High intensity focused ultrasound (HIFU) is a non-invasive treatment technique to induce thermal or mechanical bioeffects. Characterising the wave field is essential for reliable and reproducible transducer operation in clinical use. This paper presents a schlieren technique to visualise and quantify transducer wave fields. The technique is based on the piezo-optical effect of water, i.e. the refractive index variation caused by sound pressure. Our custom-built system equipped with a Raspberry Pi HQ camera can capture schlieren photographs of acoustic fields generated by a clinical HIFU system. Alternatively, a high-speed camera allows analysis of short burst pulses. We investigated the focal zone shape of continuously generated HIFU fields at acoustic powers of 10-250 W. Images of the focal area at 100 W indicated dimensions comparable to the reported literature values. Notably, as power increases, we observe waveform distortion in the focal zone due to nonlinear propagation of ultrasound. Our findings demonstrate the efficacy of our system in visualizing and characterizing the acoustic fields generated by a clinical HIFU device.

Laser-scanning confocal microscopy of the human cornea acquires \textit{in vivo} images of corneal tissues with cellular resolution, which offers diagnostic potential for a variety of diseases. However, involuntary fixational eye movements induce motion artefacts that pose a challenge for accurate morphometric analysis and particularly for preceding image data fusion steps. Different image registration algorithms promise to eliminate such artefacts, but objective, quantitative evaluation of the registration results is difficult because of the lack of ground truth data. Simulation approaches offer a possibility to close this gap. Existing open-source software for the simulation of fixational eye movements is currently limited to creating drift movement. The present contribution proposes complementary models for microsaccade and tremor components to provide complete simulated fixational eye movement paths. In addition, it reports results from an extensive examination of different model parameter combinations. It is shown that the microsaccade model is capable of reproducing intermicrosaccade intervals that closely resemble experimental data. A software implementation is provided as open-source Python modules.

Alzheimer’s disease (AD) is a progressive neurodegenerative brain disorder that primarily affects elderly individuals. Mild cognitive impairment (MCI) represents an intermediate stage between normal cognitive functioning and the onset of AD. During this transition state, various sub-anatomic structures of the brain, including fornix, undergo pathological changes. In this study, an attempt has been made to analyse the structural variations in the fornix region of MCI and AD using invariant moments. For this purpose, T1-weighted brain structural magnetic resonance (sMR) images are obtained from a public database. The pre-processing of the raw images is conducted in FreeSurfer, and the fornix region is segmented using the reaction-diffusion level set (RDLS) method. Further, seven Hu’s invariant moments are extracted from the segmented fornix region, and statistical analysis is carried out using student t-test and Wilcoxon’s rank sum test to identify the significant features that could differentiate between the MCI and AD conditions. The results demonstrate that the combination of FreeSurfer and RDLS technique effectively pre-processes the brain sMR images and accurately delineates the fornix region. Statistical results revealed that six out of seven invariant moments are significant (p <0.001). It is observed that the mean values of all the moments in MCI are lower than AD, suggesting a higher degree of structural variation in AD compared to MCI. Considering the potential of fornix alterations in predicting the early stages of AD, the proposed approach holds considerable clinical relevance for further investigation.

The non-invasive detection of vital parameters is gaining significance in the medical field through the use of various established and novel camera technologies and the use of artificial intelligence for data processing. A recently emerging type of imaging sensor, the neuromorphic camera, mimics the way the human eye perceives changes in its vision by responding to local changes in brightness for each pixel. The use of these neuromorphic cameras in the medical field is mostly unexplored and offers new possibilities. This research experiment is designed as a proof of concept for the use of neuromorphic cameras to detect the heart rate and respiration rate of a person by monitoring movement and subtle vibrations of the abdominal and chest area. The experimental setup consisted of a DVXplorer camera positioned 30 cm from a healthy person, directed at the abdominal and chest area. The respiration rate was detected with a mean absolute error of 0.66 bpm. The heart rate was detected with an accuracy of 95 % and a mean absolute error of less than 2 bpm. This shows the possibility to detect the heart rate and respiration rate of a person reliably, using neuromorphic cameras under controlled conditions. Future research will focus on improving reliability under more challenging environmental circumstances like varying light conditions and movement of the patient.

Transcatheter aortic valve replacement (TAVR) has become the standard therapy for aortic valve stenosis in pa-tients with high surgical risk. Understanding the flow dynam-ics in TAVR is crucial for its evaluation and optimization. Ex-perimental flow measurement by means of Particle Image Ve-locimetry (PIV) is increasingly applied alongside numerical analyses.

This study introduces a novel test rig concept enabling the determination of velocity fields using Stereo-PIV under steady forward flow conditions through a TAVR during the peak systole matching the ISO 5840-1:2021 requirements. The experimental setup utilized an impeller pump to generate steady forward flow through a silicone aortic root model with implanted TAVR. A Stereo-PIV setup captured velocity fields in both ventricular inflow and aortic outflow regions. Test con-ditions were based on physiological flow rates determined from pulsatile measurements.

Results showed characteristic flow patterns: a central jet flow entering the TAVR in the ventricular flow field. A jet flow directed towards the sinus side and a recirculation zone forming on the opposite side of the sinus could be detected in the aortic outflow. The width of the recirculation zone in-creases with distance from the TAVR.

This study provides a comprehensive approach for fluid dynamic analysis of TAVR under steady flow conditions, offering insights into flow mechanics performance crucial for device optimization. Further investigations could enhance the PIV – measurement procedure by increasing both the spatial resolution and the tracer particle density within the acquired images for a comprehensive characterization of TAVR flow dynamics.

The technique of PC-MRI flow measurement offers a great opportunity to diagnose and understand the pathogenesis of various diseases and clinical pictures. Although previously criticized for its lack of accuracy, the method is now expanding the possibilities in several research areas. In this study, the design of an MR-compatible pump for the validation of PC-MRI flow measurements is presented. Initial PC-MRI measurements have demonstrated MR- compatibility and the ability to record artifact-free flows. The flow generated by the pump was further measured with an ultrasound flow sensor and compared with a physiological flow curve. The results showed that both the course and the minima and maxima match. Thus, the resulting pump generates a bidirectional, pulsatile flow within a physiological range and a variable frequency between 60-90 rpm with a stroke volume of 0.9 ml. Further flows, frequencies and stroke volumes can be adjusted. This enables the validation of PC- MRI flow measurements and addresses current difficulties such as the lack of in vivo data.

A novel tool to create artificial, cell-based model systems of biological barriers for preclinical drug testing and basic research are artificial collagen membranes (ACM). They closely reflect in vivo basement membrane properties like permeability and stiffness. Besides, they act as initial artificial basement membrane during cell culture. Nevertheless, up to now only complex protocols are published to create such artificial membranes. Also the deflection relies on very low pressure to elongate ACM, if in vivo like deflection – as in the lung mucosa – shall be emulated. Moreover, online monitoring of the deflection of ACM is a crucial part, hence collagen is non-transparent in the visual spectrum, reducing the applicability of standard microscopy. Here we show an easy protocol to generate ACM using commercially available NetwellTM inserts and collagen gel based coating. To address above mentioned issues in membrane deflection we developed a novel pneumatic actuation device (MPSstimulus) as well as a 3D-printed lid and a holder for 6-well plates as an easy to use microphysiological system (MPS) to stimulate ACM. Furthermore, we characterized the 3D membrane structure and dynamic elongation using optical coherence tomography (OCT). Based on our preliminary results, OCT is a promising technique for high-resolution inspection and elastographic analysis of ACM and adherent cell layers using the novel pneumatic actuation device.