The Surviral Epidemiological Early Warning System Tyrol Dashboard - System, Functionality and Findings.

BACKGROUND: Dashboards provide a good retrospective view of the development of the disease. Yet, current COVID-related dashboards typically lack the capability to predict future trends. However, this is important for health policy makers and health care providers in order to adopt meaningful containment strategies. OBJECTIVES: The aim of this paper is to present the Surviral dashboard, which allows the effective monitoring of infectious disease dynamics. METHODS: The presented dashboard comprises a wide range of information, including retrospective and prognostic data based on an agent-based simulation framework. It served as the basis for informed decision-making and planning of disease control strategies within the federal state of Tyrol. RESULTS: By visualizing the information in an understandable format, the dashboard provided a comprehensive overview of the COVID-19 situation in Tyrol and allowed for the identification of trends and patterns. CONCLUSION: The presented dashboard is a valuable tool for managing pandemics such as COVID-19. It provides a convenient and efficient way to monitor the spread of a disease and identify potential areas for intervention.

A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry.

MOTIVATION: Prostate cancer is the most prevalent tumor in males and its incidence is expected to increase as the population ages. Prostate cancer is treatable by excision if detected at an early enough stage. The challenges of early diagnosis require the discovery of novel biomarkers and tools for prostate cancer management. RESULTS: We developed a novel feature selection algorithm termed as associative voting (AV) for identifying biomarker candidates in prostate cancer data measured via targeted metabolite profiling MS/MS analysis. We benchmarked our algorithm against two standard entropy-based and correlation-based feature selection methods [Information Gain (IG) and ReliefF (RF)] and observed that, on a variety of classification tasks in prostate cancer diagnosis, our algorithm identified subsets of biomarker candidates that are both smaller and show higher discriminatory power than the subsets identified by IG and RF. A literature study confirms that the highest ranked biomarker candidates identified by AV have independently been identified as important factors in prostate cancer development. AVAILABILITY: The algorithm can be downloaded from the following http://biomed.umit.at/page.cfm?pageid=516.

Mother rotor anchoring in branching tissue with heterogeneous membrane properties.

Abstract Current understanding of atrial fibrillation is based on the co-existence of multiple re-entrant waves propagating randomly throughout the tissue. However, recent experimental results indicate that in many cases one or a small number of periodic, high-frequency re-entrant sources (mother rotors) can drive the arrhythmia. Owing to the high activation rate, mother rotors seem to be located in regions of shortened action potential duration. In this study a computer model of cardiac propagation was applied to investigate mechanisms leading to the formation and maintenance of such mother rotors. For this purpose, a region of short action potential duration was generated by varying the acetylcholine concentration across the tissue. A mother rotor initiated in the center of this region drifts away, and the activation terminates. If an additional heterogeneity such as a bundle is included into the model, a further drift mechanism directed to the bundle is observed and the rotor can be stabilized. Therefore, bundle insertions may play an important role in the maintenance of mother rotors. The influence of the driving rotor on the activation pattern was studied in a three-dimensional model of rectangular shape and a monolayer model of anatomically correct atrial geometry.

Spatial-temporal filter effect in a computer model study of ventricular fibrillation.

Prediction of countershock success from ventricular fibrillation (VF) ECG is a major challenge in critical care medicine. Recent findings indicate that stable, high frequency mother rotors are one possible mechanism maintaining VF. A computer model study was performed to investigate how epicardiac sources are reflected in the ECG. In the cardiac tissues of two computer models - a model with cubic geometry and a simplified torso model with a left ventricle - a mother rotor was induced by increasing the potassium rectifier current. On the epicardium, the dominant frequency (DF) map revealed a constant DF of 23 Hz (cubic model) and 24.4 Hz (torso model) in the region of the mother rotor, respectively. A sharp drop of frequency (3-18 Hz in the cubic model and 12.4-18 Hz in the torso model) occurred in the surrounding epicardial tissue of chaotic fibrillatory conduction. While no organized pattern was observable on the body surface of the cubic model, the mother rotor frequency can be identified in the anterior surface of the torso model because of the chosen position of the mother rotor in the ventricle (shortest distance to the body surface). Nevertheless, the DFs were damped on the body surfaces of both models (4.6-8.5 Hz in the cubic model and 14.4-16.4 Hz in the torso model). Thus, it was shown in this computer model study that wave propagation transforms the spatial low pass filtering of the thorax into a temporal low pass. In contrast to the resistive-capacitive low pass filter formed by the tissue, this spatial-temporal low pass filter becomes effective at low frequencies (tens of Hertz). This effect damps the high frequency components arising from the heart and it hampers a direct observation of rapid, organized sources of VF in the ECGs, when in an emergency case an artifact-free recording is not possible.

On computing dominant frequency from bipolar intracardiac electrograms.

Dominant frequency (DF) computed from action potentials is a key parameter for investigating atrial fibrillation in animal studies and computer models. A recent clinical trial reported consistent results computing DF from 30 Hz to 400 Hz bandpass filtered bipolar electrograms in humans. The DF (< 15 Hz and, thus, filtered out) was recovered by rectifying the signal, while the theoretical background of this approach was left uncommented. It is the focus of this paper to provide this background by a Fourier analysis. We demonstrate that it is mainly the timing of the narrow deflections (local activation at the catheter tip) which contribute to the DF peak in the frequency spectrum. Due to the typical signal morphology pronounced harmonic peaks occur in the spectrum. This is a disadvantage when computing the regularity index (RI) as a parameter for local organization and signal quality. It is demonstrated for synthetical and patient data that at low DF the RI is far below the optimal value one even for high underlying organization and good signal quality. The insight obtained promotes the development of better measures for organization. The finding that mainly timing of activation contributes to DF might promote the development of powerful realtime signal processing tools for computing DF.

Systematic analysis of signaling pathways using an integrative environment.

INTRODUCTION: Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. METHODS: This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. RESULTS: The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. CONCLUSION: The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Sensitivity- and effort-gain analysis: multilead ECG electrode array selection for activation time imaging.

Methods for noninvasive imaging of electric function of the heart might become clinical standard procedure the next years. Thus, the overall procedure has to meet clinical requirements as an easy and fast application. In this paper, we propose a new electrode array which improves the resolution of methods for activation time imaging considering clinical constraints such as easy to apply and compatibility with routine leads. For identifying the body-surface regions where the body surface potential (BSP) is most sensitive to changes in transmembrane potential (TMP), a virtual array method was used to compute local linear dependency (LLD) maps. The virtual array method computes a measure for the LLD in every point on the body surface. The most suitable number and position of the electrodes within the sensitive body surface regions was selected by constructing effort gain (EG) plots. Such a plot depicts the relative attainable rank of the leadfield matrix in relation to the increase in number of electrodes required to build the electrode array. The attainable rank itself was computed by a detector criterion. Such a criterion estimates the maximum number of source space eigenvectors not covered by noise when being mapped to the electrode space by the leadfield matrix and recorded by a detector. From the sensitivity maps, we found that the BSP is most sensitive to changes in TMP on the upper left frontal and dorsal body surface. These sensitive regions are covered best by an electrode array consisting of two L-shaped parts of approximately 30 cm x 30 cm and approximately 20 cm x 20 cm. The EG analysis revealed that the array meeting clinical requirements best and improving the resolution of activation time imaging consists of 125 electrodes with a regular horizontal and vertical spacing of 2-3 cm.

Cardiac anisotropy: is it negligible regarding noninvasive activation time imaging?

The aim of this study was to quantify the effect of cardiac anisotropy in the activation-based inverse problem of electrocardiography. Differences of the patterns of simulated body surface potential maps for isotropic and anisotropic conditions were investigated with regard to activation time (AT) imaging of ventricular depolarization. AT maps were estimated by solving the nonlinear inverse ill-posed problem employing spatio-temporal regularization. Four different reference AT maps (sinus rhythm, right-ventricular and septal pacing, accessory pathway) were calculated with a bidomain theory based anisotropic finite-element heart model in combination with a cellular automaton. In this heart model a realistic fiber architecture and conduction system was implemented. Although the anisotropy has some effects on forward solutions, effects on inverse solutions are small indicating that cardiac anisotropy might be negligible for some clinical applications (e.g., imaging of focal events) of our AT imaging approach. The main characteristic events of the AT maps were estimated despite neglected electrical anisotropy in the inverse formulation. The worst correlation coefficient of the estimated AT maps was 0.810 in case of sinus rhythm. However, all characteristic events of the activation pattern were found. The results of this study confirm our clinical validation studies of noninvasive AT imaging in which cardiac anisotropy was neglected.

Model-based imaging of cardiac electrical excitation in humans.

Activation time (AT) imaging from electrocardiographic (ECG) mapping data has been developing for several years. By coupling ECG mapping and three-dimensional (3-D) + time anatomical data, the electrical excitation sequence can be imaged completely noninvasively in the human heart. In this paper, a bidomain theory-based surface heart model AT imaging approach was applied to single-beat data of atrial and ventricular depolarization in two patients with structurally normal hearts. In both patients, the AT map was reconstructed from sinus and paced rhythm data. Pacing sites were the apex of the right ventricle and the coronary sinus (CS) ostium. For CS pacing, the reconstructed AT pattern on the endocardium of the right atrium was compared with the CARTO map in both patients. The localization errors of the origins of the initial endocardial breakthroughs were determined to be 6 and 12 mm. The sites of early activation and the areas with late activation were estimated with sufficient accuracy. The reconstructed sinus rhythm sequence was in good qualitative agreement with the pattern previously published for the isolated Langendorff-perfused human heart.

Noninvasive myocardial activation time imaging: a novel inverse algorithm applied to clinical ECG mapping data.

Linear approaches like the minimum-norm least-square algorithm show insufficient performance when it comes to estimating the activation time map on the surface of the heart from electrocardiographic (ECG) mapping data. Additional regularization has to be considered leading to a nonlinear problem formulation. The Gauss-Newton approach is one of the standard mathematical tools capable of solving this kind of problem. To our experience, this algorithm has specific drawbacks which are caused by the applied regularization procedure. In particular, under clinical conditions the amount of regularization cannot be determined clearly. For this reason, we have developed an iterative algorithm solving this nonlinear problem by a sequence of regularized linear problems. At each step of iteration, an individual L-curve is computed. Subsequent iteration steps are performed with the individual optimal regularization parameter. This novel approach is compared with the standard Gauss-Newton approach. Both methods are applied to simulated ECG mapping data as well as to single beat sinus rhythm data from two patients recorded in the catheter laboratory. The proposed approach shows excellent numerical and computational performance, even under clinical conditions at which the Gauss-Newton approach begins to break down.

A new spatiotemporal regularization approach for reconstruction of cardiac transmembrane potential patterns.

The single-beat reconstruction of electrical cardiac sources from body-surface electrocardiogram data might become an important issue for clinical application. The feasibility and field of application of noninvasive imaging methods strongly depend on development of stable algorithms for solving the underlying ill-posed inverse problems. We propose a novel spatiotemporal regularization approach for the reconstruction of surface transmembrane potential (TMP) patterns. Regularization is achieved by imposing linearly formulated constraints on the solution in the spatial as well as in the temporal domain. In the spatial domain an operator similar to the surface Laplacian, weighted by a regularization parameter, is used. In the temporal domain monotonic nondecreasing behavior of the potential is presumed. This is formulated as side condition without the need of any regularization parameter. Compared to presuming template functions, the weaker temporal constraint widens the field of application because it enables the reconstruction of TMP patterns with ischemic and infarcted regions. Following the line of Tikhonov regularization, but considering all time points simultaneously, we obtain a linearly constrained sparse large-scale convex optimization problem solved by a fast interior point optimizer. We demonstrate the performance with simulations by comparing reconstructed TMP patterns with the underlying reference patterns.

A comparison of noninvasive reconstruction of epicardial versus transmembrane potentials in consideration of the null space.

We compare two source formulations for the electrocardiographic forward problem in consideration of their implications for regularizing the ill-posed inverse problem. The established epicardial potential source model is compared with a bidomain-theory-based transmembrane potential source formulation. The epicardial source approach is extended to the whole heart surface including the endocardial surfaces. We introduce the concept of the numerical null and signal space to draw attention to the problems associated with the nonuniqueness of the inverse solution and show that reconstruction of null-space components is an important issue for physiologically meaningful inverse solutions. Both formulations were tested with simulated data generated with an anisotropic heart model and with clinically measured data of two patients. A linear and a recently proposed quasi-linear inverse algorithm were applied for reconstructions of the epicardial and transmembrane potential, respectively. A direct comparison of both formulations was performed in terms of computed activation times. We found the transmembrane potential-based formulation is a more promising source formulation as stronger regularization by incorporation of biophysical a priori information is permitted.

On modeling the Wilson terminal in the boundary and finite element method.

In clinical electrocardiography, the zero-potential is commonly defined by the Wilson central terminal. In the electrocardiographic forward and inverse problem, the zero-potential is often defined in a different way, e.g., by the sum of all node potentials yielding zero. This study presents relatively simple to implement techniques, which enable the incorporation of the Wilson Terminal in the boundary element method (BEM) and finite element method (FEM). For the BEM, good results are obtained when properly adopting matrix deflation for modeling the Wilson terminal. Applying other zero-potential-definitions, the obtained solutions contained a remarkable offset with respect to the reference defined by the Wilson terminal. In the inverse problem (nonlinear dipole fit), errors introduced by an erroneous zero-potential-definition can lead to displacements of more than 5 mm in the computed dipole location. For the FEM, a method similar to matrix deflation is proposed in order to properly consider the Wilson central terminal. The matrix obtained from this manipulation is symmetric, sparse and positive definite enabling the application of standard FEM-solvers.

Electrocardiographic imaging of atrial and ventricular electrical activation.

Inverse electrocardiography has been developing for several years. By combining measurements obtained by electrocardiographic body surface mapping with three-dimensional anatomical data, one can non-invasively image the electrical activation sequence in the human heart. In this study, an imaging approach that uses a bidomain theory-based surface heart model was applied to single-beat data of atrial and ventricular activation. We found that for sinus and paced rhythms, the sites of early activation and the areas with late activation were estimated with sufficient accuracy. In particular, for focal arrhythmias, this model-based imaging approach might allow the guidance and evaluation of antiarrhythmic interventions, for instance, in case of catheter ablation or drug therapy.

ECG mapping and imaging of cardiac electrical function.

Inverse electrocardiography has been developed for several years. By coupling electrocardiographic mapping and 3D-time anatomical data, the electrical excitation sequence can be imaged completely non-invasively in the human heart. In this study, a bidomain theory based surface heart model activation time imaging approach was applied to single beat data of atrial and ventricular depolarization. For sinus and paced rhythms, the sites of early activation and the areas with late activation were estimated with sufficient accuracy. In particular for focal arrhythmias, this model-based imaging approach might allow the guidance and evaluation of antiarrhythmic interventions, for instance, in case of catheter ablation or drug therapy.

Dynamic simulations on the mitochondrial fatty acid beta-oxidation network.

BACKGROUND: The oxidation of fatty acids in mitochondria plays an important role in energy metabolism and genetic disorders of this pathway may cause metabolic diseases. Enzyme deficiencies can block the metabolism at defined reactions in the mitochondrion and lead to accumulation of specific substrates causing severe clinical manifestations. Ten of the disorders directly affecting mitochondrial fatty acid oxidation have been well-defined, implicating episodic hypoketotic hypoglycemia provoked by catabolic stress, multiple organ failure, muscle weakness, or hypertrophic cardiomyopathy. Additionally, syndromes of severe maternal illness (HELLP syndrome and AFLP) have been associated with pregnancies carrying a fetus affected by fatty acid oxidation deficiencies. However, little is known about fatty acids kinetics, especially during fasting or exercise when the demand for fatty acid oxidation is increased (catabolic stress). RESULTS: A computational kinetic network of 64 reactions with 91 compounds and 301 parameters was constructed to study dynamic properties of mitochondrial fatty acid beta-oxidation. Various deficiencies of acyl-CoA dehydrogenase were simulated and verified with measured concentrations of indicative metabolites of screened newborns in Middle Europe and South Australia. The simulated accumulation of specific acyl-CoAs according to the investigated enzyme deficiencies are in agreement with experimental data and findings in literature. Investigation of the dynamic properties of the fatty acid beta-oxidation reveals that the formation of acetyl-CoA - substrate for energy production - is highly impaired within the first hours of fasting corresponding to the rapid progress to coma within 1-2 hours. LCAD deficiency exhibits the highest accumulation of fatty acids along with marked increase of these substrates during catabolic stress and the lowest production rate of acetyl-CoA. These findings might confirm gestational loss to be the explanation that no human cases of LCAD deficiency have been described. CONCLUSION: In summary, this work provides a detailed kinetic model of mitochondrial metabolism with specific focus on fatty acid beta-oxidation to simulate and predict the dynamic response of that metabolic network in the context of human disease. Our findings offer insight into the disease process (e.g. rapid progress to coma) and might confirm new explanations (no human cases of LCAD deficiency), which can hardly be obtained from experimental data alone.

Improving calibration of logistic regression models by local estimates.

OBJECTIVE: To improve the calibration of logistic regression (LR) estimates using local information. BACKGROUND: Individualized risk assessment tools are increasingly being utilized. External validation of these tools often reveals poor model calibration. METHODS: We combine a clustering algorithm with an LR model to produce probability estimates that are close to the true probabilities for a particular case. The new method is compared to a standard LR model in terms of calibration, as measured by the sum of absolute differences (SAD) between model estimates and true probabilities, and discrimination, as measured by area under the ROC curve (AUC). RESULTS: We evaluate the new method on two synthetic data sets. SADs are significantly lower (p < 0.0001) in both data sets, and AUCs are significantly higher in one data set (p < 0.01). CONCLUSION: The results suggest that the proposed method may be useful to improve the calibration of LR models.

Frequency distribution effects of anchored mother rotors--a computer model study.

Recent findings indicate that major organized centers (mother rotors) can maintain ventricular fibrillation (VF). In computer models the mother rotors can be induced by local shortening of the action potential duration (APD) in the cardiac tissue. Because of the fact that these rotors tend to drift away towards regions with longer APD, an additional heterogeneity (e.g. bundle) has to be included in the model for stabilizing the activation. Thus, the rotor anchors on this bundle and yields to interesting frequency distribution effects. In the dominant frequency (DF) map of a simplified computer model of the left ventricle it can be observed that the anchoring site of the rotor produces a slightly lower DF than in the surrounding cardiac tissue. That means that due to the load effect of the bundle the frequency is decreased. Furthermore the meandering of the mother rotor around this anchor site is reflected in the spectra of signals taken randomly in the organized region. These effects are both detected with two different independent spectral estimators with different resolutions.

A cellular automaton framework for infectious disease spread simulation.

In this paper, a cellular automaton framework for processing the spatiotemporal spread of infectious diseases is presented. The developed environment simulates and visualizes how infectious diseases might spread, and hence provides a powerful instrument for health care organizations to generate disease prevention and contingency plans. In this study, the outbreak of an avian flu like virus was modeled in the state of Tyrol, and various scenarios such as quarantine, effect of different medications on viral spread and changes of social behavior were simulated.The proposed framework is implemented using the programming language Java. The set up of the simulation environment requires specification of the disease parameters and the geographical information using a population density colored map, enriched with demographic data.The results of the numerical simulations and the analysis of the computed parameters will be used to get a deeper understanding of how the disease spreading mechanisms work, and how to protect the population from contracting the disease. Strategies for optimization of medical treatment and vaccination regimens will also be investigated using our cellular automaton framework.In this study, six different scenarios were simulated. It showed that geographical barriers may help to slow down the spread of an infectious disease, however, when an aggressive and deadly communicable disease spreads, only quarantine and controlled medical treatment are able to stop the outbreak, if at all.

Evaluation of cardiac scoring models for an Austrian cardiac register.

The Austrian Health 2006 Structural Plan of 28 June 2006 requires that reference centres for heart surgery 'participate in result-quality registers (e.g. cardiac registers)'. The aim of the present study was to identify a suitable scoring model for the Austrian register during the run-up to its creation. During the period from November 2004 to December 2005 a survey was done of the actual situation, the organisational and economic possibilities, and the requirements of all Austrian heart centres. General and also specific Austrian basic conditions were defined. Scoring models were then classified and evaluated. The characteristics 'national and international comparability', the associated 'distribution of the scoring system' and 'detailed scientific discussion of the applicability' were found as the main criteria for selection. Economic aspects such as survey and analysis costs, and the everyday practicability of gathering data in the actual situation revealed by the survey, were also included in the evaluation framework. It could be demonstrated that under the given circumstances, the EuroSCORE represented the suitable predictive model.