We have shown that a simple algorithm, based on time-frequency analysis of bladder pressure, may be a promising tool in the clinical setting. The algorithm can provide quantitative data on non-voiding bladder activity in patients and quantify the changes according to phenotype. Moreover the algorithm can detect DO, showing potential for triggering conditional bladder stimulation.

IntroductionArteriovenous malformations (AVMs) are characterized by pathological high flow, low resistance connections between arteries and veins. Treatment is critically dependent on correct interpretation of angioarchitectural features. However, some microfistular AVMs do not match the characteristics described in current AVM classification systems. Therefore, we propose a new subgroup of microfistular AVMs, composed of enlarged, fistulous paths on the venous half of capillaries and/or dilated draining venules (hyperdynamic, capillary-venulous malformation [CV-AVM]). CV-AVMs still ensure arterial flow to the periphery and fistulous venous drainage is less pronounced than in classical AVMs such that these lesions are often misinterpreted as venous malformations.Materials and methodsWe developed a computational model to study the effects of microvascular anomalies on local hemodynamics, as well as their impact on angiographic contrast propagation. Flow rates and pressures were computed with a lumped parameter description, while contrast propagation was determined by solving the 1D advection-diffusion equation.Results and conclusionsFor the newly proposed CV-AVM angioarchitecture, the computational model predicts increased arterio-venous contrast agent transit times and highly dispersive transport characteristics, compared to microfistular, interstitial type IV AVMs and high flow type II and III AVMs. We related these findings to time-contrast intensity curves sampled from clinical angiographies and found that there is strong evidence for the existence of CV-AVM.

The present work aims to describe the detectability limits of hypoxic regions in human muscle under moderate thicknesses of adipose tissue to serve as a groundwork for the development of a wearable device to prevent pressure injuries. The optimal source-detector distances, detection limits, and the spatial resolution of hypoxic volumes in the human muscle are calculated using finite element method-based computer simulations conducted on 3-layer tissue models. Silicone phantoms matching the simulation geometries were manufactured, and their measurement results were compared to the simulations. The simulations showed good agreement with the performed experiments. Our results show detectability of hypoxic volumes under adipose tissue thicknesses of up to 1.5 cm. The maximum tissue depth, at which hypoxic volumes could be detected was 2.8 cm. The smallest detectable hypoxic volume in our study was 1.2 cm3. We thus show the detectability of hypoxic volumes in sizes consistent with those of early-stage pressure injury formation and, consequently, the feasibility of a device to prevent pressure injuries.

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