Anatomy-guided multi-resolution image reconstruction in PET

In this paper, we propose positron emission tomography (PET) image reconstruction using a multi-resolution triangular mesh. The mesh can be adapted based on patient specific anatomical information that can be in the form of a computed tomography (CT) or magnetic resonance imaging (MRI) image in the hybrid imaging systems. The triangular mesh can be adapted to high resolution in localized anatomical regions of interest (ROI) and made coarser in other regions, leading to an imaging model with high resolution in the ROI with clearly reduced number of degrees of freedom compared to a conventional uniformly dense imaging model. We compare maximum likelihood expectation maximization (MLEM) reconstructions with the multi-resolution model to reconstructions using a uniformly dense mesh, a sparse mesh and regular rectangular pixel mesh. Two simulated cases are used in the comparison, with the first one using the NEMA image quality phantom and the second the XCAT human phantom. When compared to the results with the uniform imaging models, the locally refined multi-resolution mesh retains the accuracy of the dense mesh reconstruction in the ROI while being faster to compute than the reconstructions with the uniformly dense mesh. The locally dense multi-resolution model leads also to more accurate reconstruction than the pixel-based mesh or the sparse triangular mesh. The findings suggest that triangular multi-resolution mesh, which can be made patient and application specific, is a potential alternative for pixel-based reconstruction.

Dual-Modal Electrical Imaging of Two-Phase Flow-Experimental Evaluation of the State Estimation Approach

Accurate measurement of two-phase flow quantities is essential for managing production in many industries. However, the inherent complexity of two-phase flow often makes estimating these quantities difficult, necessitating the development of reliable techniques for quantifying two-phase flow. In this paper, we investigated the feasibility of using state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flow. We utilized electromagnetic flow tomography (EMFT) to estimate velocity fields and electrical tomography (ET) to determine phase fraction distributions. In state estimation, the contribution of the velocity field to the temporal evolution of the phase fraction distribution was accounted for by approximating the process with a convection-diffusion model. The extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) were used to reconstruct the temporally evolving velocity and phase fraction distributions, which were further used to estimate the volumetric flow rates of the phases. Experimental results on a laboratory setup showed that the FIKS approach outperformed the conventional stationary reconstructions, with the average relative errors of the volumetric flow rates of oil and water being less than 4%. The FIKS approach also provided feasible uncertainty estimates for the velocity, phase fraction, and volumetric flow rate of the phases, enhancing the reliability of the state estimation approach.

A Review on Fast Tomographic Imaging Techniques and Their Potential Application in Industrial Process Control

With the ongoing digitalization of industry, imaging sensors are becoming increasingly important for industrial process control. In addition to direct imaging techniques such as those provided by video or infrared cameras, tomographic sensors are of interest in the process industry where harsh process conditions and opaque fluids require non-intrusive and non-optical sensing techniques. Because most tomographic sensors rely on complex and often time-multiplexed excitation and measurement schemes and require computationally intensive image reconstruction, their application in the control of highly dynamic processes is often hindered. This article provides an overview of the current state of the art in fast process tomography and its potential for use in industry.

An Electromagnetic Time-Reversal Imaging Algorithm for Moisture Detection in Polymer Foam in an Industrial Microwave Drying System

Microwave tomography (MWT) based control is a novel idea in industrial heating systems for drying polymer foam. In this work, an X-band MWT module is designed and developed using a fixed antenna array configuration and integrated with the HEPHAISTOS industrial heating system. A decomposition of the time-reversal operator (DORT) algorithm with a proper Green’s function of multilayered media is utilized to localize the moisture location. The derived Green’s function can be applied to the media with low or high contrast layers. It is shown that the time-reversal imaging (TRI) with the proposed Green’s function can be applied to the multilayered media with a moderately rough surface. Moreover, a single frequency TRI is proposed to decrease the measurement time. Numerical results for different moisture scenarios are presented to demonstrate the efficacy of the proposed method. The developed method is then tested on the experimental data for different moisture scenarios from our developed MWT experimental prototype. Image reconstruction results show promising capabilities of the TRI algorithm in estimating the moisture location in the polymer foam.

Model reduction in acoustic inversion by artificial neural network

In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model is a prominent factor for high-quality image reconstruction, but it can make computations far too time-consuming in many applications. Using approximate forward models, it is possible to speed up the computations, but the quality of the reconstruction may have to be compromised. In this paper, a neural network-based approach is proposed that can compensate for modelling errors caused by the approximate forward models. The approach is tested with various different imaging scenarios in a simulated two-dimensional domain. The results show that with fairly small training datasets, the proposed approach can be utilized to approximate the modelling errors, and to significantly improve the image reconstruction quality in ultrasound tomography, compared to commonly used inversion algorithms.

System Identification of Conveyor Belt Microwave Drying Process of Polymer Foams Using Electrical Capacitance Tomography

The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers. Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor. The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process.

Microwave Tomography Using Neural Networks for Its Application in an Industrial Microwave Drying System

The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities.

Costs of multidrug-resistant TB treatment in Finland and Estonia affected by the 2019 WHO guidelines

BACKGROUND:

Multidrug-resistant TB (MDR-TB) is a growing problem in the effort to end the global TB epidemic. In 2019, the WHO adopted a new standardised regiment for MDR-TB, consisting of only oral medications.

METHODS:

We estimated the impact of the new guidelines on the costs of TB treatment in Estonia and Finland. For both countries, the costs of the two most common new drug regimens were calculated, including drug costs, as well as care- and monitoring-related costs.

RESULTS:

In Turku, Finland, treatment costs with the old regimen were €178,714; this could either increase by 10% or decrease by 18%, depending on the duration of bedaquiline use (6 months vs. 20 months). In Estonia, treatment costs with the old regimen were €33,664, whereas the new regimens were associated with a 40% increase in overall costs.

CONCLUSIONS:

The 2019 WHO guidelines have led to significant changes in the costs of MDR-TB treatment in Finland and Estonia. These changes depend mostly on the drug regimen administered and on care-related practices, with important differences between countries and even within the same country due to local practices.

OMEGA-open-source emission tomography software

In this paper we present OMEGA, an open-source software, for efficient and fast image reconstruction in positron emission tomography (PET). OMEGA uses the scripting language of MATLAB and GNU Octave allowing reconstruction of PET data with a MATLAB or GNU Octave interface. The goal of OMEGA is to allow easy and fast reconstruction of any PET data, and to provide a computationally efficient, easy-access platform for development of new PET algorithms with built-in forward and backward projection operations available to the user as a MATLAB/Octave class. OMEGA also includes direct support for GATE simulated data, facilitating easy evaluation of the new algorithms using Monte Carlo simulated PET data. OMEGA supports parallel computing by utilizing OpenMP for CPU implementations and OpenCL for GPU allowing any hardware to be used. OMEGA includes built-in function for the computation of normalization correction and allows several other corrections to be applied such as attenuation, randoms or scatter. OMEGA includes several different maximum-likelihood and maximum a posteriori (MAP) algorithms with several different priors. The user can also input their own priors to the built-in MAP functions. The image reconstruction in OMEGA can be computed either by using an explicitly computed system matrix or with a matrix-free formalism, where the latter can be accelerated with OpenCL. We provide an overview on the software and present some examples utilizing the different features of the software.

Data-Driven Regularization Parameter Selection in Dynamic MRI

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are obtained from the measurement data for temporal regularization and from a reference image for spatial regularization. Two formulations are proposed. Simultaneous search for a parameter pair yielding expected sparsity in both domains (S-surface), and a sequential parameter selection using the S-curve method (Sequential S-curve). The approaches are evaluated using simulated and experimental DCE-MRI. In the simulated test case, both methods produce a parameter pair and reconstruction that is close to the root mean square error (RMSE) optimal pair and reconstruction. In the experimental test case, the methods produce almost equal parameter selection, and the reconstructions are of high perceived quality. Both methods lead to a highly feasible selection of the regularization parameters in both test cases while the sequential method is computationally more efficient.

Reconstruction of velocity fields in electromagnetic flow tomography

Electromagnetic flow meters (EMFMs) are the gold standard in measuring flow velocity in process industry. The flow meters can measure the mean flow velocity of conductive liquids and slurries. A drawback of this approach is that the velocity field cannot be determined. Asymmetric axial flows, often encountered in multiphase flows, pipe elbows and T-junctions, are problematic and can lead to serious systematic errors. Recently, electromagnetic flow tomography (EMFT) has been proposed for measuring velocity fields using several coils and a set of electrodes attached to the surface of the pipe. In this work, a velocity field reconstruction method for EMFT is proposed. The method uses a previously developed finite-element-based computational forward model for computing boundary voltages and a Bayesian framework for inverse problems. In the approach, the vz-component of the velocity field along the longitudinal axis of the pipe is estimated on the pipe cross section. Different asymmetric velocity fields encountered near pipe elbows, solids-in-water flows in inclined pipes and in stratified or multiphase flows are tested. The results suggest that the proposed reconstruction method could be used to estimate velocity fields in complicated pipe flows in which the conventional EMFMs have limited accuracy. This article is part of the themed issue 'Supersensing through industrial process tomography'.

Contrast enhancement in EIT imaging of the brain

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

Electrical impedance tomography for three-dimensional drug release monitoring

Electrical impedance tomography (EIT) was adapted to monitor drug release three-dimensionally as a function of time. EIT is an electrical imaging modality in which the three-dimensional conductivity distribution inside an object is computed based on electrical measurements from the boundaries. Here, the three-dimensional concentration distribution was monitored with the help of the experimentally determined relationship between drug concentration and conductivity. The EIT monitoring was carried out with propranolol hydrochloride tablets in an apparatus similar to USP dissolution apparatus 2. The release profiles estimated using EIT matched well with the UV/VIS spectrophotometric analyses that were performed as a reference. There are several benefits conferred by three-dimensional monitoring, i.e., comprehensive information about the release process; no need to take samples during experiments; and not essential to assume homogenous concentration distribution in the drug release analysis. EIT is an in-line technique, and moreover, it is non-intrusive and non-invasive. The possibilities and the characteristics of the EIT monitoring are described in detail, and some potential drug release applications are proposed. EIT is especially encouraged to be exploited for research and development purposes.

An electrical impedance tomography-based approach to monitor in vitro sodium chloride dissolution from pharmaceutical tablets

An approach to monitor in vitro dissolution process from pharmaceutical tablets utilizing electrical impedance tomography (EIT) is introduced. In the demonstration, a tablet containing sodium chloride (NaCl) was dissolution tested using tap water as a dissolution medium within an apparatus similar to the United States Pharmacopoeia dissolution apparatus II. During the process, the three-dimensional sodium chloride concentration distribution was monitored with EIT measurements as a function of time. For EIT measurements, an array of electrodes was attached on the boundary of the dissolution vessel, a set of alternating electric currents was injected through the electrodes, and the resulting voltages were measured. With these data and by applying mathematical algorithms, an approximation for the spatial/temporal concentration distribution inside the vessel was computed. It was found that the computed distributions were relatively homogeneous. A NaCl release curve was computed by integrating the concentration distribution over the vessel volume, and the final value of the curve matched well with the reference point based on the weight loss of the tablet. Finally, EIT monitoring is suggested to be used for research and product development purposes.

A measurement system and image reconstruction in magnetic induction tomography

Magnetic induction tomography (MIT) is a technique for imaging the internal conductivity distribution of an object. In MIT current-carrying coils are used to induce eddy currents in the object and the induced voltages are sensed with other coils. From these measurements, the internal conductivity distribution of the object can be reconstructed. In this paper, we introduce a 16-channel MIT measurement system that is capable of parallel readout of 16 receiver channels. The parallel measurements are carried out using high-quality audio sampling devices. Furthermore, approaches for reconstructing MIT images developed for the 16-channel MIT system are introduced. We consider low conductivity applications, conductivity less than 5 S m(-1), and we use a frequency of 10 MHz. In the image reconstruction, we use time-harmonic Maxwell's equation for the electric field. This equation is solved with the finite element method using edge elements and the images are reconstructed using a generalized Tikhonov regularization approach. Both difference and static image reconstruction approaches are considered. Results from simulations and real measurements collected with the Philips 16-channel MIT system are shown.

Approximation errors and model reduction in optical tomography

Model reduction is often required in optical diffusion tomography (ODT), typically due to limited available computation time or computer memory. In practice, this often means that we are bound to use sparse meshes in the model for the forward problem. Conversely, if we are given more and more accurate measurements, we have to employ increasingly accurate forward problem solvers in order to exploit the information in the measurements. In this paper we apply the approximation error theory to ODT. We show that if the approximation errors are estimated and employed, it is possible to use mesh densities that would be unacceptable with a conventional measurement model.

Simulations of localized harmonic motions on a blood vessel wall induced by an acoustic radiation force used in ultrasound elastography

Many noninvasive techniques have been developed recently to explore the mechanical properties of soft tissue. In this paper, dynamic acoustic radiation force induced vibrations on a blood vessel wall were simulated using different stimulation frequencies and stiffness parameters for the vessel wall. The stimulation frequency was varied between 20 Hz and 20 kHz and the stiffness parameter (Young's modulus) was varied between 60 kPa and 360 kPa. The vibration simulations were computed using a finite-element method in a 3D geometry that contained a vessel wall surrounded by soft tissue. The results indicate that vibrations caused by acoustic stimulation are sensitive to the changes in mechanical properties of the vessel wall and that the vibrations are highly dependent on the stimulation frequency and target structure. Therefore, measurements of absolute stiffness parameters may not be accurately achieved because this method is so dependent on the whole target structure, whereas the monitoring of changes during some process may be feasible.

A biopsy-based quick test in the diagnosis of duodenal hypolactasia in upper gastrointestinal endoscopy

BACKGROUND AND STUDY AIMS

The usefulness of a new quick test for endoscopic diagnosis of adult-type hypolactasia was tested in duodenal biopsies. In this test, an endoscopic biopsy from the postbulbar duodenum is incubated with lactose on a test plate, and a color reaction develops within 20 min as a result of hydrolyzed lactose (a positive result) in patients with normolactasia, whereas no reaction (a negative result) develops in patients with severe hypolactasia.

PATIENTS AND METHODS

Two postbulbar duodenal biopsies were taken from 80 prospectively enrolled adult outpatients with dyspepsia. The biopsies were used for the Quick Lactase Test (Biohit PLC, Helsinki, Finland) and in biochemical disaccharidase (lactase, sucrase, and maltase) assays. In addition, the C/T (-13,910) genotype was determined from DNA extracted from gastric antral biopsies using polymerase chain reaction sequencing in genomic analysis of adult-type hypolactasia.

RESULTS

Twenty-one of 22 patients (95 %; 95 % CI, 87 - 100 %) with biochemical lactase activity < 10 U/g protein, but none of the 58 patients with lactase activity of 10 U/g protein or more had a negative result in the Quick Lactase Test. Seven of the 80 patients (9 %; 95 % CI, 3 - 15 %) had a Quick Lactase Test result that indicated mild hypolactasia (a mild color reaction). All patients with celiac disease (n = 6) had a negative Quick Lactase Test result. Nine of 74 patients (six patients with celiac disease were excluded) had a CC (-13,910) genotype in genomic testing, indicating adult-type hypolactasia. All of them had negative test results with the Quick Lactase Test. Twenty-six patients had a TT genotype, indicating normolactasia, and none of these patients had a negative test result in the Quick Lactase Test. Six of 39 patients (15 %; 95 % CI, 4 - 27 %) with a CT genotype had a negative result in the Quick Lactase Test.

CONCLUSIONS

The Quick Lactase Test effectively identifies patients with severe duodenal hypolactasia. In comparison with CC (adult-type hypolactasia) and TT individuals (normolactasia), the sensitivity and specificity of the Quick Lactase Test result was 100 %. In comparison with biochemical lactase assays, the sensitivity and specificity of a negative Quick Lactase Test for indicating hypolactasia (lactase activity < 10 U/g protein) were 95 % (95 % CI, 87 - 100 %) and 100 %, respectively.

Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions

In this paper, a coupled radiative transfer equation and diffusion approximation model is extended for light propagation in turbid medium with low-scattering and non-scattering regions. The light propagation is modelled with the radiative transfer equation in sub-domains in which the assumptions of the diffusion approximation are not valid. The diffusion approximation is used elsewhere in the domain. The two equations are coupled through their boundary conditions and they are solved simultaneously using the finite element method. The streamline diffusion modification is used to avoid the ray-effect problem in the finite element solution of the radiative transfer equation. The proposed method is tested with simulations. The results of the coupled model are compared with the finite element solutions of the radiative transfer equation and the diffusion approximation and with results of Monte Carlo simulation. The results show that the coupled model can be used to describe photon migration in turbid medium with low-scattering and non-scattering regions more accurately than the conventional diffusion model.

Correlation between the allelic distribution of STRs in a Finnish population and phenotypically different gastrointestinal tumours: a study using four X-chromosomal markers (DXS7423, DXS8377, ARA, DXS101)

Microsatellite instability in tumours has been suggested as a model to study the process of short tandem repeat (STR) mutations. In the present study we have determined the allelic variation of four X-STRs (DXS7423, DXS8377, DXS101 and ARA) in a Finnish population of 103 individuals, and assessed whether a comparable allelic distribution could be found in a series of gastrointestinal cancers differing by the level of microsatellite instability. Fifty-seven gastric and colorectal cancers were stratified by autosomal STRs, and the mononucleotide marker BAT-26 into stable, low-level unstable and high-level unstable microsatellite (MSI-H) cancers, of which the last produced the majority of X-STR alleles. For the four markers analysed, a significant correlation of allele distribution between our Finnish population sample and MSI-H tumours was noted. Together, the eight MSI-H tumours found represented 80%, 66-80% and 100% of the DXS101 alleles in the Finnish, and in previously described Caucasian and Korean population samples, respectively. Of the ARA, DXS7423 and DXS8377 alleles in the Finnish population, 42%, 75% and 79% were found in the MSI-H cancers, respectively. The results suggest that analysis of STR variation in a relatively small number of MSI-H cancers may aid in pre-evaluation of their allelic distribution in a population.

Computational calibration method for optical tomography

We propose a computational calibration method for optical tomography. The model of the calibration scheme is based on the rotation symmetry of source and detector positions in the measurement setup. The relative amplitude losses and phase shifts at the optic fibers are modeled by complex-valued coupling coefficients. The coupling coefficients can be estimated when optical tomography data from a homogeneous and isotropic object are given. Once these coupling coefficients have been estimated, any data measured with the same measurement setup can be corrected for the relative variation in the data due to source and detector losses. The final calibration of the data for the source and detector losses and the source calibration between the data and the forward model are obtained as part of the initial estimation for reconstruction. The calibration method was tested with simulations and measurements. The results show that the coupling coefficients of the sources and detectors can be estimated with good accuracy. Furthermore, the results show that the method can significantly improve the quality of reconstructed images.

Hybrid radiative-transfer-diffusion model for optical tomography

A hybrid radiative-transfer-diffusion model for optical tomography is proposed. The light propagation is modeled with the radiative-transfer equation in the vicinity of the laser sources, and the diffusion approximation is used elsewhere in the domain. The solution of the radiative-transfer equation is used to construct a Dirichlet boundary condition for the diffusion approximation on a fictitious interface within the object. This boundary condition constitutes an approximative distributed source model for the diffusion approximation in the remaining area. The results from the proposed approach are compared with finite-element solutions of the radiative-transfer equation and the diffusion approximation and Monte Carlo simulation. The results show that the method improves the accuracy of the forward model compared with the conventional diffusion model.

Modelling the transport of ionizing radiation using the finite element method

Radiation therapy treatment planning is based on the calculation of the absorbed dose in the patient domain. For exact dose calculations, the solution of three coupled Boltzmann transport equations (BTEs) is needed to cover the transport of photons, electrons and positrons. In many situations, however, two coupled systems for photons and electrons are enough. The use of numerical methods in finding the exact solution of the unknown particle fluxes is necessary. In the stationary case, the BTE has six variables, three spatial, two directional and one energy variable. In this paper, we describe an approach in which the finite element method (FEM) is used to solve the six-dimensional problem. For the coupled photon-electron system, the variational formulation and the existence and uniqueness of the solution are derived. We simulate the solution of two coupled BTEs describing the travelling of photons and electrons in two spatial dimensions. The results are compared to Monte Carlo calculations with good agreement.

Evaluation of gastrointestinal cancer tissues as a source of genetic information for forensic investigations by using STRs

Malignant tissue samples may sometimes be the only source of biological material for forensic investigations, including identification of individuals or paternity testing. However, in use of such samples, uncertainties due to microsatellite instability (MSI) and loss of heterozygosity (LOH) often associated with neoplasias may be encountered. In this study, we have analysed the applicability of autosomal tetranucleotide short tandem repeat (STR) markers, which are routinely used in forensic analysis, to gain genetic information. MSI and LOH were analysed in 41 surgically removed gastrointestinal cancer specimens and the adjascent non-cancerous tissue marginals. The cancer specimens showed great variability in their genetic phenotypes due to MSI or LOH, with only 32% being microsatellite-stable. Of the 15 autosomal STR loci analysed, only TH01 had no MSI-type alteration in these samples. The loci most frequently affected by MSI were D8S1179, D21S11, D18S51 and D19S433 (MSI in 15-17% of cases). LOH-type alterations were observed at all of the loci, including the amelogenin locus used for sex determination. The highest LOH frequency was found at locus D18S51 (27%). The genetic alterations at the marker loci may indicate false homozygosity or heterozygosity, and false gender may result from erroneous deduction of DNA profiles. Therefore, typing of autosomal STRs from malignant tissues in forensic settings warrants careful interpretation of MSI and LOH results together with microscopic analysis of a tissue specimen. Results by two commercially available and widely used forensic DNA profiling kits used here were comparable.

Non-endoscopic diagnosis of atrophic gastritis with a blood test. Correlation between gastric histology and serum levels of gastrin-17 and pepsinogen I: a multicentre study

BACKGROUND AND AIMS

Serum levels of gastrin-17 (S-G-17) and pepsinogen I (S-PGI) are biomarkers of gastric antral and corpus mucosa, respectively. In a prospective multicentre investigation, we determined whether these tests, together with the assay of Helicobacter pylori antibodies, are a non-endoscopic tool for the diagnosis of atrophic gastritis.

MATERIALS AND METHODS

The series comprised 404 consecutive adult outpatients undergoing diagnostic upper-gastrointestinal endoscopy for various dyspeptic symptoms in five outpatient clinics. Gastric biopsies from the antrum and corpus (at least two biopsies from both sites) were available from all patients, and they were evaluated according to the guidelines of the updated Sydney system. S-PGI and S-G-17 were assayed with ELISA methods using monoclonal antibodies to pepsinogen I and amidated gastrin-17. In addition to the fasting level (S-G-17(fast)), a postprandial S-G-17 (S-G-17(prand)) level was measured 20 min after ingestion of a protein-rich drink. H. pylori antibodies were determined using a polyclonal EIA method.

RESULTS

S-G-17(prand) (and S-G-17(fast)) and S-PGI levels decreased with increasing grade of atrophy of the antrum or corpus, respectively. S-G-17(prand) levels were significantly lower in patients with advanced (moderate or severe) atrophic antral H. pylori gastritis than in those with non-atrophic H. pylori gastritis. All patients with a resected antrum demonstrated S-G-17(prand) levels that were almost undetectable. Of the nine patients with an H. pylori-positive moderate or severe atrophic antral gastritis, six had S-G-17(prand) levels below 5 pmol/l. Similarly, S-PGI levels were significantly lower in patients with advanced corpus atrophy than in those without. Of the 45 patients with moderate or severe corpus atrophy in endoscopic biopsies, 35 patients had S-PGI levels < 25 microg/l. By using the cut-off levels for S-G-17(prand) and S-PGI with the best discrimination, the sensitivity and specificity of the blood test panel in delineation of patients with advanced atrophic gastritis (either in the antrum or the corpus, or both) were 83% and 95%, respectively. The predictive values of the positive and negative test results were 75% and 97%, respectively. In the diagnosis of atrophic gastritis, the application of S-G-17(fast) showed a slightly lower sensitivity and specificity than the application of S-G-17(prand) as a biomarker for antral atrophy.

CONCLUSIONS

The diagnosis of atrophic gastritis obtained with the blood test panel of S-G-17, S-PGI and H. pylori antibodies is in good agreement with the endoscopic and biopsy findings. The panel is a tool for non-endoscopic diagnosis and screening of atrophic gastritis.

A new computational approach for cortical imaging

Estimation of current or potential distribution on the cortex is used to obtain information about neural sources from the scalp recorded electroencephalogram. If the active sources in the brain are superficial, the estimated field distribution on the cortex also yields information about the active source configuration. In these cases, these methods can be used as source localization methods. In this study, we concentrate on finite-element-based cortex potential estimation. Usually these methods require surface interpolation of the recorded voltages at the electrodes onto the entire scalp surface. We propose a new computational approach which does not require the use of surface interpolation but does it implicitly and uses only the recorded data at the electrodes. We refer to this method as the systematic approach (SA). We compare the SA with the surface interpolation approach (IA) and show that the SA is able to produce somewhat better accuracy than the IA. However, the main asset is that the sensitivity of the cortical potential maps to the regularization parameter is significantly lower than with the IA.

A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images

The EIDORS (electrical impedance and diffuse optical reconstruction software) project aims to produce a software system for reconstructing images from electrical or diffuse optical data. MATLAB is a software that is used in the EIDORS project for rapid prototyping, graphical user interface construction and image display. We have written a MATLAB package (http://venda.uku.fi/ vauhkon/) which can be used for two-dimensional mesh generation, solving the forward problem and reconstructing and displaying the reconstructed images (resistivity or admittivity). In this paper we briefly describe the mathematical theory on which the codes are based on and also give some examples of the capabilities of the package.

Recovery of piecewise constant coefficients in optical diffusion tomography

In optical diffusion tomography the reconstruction of the absorbtion and scattering coefficients is conventionally carried out in a pixel basis. The resulting number of unknowns makes the associated inverse problem severely ill-posed. We have recently proposed a new approach in which the goal is to reconstruct boundaries of piecewise constant tissue regions as well as the diffusion and absorption coefficients within these regions. This method assumes that there is a feasible initial guess on the domain boundaries. In this paper we propose an extension to this approach in which the initial estimate for the boundary and coefficient estimation is extracted from a conventional pixel based reconstruction using standard image processing operations. In the computation of the pixel based reconstruction the output least squares problem is augmented with an approximated total variation prior. The performance of the proposed approach is evaluated using simulated frequency domain data. It is shown that since the total variation type approach favors domains with constant coefficients it is well suited for the fixing of the starting point for the actual boundary and coefficient reconstruction method.

Simultaneous reconstruction of internal tissue region boundaries and coefficients in optical diffusion tomography

In this paper we propose a new numerical method to the inverse problem in optical diffusion tomography. We consider the reconstruction of the diffusion and absorption coefficients (kappa, mu(a)) within a domain omega which is known to consist of a set of disjoint regions of distinct tissue types. The assumption is that the regions of different tissues are bounded by smooth boundary curves and have constant absorption and diffusion coefficients. The goal in the proposed method is to reconstruct simultaneously the boundaries of the tissue regions together with the absorption and diffusion coefficients within these regions. The solution of the problem is based on the finite element method and subdivision of the elements. The performance of the proposed method is evaluated by simulations in which the optical parameters (kappa, mu(a)) are relevant in medical applications of optical tomography. It is shown that the proposed method is able to recover both the boundaries and the coefficients with good accuracy.

Effects of electrode properties on EEG measurements and a related inverse problem

A trend in EEG measurements is to increase the number of measurement electrodes in order to improve the spatial resolution of the recorded voltage distribution at the scalp. It is assumed that this would implicate better accuracy in the EEG inverse estimates. However, this does not necessarily hold. The reason for this is that the electrodes create a well conducting shunting "layer" on the scalp which affects the voltage distribution. This may decrease the information obtained and may therefore worsen the inverse estimates. Electrodes in EEG inverse problems are commonly modeled as point electrodes. This model cannot take into account the possible shunting effect of the electrodes. In this study the measurement electrodes are modeled using the so-called complete electrode model which takes into account the actual size of the electrode, the contact impedance between the skin and the electrode and also the shunting effect of the electrodes. In this paper the effects of the electrode size and the contact impedance on the voltage distribution are studied by simulations. It is shown that, depending on the size and the contact impedance of the electrodes, increasing the number of electrodes does not necessarily improve the accuracy of the inverse estimates. We also conclude that the use of the point electrode model is quite adequate in normal EEG studies. The use of a complete electrode model is necessary if electrodes cover more than 50% of the surface area.

Sensitivity matrix and reconstruction algorithm for EIT assuming axial uniformity

In electrical impedance tomography (EIT) two-dimensional models continue to be applied despite their known inability to provide correct reconstruction. In this paper, a reconstruction algorithm that assumes a translationally invariant conductivity distribution is described. A more precise forward solver is obtained by taking off-slice currents into consideration. An appropriate sensitivity matrix is derived. Numerical evidence for the improvement in precision compared to two-dimensional reconstruction is given.

Errors due to the truncation of the computational domain in static three-dimensional electrical impedance tomography

In electrical impedance tomography (EIT), an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. The currents spread out in three dimensions and therefore off-plane structures have a significant effect on the reconstructed images. A question arises: how far from the current carrying electrodes should the discretized model of the object be extended? If the model is truncated too near the electrodes, errors are produced in the reconstructed images. On the other hand if the model is extended very far from the electrodes the computational time may become too long in practice. In this paper the model truncation problem is studied with the extended finite element method. Forward solutions obtained using so-called infinite elements, long finite elements and separable long finite elements are compared to the correct solution. The effects of the truncation of the computational domain on the reconstructed images are also discussed and results from the three-dimensional (3D) sensitivity analysis are given. We show that if the finite element method with ordinary elements is used in static 3D EIT, the dimension of the problem can become fairly large if the errors associated with the domain truncation are to be avoided.