BACKGROUND:Intracranial pressure (ICP) is a vital parameter that is continuously monitored in patients with severe brain injury and imminent intracranial hypertension.OBJECTIVE:To estimate intracranial pressure without intracranial probes based on transcutaneous near infrared spectroscopy (NIRS).METHODS:We developed machine learning based approaches for noninvasive intracranial pressure (ICP) estimation using signals from transcutaneous near infrared spectroscopy (NIRS) as well as other cardiovascular and artificial ventilation parameters.RESULTS:In a patient cohort of 25 patients, with 22 used for model development and 3 for model testing, the best performing models were Fourier transform based Transformer ICP waveform estimation which produced a mean absolute error of 4.68 mm Hg (SD = 5.4) in estimation.CONCLUSION:We did not find a significant improvement in ICP estimation accuracy by including signals measured by transcutaneous NIRS. We expect that with higher quality and greater volume of data, noninvasive estimation of ICP will improve.

Objective: Detection of delayed cerebral ischemia (DCI) is challenging in comatose patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH). Brain tissue oxygen pressure (PbtO2) monitoring may allow early detection of its occurrence. Recently, a probe for combined measurement of intracranial pressure (ICP) and intraparenchymal near-infrared spectroscopy (NIRS) has become available. In this pilot study, the parameters PbtO2, Hboxy, Hbdeoxy, Hbtotal and rSO2 were measured in parallel and evaluated for their potential to detect perfusion deficits or cerebral infarction. Methods: In patients undergoing multimodal neuromonitoring due to poor neurological condition after aSAH, Clark oxygen probes, microdialysis and NIRS-ICP probes were applied. DCI was suspected when the measured parameters in neuromonitoring deteriorated. Thus, perfusion CT scan was performed as follow up, and DCI was confirmed as perfusion deficit. Median values for PbtO2, Hboxy, Hbdeoxy, Hbtotal and rSO2 in patients with perfusion deficit (Tmax > 6 s in at least 1 vascular territory) and/or already demarked infarcts were compared in 24- and 48-hour time frames before imaging. Results: Data from 19 patients (14 University Hospital Zurich, 5 Charite Universitatsmedizin Berlin) were prospectively collected and analyzed. In patients with perfusion deficits, the median values for Hbtotal and Hboxy in both time frames were significantly lower. With perfusion deficits, the median values for Hboxy and Hbtotal in the 24 h time frame were 46,3 [39.6, 51.8] mu mol/l (no perfusion deficits 53 [45.9, 55.4] mu mol/l, p = 0.019) and 69,3 [61.9, 73.6] mu mol/l (no perfusion deficits 74,6 [70.1, 79.6] mu mol/l, p = 0.010), in the 48 h time frame 45,9 [39.4, 51.5] mu mol/l (no perfusion deficits 52,9 [48.1, 55.1] mu mol/l, p = 0.011) and 69,5 [62.4, 74.3] mu mol/l (no perfusion deficits 75 [70,80] mu mol/l, p = 0.008), respectively. In patients with perfusion deficits, PbtO2 showed no differences in both time frames. PbtO2 was significantly lower in patients with infarctions in both time frames. The median PbtO2 was 17,3 [8,25] mmHg (with no infarctions 29 [22.5, 36] mmHg, p = 0.006) in the 24 h time frame and 21,6 [11.1, 26.4] mmHg (with no infarctions 31 [22,35] mmHg, p = 0.042) in the 48 h time frame. In patients with infarctions, the median values of parameters measured by NIRS showed no significant differences. Conclusions: The combined NIRS-ICP probe may be useful for early detection of cerebral perfusion deficits and impending DCI. Validation in larger patient collectives is needed.

The knowledge of accurate optical parameters of materials is paramount in biomedical optics applications and numerical simulations of such systems. Phantom materials with variable but predefined parameters are needed to optimise these systems. An optimised integrating sphere measurement setup and reconstruction algorithm are presented in this work to determine the optical properties of silicone rubber based phantoms whose absorption and scattering properties are altered with TiO2 and carbon black particles. A mixing formula for all constituents is derived and allows to create phantoms with predefined optical properties.

A novel way to attain three dimensional fluence rate maps from Monte-Carlo simulations of photon propagation is presented in this work. The propagation of light in a turbid medium is described by the radiative transfer equation and formulated in terms of radiance. For many applications, particularly in biomedical optics, the fluence rate is a more useful quantity and directly derived from the radiance by integrating over all directions. Contrary to the usual way which calculates the fluence rate from absorbed photon power, the fluence rate in this work is directly calculated from the photon packet trajectory. The voxel based algorithm works in arbitrary geometries and material distributions. It is shown that the new algorithm is more efficient and also works in materials with a low or even zero absorption coefficient. The capabilities of the new algorithm are demonstrated on a curved layered structure, where a non-scattering, non-absorbing layer is sandwiched between two highly scattering layers.

For the reconstruction of physiological changes in specific tissue layers detected by optical techniques, the exact knowledge of the optical parameters μa, μs and g of different tissue types is of paramount importance. One approach to accurately determine these parameters for biological tissue or phantom material is to use a double-integrating-sphere measurement system. It offers a flexible way to measure various kinds of tissues, liquids and artificial phantom materials. Accurate measurements can be achieved by technical adjustments and calibration of the spheres using commercially available reflection and transmission standards. The determination For the reconstruction of physiological changes in specific tissue layers detected by optical techniques, the exact knowledge of the optical parameters μa, μs and g of different tissue types is of paramount importance. One approach to accurately determine these parameters for biological tissue or phantom material is to use a double-integrating-sphere measurement system. It offers a flexible way to measure various kinds of tissues, liquids and artificial phantom materials. Accurate measurements can be achieved by technical adjustments and calibration of the spheres using commercially available reflection and transmission standards. The determination of the optical parameters of a material is based on two separate steps. Firstly, the reflectance ρs, the total transmittance TsT and the unscattered transmittance TsC of the sample s are measured with the double-integrating-sphere setup. Secondly, the optical parameters μa, μs and g are reconstructed with an inverse search algorithm combined with an appropriate solver for the forward problem (calculating ρs, TsT and TsC from μa, μs and g) has to be applied. In this study a Genetic Algorithm is applied as search heuristic, since it offers the most flexible and general approach without requiring any foreknowledge of the fitness-landscape. Given the challenging preparation of real tissue samples it comes as no surprise that these are subject to various uncertainties. In order to perform a robust parameter reconstruction samples of different thickness are used. This adds a further, strong restriction to the potential results from the heuristic reconstruction algorithm.

Numerical methods applied in Cartesian grids have become workhorses for general purpose time-domain electromagnetic simulations because of their simplicity, efficiency and scalability. Implementations often consider specific treatments for curved and slanted boundaries, as well as sub-cell models and sub-gridding schemes. As alternative, methods based on unstructured discretisation, such as a tetrahedral mesh, have never truly become mainstream techniques despite their remarkable capabilities for accurate multi-scale and conformal modelling. This paper firstly reviews the development of a particular conformal time-domain method applied in tetrahedral meshes, namely the Finite-Volume Time-Domain method, and illustrates its potential for multi-scale problems in a selected example. The second part of the paper points out a novel class of methods which are amenable to conformal time-domain implementation on clouds of points. These so-called "meshless methods" do not require an explicit mesh definition, and open new perspectives towards future applications involving multi-scale multi-physics problems.

Near Infrared (NIR) extinction measurements can be used to determine the cerebral hemodynamics of adult patients. To be able to interpret and verify measurement data, it is necessary to know the three-dimensional light intensity distribution in the human head. This light intensity map can advantageously be created by numerical simulations. Such simulations of light intensity in the head are complex, since the light is crossing several tissue types with very distinct optical properties. The Monte-Carlo method proved to represent a reliable tool for simulation of light intensity in turbid media. The desired result of a Monte-Carlo simulation is the spatially resolved average light intensity, which has to be derived from the statistical output of the Monte-Carlo simulation. We propose a novel analysis method which directly tracks the intensity based on a linedrawing algorithm to attain a 3D intensity map of the whole computational domain. The proposed method largely operates independently of the underlying Monte-Carlo algorithm itself. The algorithm is verified through comparison with analytical approximations of the Radiative Transport Equation. As a challenging example, the simulation of the light intensity distribution inside the human head based on segmented MRI data is presented.

Wireless body area network (WBAN) is a new enabling system with promising applications in areas such as remote health monitoring and interpersonal communication. Reliable and optimum design of a WBAN system relies on a good understanding and in-depth studies of the wave propagation around a human body. However, the human body is a very complex structure and is computationally demanding to model. This paper aims to investigate the effects of the numerical model's structure complexity and feature details on the simulation results. Depending on the application, a simplified numerical model that meets desired simulation accuracy can be employed for efficient simulations. Measurements of ultra wideband (UWB) signal propagation along a human arm are performed and compared to the simulation results obtained with numerical arm models of different complexity levels. The influence of the arm shape and size, as well as tissue composition and complexity is investigated.

The sensitivity and specificity of dielectric spectroscopy for the detection of dielectric changes inside a multi-layered structure is investigated. We focus on providing a base for sensing physiological changes in the human skin, i.e. in the epidermal and dermal layers. The correlation between changes of the human skin's effective permittivity and changes of dielectric parameters and layer thickness of the epidermal and dermal layers is assessed using numerical simulations. Numerical models include fringing-field probes placed directly on a multi-layer model of the skin. The resulting dielectric spectra in the range from 100 kHz up to 100 MHz for different layer parameters and sensor geometries are used for a sensitivity and specificity analysis of this multi-layer system. First, employing a coaxial probe, a sensitivity analysis is performed for specific variations of the parameters of the epidermal and dermal layers. Second, the specificity of this system is analysed based on the roots and corresponding sign changes of the computed dielectric spectra and their first and second derivatives. The transferability of the derived results is shown by a comparison of the dielectric spectra of a coplanar probe and a scaled coaxial probe. Additionally, a comparison of the sensitivity of a coaxial probe and an interdigitated probe as a function of electrode distance is performed. It is found that the sensitivity for detecting changes of dielectric properties in the epidermal and dermal layers strongly depends on frequency. Based on an analysis of the dielectric spectra, changes in the effective dielectric parameters can theoretically be uniquely assigned to specific changes in permittivity and conductivity. However, in practice, measurement uncertainties may degrade the performance of the system.

In this paper we discuss challenges related with time-domain simulations of a complete microwave radar imaging system for breast cancer detection. Two different numerical methods are considered to address this demanding electromagnetic problem featuring 31 ultra-wideband antennas. The first method is the Finite Integration Technique (FIT) applied in a regular grid and implemented in a commercial solver, whereas the second method is an in-house developed Finite-Volume Time-Domain (FVTD) code applied in a tetrahedral mesh. Our work focuses on the fundamental differences between the two approaches for the comprehensive full-wave modeling of the considered problem. The emphasis of the comparison is placed on the computational cost, which reveals the strengths and limitations of both methods for the problem considered.

This paper demonstrates large-scale electromagnetic simulations of a real microwave imaging system for breast cancer detection. In particular we present calculated transient scattering responses from a tumour in a breast phantom modelled with dispersive materials. The responses are obtained from the full-scale numerical model of the 31-element antennas array. Two different numerical methods are considered in this work, i.e. the Finite Integration Technique (FIT) method implemented in a commercial solver and an inhouse developed Finite-Volume Time-Domain (FVTD) code.

The electromagnetic modeling of distributed or other highly complex systems requires reliable and strongly adaptable simulation algorithms. In this respect, the finite-volume time-domain (FVTD) method is a promising and very flexible approach in the class of volume-discretizing numerical techniques, because of its combination of explicit time stepping with an unstructured, inhomogeneous mesh. For scattering problems, in order to achieve accurate simulation results, a highly absorbing boundary truncation scheme is required. This paper proposes an approximate conformal perfectly matched absorber for the FVTD method and demonstrates its applicability with a practical example of the simulation of mutual coupling between two dielectric resonator antennas (DRAs).

The performance of two different head coil designs, an asymmetrically fed microstrip and a microstrip dipole, for whole-brain MRI at 7 T were analyzed regarding the B1 +-field and SAR distributions. The simulated electromagnetic behavior of the single elements are validated by bench measurements. The microstrip dipole design turned out to exhibit an almost similar B1 + -field distribution along with a significantly lower SAR. Preliminary measurement results confirm the simulations of the realized prototype array exciting one single element. The design of the prototype could be substantially supported by numerical simulations.

The performance of three different antennas typically used in EMC testings is thoroughly analyzed: A doubleridged horn, a trapezoidal logarithmic-periodic, and a biconical antenna. Those antennas are briefly compared considering their relevant characteristics, their radiation patterns, and their operational frequency range. However, the emphasis of this paper is placed on the relevant aspects regarding their numerical modeling. In order to obtain reliable and highly precise simulation results, certain significant simulation guidelines should be followed, amongst others how to include the feeding in the models. The Finite-Volume Time-Domain (FVTD) method is applied here as an appropriate numerical tool in order to accomplish accurate simulations. The method exploits conformal meshing and therefore is capable of precisely modeling fine structural details in close proximity to an overall large structure.