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Optical Coherence Tomography Angiography (OCTA) is an imaging modality that provides threedimensional information of the retinal microvasculature and therefore promises early diagnosis and sufficient monitoring in ophthalmology. However, there is considerable variability between experts analysing this data. Measures for quantitative assessment of the vasculature need to be developed and established, such as fractal dimension. Fractal dimension can be used to assess the complexity of vessels and has been shown to be independently associated with neovascularization, a symptom of diseases such as diabetic retinopathy. This investigation assessed the performance of three fractal dimension algorithms: Box Counting Dimension (BCD), Information Dimension (ID), and Differential Box Counting (DBC). Two of those, BCD and ID, rely on previous vessel segmentation. Assessment of the added value or disturbance regarding the segmentation step is a second aim of this study. The investigation was performed on a data set composed of 9 in vivo human eyes. Since there is no ground truth available, the performance of the methods in differentiating the Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC) layers apart and the consistency of measurements of the same layer at different time-points were tested. The performance parameters were the ICC and the Mann- Whitney U tests. The three applied methods were suitable to tell the different layers apart and showed consistent values applied in the same slab. Within the consistency test, the non-segmentation-based method, DBC, was found to be less accurate, expressed in a lower ICC value, compared to its segmentation-based counterparts. This result is thought to be due to the DBC’s higher sensitivity when compared to the other methods. This higher sensitivity might help detect changes in the microvasculature, like neovascularization, but is also more likely prone to noise and artefacts.

Intraoperative blood flow measurement is an effective way to assess the quality of bypass surgery. Flow quantification from indocyanine green (ICG) angiography promises to be an easy, contact-free method. It shows deviations compared to a reference. These are given as factor k, which depends on the vessel diameter d. The radiation transport within the vessel while recording the ICG passage might cause this. It is analyzed in silico to disclose its impact on k (d). A Fluorescence Monte Carlo Multi Cylinder (FMCMC) model was developed as a static model, assuming homogeneous concentration of ICG. In contrast to published approaches utilizing a Monte Carlo Multi Layer (MCML) model assuming the deepest penetration location within a photon packet’s path to be the fluorescence location, the events are modeled. Fluorescence event modeling, Multi Cylinder geometry and a homogeneous illumination as well as combinations of these were implemented in separate aspect models. Resulting k (d) were compared to k (d) from MCML. Deviations in k (d) derived from FMCMC and MCML in each aspect model were present. The Root Mean Square Error ranges from 6,8% to 36 %, k (d) also varied comparing the aspect models to each other. The model geometry, the modeled fluorescence location and illumination mode show a clear impact on simulated k (d). Therefore, our study shows that simplifications of previous studies are invalid. The developed FMCMC model considers the named aspects, allowing the analysis of radiation transport in ICG angiography. The FMCMC model assumes a homogeneous concentration of ICG which is not true in clinical cases. Obtaining the heterogeneous distribution of ICG is possible via fluid flow models. Coupling the fluid flow model and the developed radiation transport model as well as including a detailed camera optic is the task for future work.

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that enables the visualization of perfused vasculature in vivo. In ophthalmology, it allows the physician to monitor diseases affecting the vascular networks of the retina such as agerelated macular degeneration or diabetic retinopathy. Due to the complexity of the vasculature in the retina, it is of interest to automatically extract vascular parameters which describe the condition of the vessels. Suitable parameters could improve the diagnosis and the treatment during the course of therapy. We present an automated algorithm to compute the diameters of the vessels in en face OCTA images. After segmenting the images, the vessel centerline was computed using a thinning algorithm. The centerline was refined by detecting invalid pixels such as spurs and by continuing the centerline until the ends of the vessels. Lastly, the diameter was computed by dilating a discrete circle at the position of the centerline or by measuring the distance between both borders of the vessels. The developed algorithms were applied to in vivo images of human eyes. Certainly, no ground truth was available. Hence, a plausibility check was performed by comparing the measured diameters of two different layers of the retina (Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC)). Each layer exhibits a different characteristic vasculature. The algorithm clearly reflected the differences from both retinal layers. The measured diameters demonstrate that the DVC consists of more capillaries and considerably smaller vessels compared to the SVC. The presented method enables automated analysis of the retinal vasculature and forms thereby the basis for monitoring diseases influencing the vasculature of the retina. The validation of the method using an artificial ground truth is still needed.

Transit times of a bolus through an organ can provide valuable information for researchers, technicians and clinicians. Therefore, an indicator is injected and the temporal propagation is monitored at two distinct locations. The transit time extracted from two indicator dilution curves can be used to calculate for example blood flow and thus provide the surgeon with important diagnostic information. However, the performance of methods to determine the transit time Δt cannot be assessed quantitatively due to the lack of a sufficient and trustworthy ground truth derived from in vivo measurements. Therefore, we propose a method to obtain an in silico generated dataset of differently subsampled indicator dilution curves with a ground truth of the transit time. This method allows variations on shape, sampling rate and noise while being accurate and easily configurable. COMSOL Multiphysics is used to simulate a laminar flow through a pipe containing blood analogue. The indicator is modelled as a rectangular function of concentration in a segment of the pipe. Afterwards, a flow is applied and the rectangular function will be diluted. Shape varying dilution curves are obtained by discrete-time measurement of the average dye concentration over different cross-sectional areas of the pipe. One dataset is obtained by duplicating one curve followed by subsampling, delaying and applying noise. Multiple indicator dilution curves were simulated, which are qualitatively matching in vivo measurements. The curves temporal resolution, delay and noise level can be chosen according to the requirements of the field of research. Various datasets, each containing two corresponding dilution curves with an existing ground truth transit time, are now available. With additional knowledge or assumptions regarding the detection-specific transfer function, realistic signal characteristics can be simulated. The accuracy of methods for the assessment of Δt can now be quantitatively compared and their sensitivity to noise evaluated.

Optical image processing is part of many applications used for brain surgeries. Microscope camera, or patient movement, like brain-movement through the pulse or a change in the liquor, can cause the image processing to fail. One option to compensate movement is feature detection and spatial allocation. This allocation is based on image features. The frame wise matched features are used to calculate the transformation matrix. The goal of this project was to evaluate different feature detectors based on spatial density and temporal robustness to reveal the most appropriate feature. The feature detectors included corner-, and blob-detectors and were applied on nine videos. These videos were taken during brain surgery with surgical microscopes and include the RGB channels. The evaluation showed that each detector detected up to 10 features for nine frames. The feature detector KAZE resulted in being the best feature detector in both density and robustness.

The segmentation and registration of structures are gaining importance due to the increasing demand of automated image enhancement and understanding. Especially in medicine and life science, assistance systems could have a large impact on diagnosis, treatment and quality control. Dye driven procedures, such as fluorescence imaging with Indocyanine green (ICG), are nowadays indispensable because they enhance contrast, reveal structures and deliver the operator with important information. The contact free ICG angiography is providing the surgeon spatial and temporal information on blood flow within a vessel. The processing of those information is done manually or semi automated but is very helpful for the surgeon. Extending the degree of automatism, the amount of information processed and even augment or transfer it into another domain could deliver the operator useful support and improve surgical work flow. Using, analyzing and transferring those information from ICG-IR domain into the RGB domain is the focus of this project. We are introducing a vessel registration method in the RGB domain driven by the spatial fluorescence behavior of the vessel in the ICG-IR domain. The method includes Superpixel based segmentation of the vessel in the ICG-IR domain, the spatial gradient based transfer and registration in the RGB domain and the continuous segmentation of the vessel in a RGB video. This paper show a proof of concept of the method. The results show an successful inter domain information transfer and registration of the vessel. Further tracking of the vessel over all frames is possible. Nevertheless limitations are revealed and discussed.

Image segmentation plays an increasingly important role in image processing. It allows for various applications including the analysis of an image for automatic image understanding and the integration of complementary data. During vascular surgeries, the blood flow in the vessels has to be checked constantly, which could be facilitated by a segmentation of the affected vessels. The segmentation of medical images is still done manually, which depends on the surgeon’s experience and is time-consuming. As a result, there is a growing need for automatic image segmentation methods. We propose an unsupervised method to detect the regions of no interest (RONI) in intraoperative images with low depth-of-field (DOF). The proposed method is divided into three steps. First, a color segmentation using a clustering algorithm is performed. In a second step, we assume that the regions of interest (ROI) are in focus whereas the RONI are unfocused. This allows us to segment the image using an edge-based focus measure. Finally, we combine the focused edges with the color RONI to determine the final segmentation result. When tested on different intraoperative images of aneurysm clipping surgeries, the algorithm is able to segment most of the RONI not belonging to the pulsating vessel of interest. Surgical instruments like the metallic clips can also be excluded. Although the image data for the validation of the proposed method is limited to one intraoperative video, a proof of concept is demonstrated.

In neurovascular surgery the intraoperative fluorescence angiography has been proven to be a reliable contact-free optical imaging technique to visualize vascular blood-flow. This angiography is obtained by injecting a fluorescence dye e.g. indocyanine green and using an infrared camera system to visualize the fluorescence inside the vessel. Obviously this requires a medical approved dye and an additional camera setup and therefore generating risks and costs. Hence, the aim of our research is to develop a comparable technique for assessing the vascular function. This approach would not require dye nor an additional infrared camera setup. It is achieved by first preprocessing the video data of a camera that records only the visible spectrum and then filter it spatially as well as temporally. The prepared data is again processed to extract information about the vascular function and visualize it. This method would provide an option to compute and visualize the vascular function using the data recorded in the visible spectrum by the surgical microscopes. Given this contact-free optical imaging system, physiological information can be easily provided to the surgeon without an additional setup. In the case of comparable results with the state-of-the-art, this technique provides a straightforward optical intraoperative angiography. Further no drug approval is needed since no dye is injected.

Background: Human-animal interactions in human services are on the rise, with an increased focus on the welfare of animals involved as well as on client safety. Based on scientifically based training methods, it has been proposed that horses involved in therapy settings could benefit from learning proactive strategies to reduce stress. One possible strategy is audible exhale communication (AEC). Inviting horses to actively use this strategy with humans could enhance the welfare of horses in equine-assisted therapy (EAT), thereby increasing client safety., Methods: A pilot project was conducted to test the feasibility of training 20 therapy horses to use AEC as a veto signal for an activity, while therapists responded to the signals. The number of audible exhales from the horses was compared between the initial and final training sessions. Furthermore, we tested whether age, years of training experience, and therapy experience served as moderating variables for the outcome. Additionally, qualitative observations were made by therapists working with the horses., Results: It has become apparent that training the horses to use AEC was successful. After 6 months of training, the horses showed a significantly higher number of audible exhales than in the initial training session, with a large effect size. Neither age nor years of training or therapy experience was found to be a moderating variable. The horses were eagerly engaged with newly acquired tools. These showed fewer indications of stress, greater sense of relaxation, and more positive emotions., Conclusion: Based on the findings of this pilot study, training horses to use AEC might be a feasible approach to reduce stress in horses working in therapeutic settings, increase client safety, enhance human-animal relationships, and open up new possibilities for improving the therapeutic process. This method is applicable to all horses, regardless of their age, training level, or experience in therapy. For future research, it would be interesting to replicate and extend the approach by addressing the aforementioned limitations and using a randomized controlled design to investigate the introduction and impact of AEC in a therapeutic setting and to gain more comprehensive insights.

Abstract Background Urinary tract infections are common affections, especially for women. Difficult access to a general practitioner to obtain a prescription has led France to offer dispensing under protocol by community pharmacists. The primary objective of this study is to evaluate the effectiveness of a pharmacist care protocol provided to manage women with urinary tract infection symptoms. This objective will be assessed using the Acute Cystitis Symptom Score. Methods PharmaCyst’ is an open-label, multicenter, controlled, cluster-randomized study conducted in the Loire region, France. Women aged between 18 and 65 years presenting to a pharmacy complaining of at least one symptom of an uncomplicated urinary tract infection present over the last 3 days (including burning pain during micturition, dysuria, pollakiuria, urgent urination) will be considered for inclusion. All patients will be contacted on day 3, 10, and month 3. A total of 480 patients need to be recruited for the 24 clusters participating in the research. The quantitative data will be described using means and standard deviations and compared using Student’s t-test. The qualitative data will be described using numbers and percentages and compared using chi2 test (or Fisher’s exact test if necessary). The primary and secondary outcomes analyses will consider the intention-to-treat population. Discussion PharmaCyst’ is the first clinical trial conducted in France only by community pharmacists. Its results could lead to an extension of the protocol. Trial registration The protocol has been approved by the French ethics committee on 2022/12/02 and is registered under the number 49RC22_0240 on ClinicalTrials.gov.

Abstract Background Physical activity referral schemes (PARS) are composed of various components, such as a written prescription or a person-centered approach. The role of these components in their effectiveness is yet to be understood. Therefore, we aimed to explore the relationships between PARS components and physical activity, scheme uptake, and adherence rate; and to estimate the effect of PARS. Methods We searched Scopus, PubMed, Web of Science, CINAHL, ScienceDirect, SpringerLink, HTA, Wiley Online Library, SAGE Journals, Taylor & Francis, Google Scholar, OpenGrey, and CORE. Eligible studies were published between 1990 and November 2023 in English or German, investigated PARS with participants aged ≥ 16 years, and reported physical activity, scheme uptake, or scheme adherence. Separate random-effects meta-analysis by comparison group were conducted for physical activity. Scheme uptake and adherence rates were pooled using proportional meta-analysis. The components were analyzed via univariate meta-regression. We rated the risk of bias using RoB2 and ROBINS-I, and the certainty of evidence using GRADE. Results Fifty-two studies were included. PARS were more effective in increasing physical activity than usual care (k = 11, n = 5046, Hedges’ g = 0.18, 95%CI 0.12 to 0.25; high certainty of evidence). When PARS were compared with physical activity advice or enhanced scheme versions, the pooled Hedges’ g values for physical activity were -0.06 (k = 5, n = 1082, 95%CI -0.21 to 0.10; low certainty of evidence), and 0.07 (k = 9, n = 2647, 95%CI -0.03 to 0.18; low certainty of evidence) respectively. Scheme uptake was 87% (95%CI 77% to 94%, k = 14, n = 5000) across experimental studies and 68% (95%CI 51% to 83%, k = 14, n = 25,048) across non-experimental studies. Pooled scheme adherence was 68% (95%CI 55% to 80%, k = 16, n = 3939) and 53% (95%CI 42% to 63%, k = 18, n = 14,605). The meta-regression did not detect any significant relationships between components and physical activity or scheme uptake. A person-centered approach, screening, and brief advice were positively associated with scheme adherence, while physical activity sessions were negatively associated. Conclusion PARS are more effective in increasing physical activity than usual care only. We did not identify any components as significant predictors of physical activity and scheme uptake. Four components predicted scheme adherence, indicating that the component-effectiveness relationship warrants further research.

Background: Recruitment of low risk blood donors can be challenging. Efforts should be made to increase the level of awareness and positive attitude towards blood donation. An essential step to achieve this is obtaining comprehensive data about the current situation of awareness, knowledge and attitudes of the population towards blood donation. Methods/materials: The present study was conducted at two blood donation centres in Amman, Jordan, during 2021. A total of 536 whole blood donors were included. Data regarding their demographic characteristics, blood donation history as well as their knowledge and attitudes regarding blood donation were collected by a questionnaire. Results: Four hundred ninety participants (91.4%) were males, whereas only 46 participants (8.6%) were females. Ninety seven subjects (18.1%) were first time donors, whereas 431 subjects (81.9%) had previous donations. The participants’ median score in the knowledge section was 19.0 points (range 5–25 points). Based on a cut-off of 15 out of 28: 84% of the participants were knowledgeable. Similarly 97% of the participants had a positive attitude based on a cut-off of 17 out of 32 points. Multivariate analysis revealed that high knowledge score was significantly associated with study major and employment status, whereas a positive attitude was significantly associated with a higher income. More than half of first time donors stated lack of awareness as being the reason for not donating blood before. Conclusion: Measures to improve awareness, knowledge and attitudes towards blood donation should be implemented in order to meet the increasing demand for blood and blood components. Targeted campaigns, correction of some misconceptions and using different motivations are suggested.

Bioelectric signal classification is a flourishing area of biomedical research, however conducting this research in a clinical setting can be difficult to achieve. The lack of inexpensive acquisition hardware can limit researchers from collecting and working with real-time data. Furthermore, hardware requiring direct connection to a computer can impose restrictions on typically mobile clinical settings for data collection. Here, we present an open-source ADS1299-based bioelectric signal acquisition system with wireless capability suitable for mobile data collection in clinical settings. This system is based on the ADS_BP and BioPatRec, both open-source bioelectric signal acquisition hardware and MATLAB-based pattern recognition software, respectively. We provide 3D-printable housing enabling the hardware to be worn by users during experiments and demonstrate the suitability of this platform for real-time signal acquisition and classification. In conjunction, these developments provide a unified hardware-software platform for a cost of around ${\$}$ 150 USD. This device can enable researchers and clinicians to record bioelectric signals from non-disabled or motor-impaired individuals in laboratory or clinical settings, and to perform offline or real-time intent classification for the control of robotic and virtual devices.

Background: This study examined age-group differences in the rate, severity, and cost of injuries among construction workers to support evidence-based worker safety and health interventions in the construction industry. Methods: Ohio workers' compensation claims for construction workers were used to estimate claim rates and costs by age group. We analyzed claims data auto-coded into five event/exposure categories: transportation incidents; slips, trips, and falls (STFs); exposure to harmful substances and environments; contact with objects and equipment (COB); overexertion and bodily reaction. American Community Survey data were used to determine the percentage of workers in each age group. Results: From 2007–2017, among 72,416 accepted injury claims for ∼166,000 construction full-time equivalent (FTE) per year, nearly half were caused by COB, followed by STFs (20%) and overexertion (20%). Claim rates related to COB and exposure to harmful substances and environments were highest among those 18–24 years old, with claim rates of 313.5 and 25.9 per 10,000 FTE, respectively. STFs increased with age, with the highest claim rates for those 55–64 years old (94.2 claims per 10,000 FTE). Overexertion claim rates increased and then declined with age, with the highest claim rate for those 35–44 years old (87.3 per 10,000 FTE). While younger workers had higher injury rates, older workers had higher proportions of lost-time claims and higher costs per claim. The total cost per FTE was highest for those 45–54 years old ($1,122 per FTE). Conclusion: The variation in rates of injury types by age suggests that age-specific prevention strategies may be useful.

Objectives This study evaluated stakeholders’ experiences of participating in a coproduction process to develop a physical activity referral scheme (PARS) in the German healthcare system. The focus was on examining facilitators and challenges, along with gathering insights on potential modifications to the joint development process, all from the viewpoint of stakeholders.Design This qualitative study employed one-to-one semi-structured interviews, and the findings were analysed using summarising qualitative content analysis.Setting The study focused on the German healthcare system.Participants Seven stakeholders from the coproduction process were purposefully selected for interviews using maximum variation sampling. The interviewees represented different sectors (physician associations, physical activity professionals’ associations, health insurance companies and patient organisations), various positions within their organisations, and different levels of attendance during the coproduction process.Results In almost all interviews, the following factors were highlighted as facilitators of the development process: coproduction approach, process of coproduction, multi-sector stakeholder group, possibility of active participation, coordinating role of researchers, communication, atmosphere and interaction. In contrast, differences in roles and hierarchy, merging of different perspectives, clarification of intervention costs, and competition and conflicting interests were pointed out as challenges. Only a few suggestions regarding adaptations in terms of group composition and cooperation among stakeholders were mentioned.Conclusions Stakeholder experiences with the joint development process were predominantly positive, indicating that coproduction is a beneficial approach for the development of PARS intended for integration into healthcare systems. The effective management of power differences among stakeholders is intricately tied to the coproduction method; therefore, it should be selected carefully. The research team plays a pivotal role in coordinating and negotiating the process, and the team should be equipped with a diverse set of skills and knowledge, particularly to understand the intricacies of the healthcare system where the PARS is intended for implementation.Trial registration number NCT04947787.

Uncomplicated cystitis is affecting many women of all ages and has a great impact on the quality of life, especially in women suffering from recurrent, uncomplicated cystitis. By far the most frequent uropathogen, , may have acquired increasing resistance against a variety of oral antibiotics, which may differ between countries and regions. Therefore, local resistance data are important to be considered. On the other hand, non-antibiotic therapy has also become an option which should be discussed and offered to the patient. In patients suffering from recurrent uncomplicated cystitis, individual risk factors and ehavioral changes should first be taken into account. Non-antimicrobial prophylactic strategies shown to be successful in well-designed clinical studies are the next options. Long term antibiotic prophylaxis, however, should only be considered as a last option. For some of those patients self-diagnosis and self-treatment may be suitable, e.g. by using a recognized questionnaire.