Cross-sectional chest circumference and shape development in infants.

Objective: This study investigates the development of the thoracic cross-section at the nipple line level during the early stages of life. Unlike the descriptive awareness regarding chest development course, there exist no quantitative references concerning shape, circumference and possible dependencies to age, gender or body weight. The proposed mathematical relations are expected to help create guidelines for more realistic modelling and potential detection of abnormalities.

Model Selection Based Algorithm in Neonatal Chest EIT.

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models.

Towards a thoracic conductive phantom for EIT.

Phantom experiments are a crucial step for testing new hardware or imaging algorithms for electrical impedance tomography (EIT) studies. However, constructing an accurate phantom for EIT research remains critical; some studies have attempted to model the skull and breasts, and even fewer, as yet, have considered the thorax. In this study, a critical comparison between the electrical properties (impedance) of three materials is undertaken: a polyurethane foam, a silicone mixture and a thermoplastic polyurethane filament.

Torso shape detection to improve lung monitoring.

Objective: Newborns with lung immaturity often require continuous monitoring and treatment of their lung ventilation in intensive care units, especially if born preterm. Recent studies indicate that electrical impedance tomography (EIT) is feasible in newborn infants and children, and can quantitatively identify changes in regional lung aeration and ventilation following alterations to respiratory conditions. Information on the patient-specific shape of the torso and its role in minimizing the artefacts in the reconstructed images can improve the accuracy of the clinical parameters obtained from EIT.

Detecting colorectal cancer using electrical impedance spectroscopy: an ex vivo feasibility study.

Objective: Colorectal cancer is the fourth most common cancer worldwide, with a lifetime risk of around 20%. Current techniques do not allow clinicians to objectively assess tissue abnormality during endoscopy and perioperatively. A method capable of objectively assessing samples in real time and which can be included in minimally invasive diagnostic and management strategies would be highly transformative.

Wearable sensors for patient-specific boundary shape estimation to improve the forward model for electrical impedance tomography (EIT) of neonatal lung function.

Electrical impedance tomography (EIT) could be significantly advantageous to continuous monitoring of lung development in newborn and, in particular, preterm infants as it is non-invasive and safe to use within the intensive care unit. It has been demonstrated that accurate boundary form of the forward model is important to minimize artefacts in reconstructed electrical impedance images. This paper presents the outcomes of initial investigations for acquiring patient-specific thorax boundary information using a network of flexible sensors that imposes no restrictions on the patient's normal breathing and movements.

Bioimpedance imaging: an overview of potential clinical applications.

Electrical Impedance Tomography (EIT) is an imaging technique based on multiple bio impedance measurements to produce a map (image) of impedance or changes in impedance across a region. Its origins lay in geophysics where it is still used to today. This review highlights potential clinical applications of EIT.

A comparison study of electrodes for neonate electrical impedance tomography.

Electrical impedance tomography (EIT) is an imaging technique that has the potential to be used for studying neonate lung function. The properties of the electrodes are very important in multi-frequency EIT (MFEIT) systems, particularly for neonates, as the skin cannot be abraded to reduce contact impedance. In this work, the impedance of various clinical electrodes as a function of frequency is investigated to identify the optimum electrode type for this application.

GREIT: a unified approach to 2D linear EIT reconstruction of lung images.

Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT).

Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography.

The development of diffuse optical tomography (DOT) instrumentation for neuroimaging of humans is challenging due to the large size and the geometry of the head and the desire to distinguish signals at different depths. One approach to this problem is to use dense imaging arrays that incorporate measurements at different source-detector distances. We previously developed a high-density DOT system that is able to obtain retinotopic measurements in agreement with functional magnetic resonance imaging and positron emission tomography.

Development of a neonate lung reconstruction algorithm using a wavelet AMG and estimated boundary form.

Objective, non-invasive measures of lung maturity and development, oxygen requirements and lung function, suitable for use in small, unsedated infants, are urgently required to define the nature and severity of persisting lung disease, and to identify risk factors for developing chronic lung problems. Disorders of lung growth, maturation and control of breathing are among the most important problems faced by the neonatologists. At present, no system for continuous monitoring of neonate lung function to reduce the risk of chronic lung disease in infancy in intensive care units exists.

Improving the finite element forward model of the human head by warping using elastic deformation.

As the use of realistic geometry in the forward model of electrical impedance tomography (EIT) of brain function appears to improve image reconstruction, the generation of patient-specific finite element meshes has been the subject of much recent work. This paper presents a more rapid method of generating more geometrically accurate finite element meshes of the human head by warping existing meshes such that the surface boundary beneath the electrodes closely matches that of the subject with minimal degradation to the quality of the mesh. Pre-existing meshes of spheres and adult head models incorporating key internal anatomical features are warped, using elastic deformation, to match a phantom latex tank incorporating a real skull.

Bacterial oxygenases: in vivo enzyme biosensors for organic pollutants.

An in vivo enzyme-based biosensor platform was developed that uses specific oxygenase enzymes to detect aromatic compounds in water. Bacteria capable of degrading highly reduced hydrocarbons initiate substrate oxidation using well-characterised oxygenase enzymes, which due to their specificity, stability and high activity can be applied in vivo as biosensor components. Oxygenase enzyme activity was determined in vivo using BD Oxygen Biosensor plates to measure oxygenase-mediated oxygen depletion in the presence of specific aromatic analytes.

A resazurin-based biosensor for organic pollutants.

A new rapid biosensor method employing the dye resazurin as an indicator of bacterial respiration has been developed to provide a rapid, facile and specific biosensor for environmental contaminants that does not rely on genetic modification techniques, is suitable for a high-throughput multiwell format, and is ideally suited to resource-constrained environmental monitoring situations. This whole-cell biosensor has been applied to the test analyte toluene using natural toluene-degrading bacteria as the biological component and is competitive with more complex recombinant approaches. The redox-driven biosensor is dependent on the catabolism of a specific compound, concomitantly reducing the redox indicator resazurin to provide the analytical signal in a whole-cell biosensor assay.

Generating accurate finite element meshes for the forward model of the human head in EIT.

The use of realistic anatomy in the model used for image reconstruction in EIT of brain function appears to confer significant improvements compared to geometric shapes such as a sphere. Accurate model geometry may be achieved by numerical models based on magnetic resonance images (MRIs) of the head, and this group has elected to use finite element meshing (FEM) as it enables detailed internal anatomy to be modelled and has the capability to incorporate information about tissue anisotropy. In this paper a method for generating accurate FEMs of the human head is presented where MRI images are manually segmented using custom adaptation of industry standard commercial design software packages.

Quantification of the Pseudomonas population in New Zealand soils by fluorogenic PCR assay and culturing techniques.

The genus Pseudomonas contains fast-growing nutritionally versatile bacteria that are able to utilize a wide variety of carbon sources. The ubiquity of the genus has been highlighted by conventional microbiology and the genus is well represented in collections of cultured bacteria. Here we evaluate the Pseudomonas population in New Zealand soils by comparing a culture-independent (real-time PCR combined with fluorescent TaqMan technology) with a culture-dependent (Gould's S1) population estimate.

Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method.

Electrical impedance tomography (EIT) is a recently developed technique which enables the internal conductivity of an object to be imaged using rings of external electrodes. In a recent study, EIT during cortical evoked responses showed encouraging changes in the raw impedance measurements, but reconstructed images were noisy. A simplified reconstruction algorithm was used which modelled the head as a homogeneous sphere.

Solving the forward problem in electrical impedance tomography for the human head using IDEAS (integrated design engineering analysis software), a finite element modelling tool.

If electrical impedance tomography is to be used as a clinical tool, the image reconstruction algorithms must yield accurate images of impedance changes. One of the keys to producing an accurate reconstructed image is the inclusion of prior information regarding the physical geometry of the object. To achieve this, many researchers have created tools for solving the forward problem by means of finite element methods (FEMs).