Elastic properties of 2D auxetic honeycomb structures- a review

The research field of auxetics, materials or structures exhibiting a negative Poisson's ratio, has received attention because of the unusually advantageous material properties that can be achieved with it, such as high indentation resistance and high shear resistance. In the past decades, the theoretical understanding of different factors that can lead to an auxetic behaviour has advanced greatly, resulting in a rapid increase in the number and type of the structures designed to exhibit this behaviour. These now exploit a number of different mechanisms, providing a large selection of properties which can be tailored for the specific needs. This review aims to describes the auxetic structures that have currently been identified and designed, describing the different approaches utilised to define their mechanical behaviour and analysing their structural properties, limitations, and potential field of application. In particular, the focus lies on the major works within the field, discussing their limitations and addressing works done to complement them

Aortic Arch Phenotypes in Double Outlet Right Ventricle (DORV)—Implications for Surgery and Multi-Modal Imaging

Abnormal aortic arches (AAAs) cover a spectrum of malformations, including abnormal laterality, branching patterns, and flow-limiting narrowing, which themselves vary from tubular hypoplasia, through discrete coarctation, to complete interruption of the arch. Neonatal surgery within the first days of life is necessary for most of these morphologies. Patch aortoplasty is widely used as it can offer a good haemodynamic result, being tailored to each combination of presenting pathologies. Our study hypothesis was that arch malformations are frequent in DORV and exhibit a plethora of phenotypes. We reviewed 54 post-mortem heart specimens from the UCL Cardiac Archive, analysing morphological features that would potentially influence the surgical repair, and taking relevant measurements of surgical importance. AAAs were found in half of the specimens, including 22.2% with aortic arch narrowing. In total, 70% and 30% of narrow arches had a subpulmonary and subaortic interventricular defect, respectively. Z-scores were significantly negative for all cases with tubular hypoplasia. We concluded that arch malformations are a common finding among hearts with DORV. Surgery on the neonatal aortic arch in DORV, performed in conjunction with other interventions that aim to balance pulmonary to systemic flow (Qp/Qs), should be anticipated and form an important part of multi-modal imaging

Patient-Specific Modelling and Parameter Optimisation to Simulate Dilated Cardiomyopathy in Children

PURPOSE: Lumped parameter modelling has been widely used to simulate cardiac function and physiological scenarios in cardiovascular research. Whereas several patient-specific lumped parameter models have been reported for adults, there is a limited number of studies aiming to simulate cardiac function in children. The aim of this study is to simulate patient-specific cardiovascular dynamics in children diagnosed with dilated cardiomyopathy, using a lumped parameter model. METHODS: Patient data including age, gender, heart rate, left and right ventricular end-systolic and end-diastolic volumes, cardiac output, systolic and diastolic aortic pressures were collected from 3 patients at Great Ormond Street Hospital for Children, London, UK. Ventricular geometrical data were additionally retrieved from cardiovascular magnetic resonance images. 23 parameters in the lumped parameter model were optimised to simulate systolic and diastolic pressures, end-systolic and end-diastolic volumes, cardiac output and left and right ventricular diameters in the patients using a direct search optimisation method. RESULTS: Difference between the haemodynamic parameters in the optimised cardiovascular system models and clinical data was less than 10%. CONCLUSION: The simulation results show the potential of patient-specific lumped parameter modelling to simulate clinical cases. Modelling patient specific cardiac function and blood flow in the paediatric patients would allow us to evaluate a variety of physiological scenarios and treatment options

3D Printing Cardiovascular Anatomy: A Single-Centre Experience

This chapter presents the experience of the cardiac engineering team within the Centre for Cardiovascular Imaging at Great Ormond Street Hospital for Children (London, UK) in using three-dimensional (3D) printing technology. 3D models can serve different functions towards implementing a patient-specific approach for studying and potentially treating congenital heart disease (CHD). In order to showcase different potential applications, this chapter discusses not only clinical case studies and engineering experiments but also the potential for translation through patients and public involvement and engagement (PPI/E)

Finite Element Analysis to Study Percutaneous Heart Valves

Communications engineering / telecommunication

Image2Flow: A hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data

Computational fluid dynamics (CFD) can be used for evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep learning model to both generate patient-specific volume-meshes of the pulmonary artery from 3D cardiac MRI data and directly estimate CFD flow fields. This study used 135 3D cardiac MRIs from both a public and private dataset. The pulmonary arteries in the MRIs were manually segmented and converted into volume-meshes. CFD simulations were performed on ground truth meshes and interpolated onto point-point correspondent meshes to create the ground truth dataset. The dataset was split 85/10/15 for training, validation and testing. Image2Flow, a hybrid image and graph convolutional neural network, was trained to transform a pulmonary artery template to patient-specific anatomy and CFD values. Image2Flow was evaluated in terms of segmentation and accuracy of CFD predicted was assessed using node-wise comparisons. Centerline comparisons of Image2Flow and CFD simulations performed using machine learning segmentation were also performed. Image2Flow achieved excellent segmentation accuracy with a median Dice score of 0.9 (IQR: 0.86-0.92). The median node-wise normalized absolute error for pressure and velocity magnitude was 11.98% (IQR: 9.44-17.90%) and 8.06% (IQR: 7.54-10.41), respectively. Centerline analysis showed no significant difference between the Image2Flow and conventional CFD simulated on machine learning-generated volume-meshes. This proof-of-concept study has shown it is possible to simultaneously perform patient specific volume-mesh based segmentation and pressure and flow field estimation. Image2Flow completes segmentation and CFD in ~205ms, which ~7000 times faster than manual methods, making it more feasible in a clinical environment.Comment: 22 pages, 7 figures, 3 table

Reconstruction of fetal and infant anatomy using rapid prototyping of post-mortem MR images

OBJECTIVES: The recent decline in autopsy rates and lack of human anatomical material donated for research and training has resulted in issues for medical training in the United Kingdom. This study aims to examine the feasibility of making accurate three-dimensional (3D) models of the human body and visceral organs using post-mortem magnetic resonance (MR) imaging and rapid prototyping. METHODS: We performed post-mortem MR imaging using a 3D T2-weighted sequence in 11 fetuses and infants, before autopsy, using either a 1.5-T or 9.4-T MR scanner. Internal organs were reconstructed in silico and 3D models were created by rapid prototyping. RESULTS: The median gestation of fetuses was 20 (range 19-30) weeks and the median age of infants was 12 (range 8-16) weeks. Models created by rapid prototyping accurately depicted structural abnormalities and allowed clear visualisation of 3D relationships. CONCLUSIONS: Accurate 3D modelling of anatomical features from post-mortem imaging in fetuses and infants is feasible. These models could have a large number of medical applications, including improved parental counselling, invaluable teaching resources and significant medico-legal applications to demonstrate disease or injury, without the need to show actual autopsy photographs

A Storable Mediatorless Electrochemical Biosensor for Herbicide Detection.

A novel mediatorless photo-bioelectrochemical sensor operated with a biofilm of the cyanobacterium Synechocystis PCC6803 wt. for herbicide detection with long term stability (>20 days) was successfully developed and tested. Photoanodic current generation was obtained in the absence of artificial mediators. The inhibitory effect on photocurrent of three commonly used herbicides (i.e., atrazine, diuron, and paraquat) was used as a means of measuring their concentrations in aqueous solution. The injection of atrazine and diuron into the algal medium caused an immediate photocurrent drop due to the inhibition of photosynthetic electron transport. The detected concentrations were suitable for environmental analysis, as revealed by a comparison with the freshwater quality benchmarks set by the Environmental Protection Agency of the United States (US EPA). In contrast, paraquat caused an initial increase (~2 h) of the photocurrent effect of about 200%, as this compound can act as a redox mediator between the cells and the anode. A relatively long-term stability of the biosensor was demonstrated, by keeping anodes colonized with cyanobacterial biofilm in the dark at 4 °C. After 22 days of storage, the performance in terms of the photocurrent was comparable with the freshly prepared biosensor. This result was confirmed by the measurement of chlorophyll content, which demonstrated preservation of the cyanobacterial biofilm. The capacity of this biosensor to recover after a cold season or other prolonged environmental stresses could be a key advantage in field applications, such as in water bodies and agriculture. This study is a step forward in the biotechnological development and implementation of storable mediatorless electrochemical biosensors for herbicide detection