current year (population-level PPV = 96%-97%, centre level PPV = 85%-100%). This approach provides a subset of data between 1852 and 1872 patients overall and a range of 8 to 279 patients per center. CONCLUSION: Historic registry data can be used to contemporaneously identify a subgroup of patients with chronic PA. Since this patient group has a narrower treatment schedule, this can facilitate a better benchmarking of adherence across centers.

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.