The presence of reactive species in plasma-activated water is known to induce oxidative stresses in bacterial species, which can result in their inactivation. By integrating a microfludic chipscale nebulizer driven by surface acoustic waves (SAWs) with a low-temperature atmospheric plasma source, we demonstrate an efficient technique for in situ production and application of plasma-activated aerosols for surface disinfection. Unlike bulk conventional systems wherein the water is separately batch-treated within a container, we show in this work the first demonstration of continuous plasma-treatment of water as it is transported through a paper strip from a reservoir onto the chipscale SAW device. The significantly larger surface area to volume ratio of the water within the paper strip leads to a significant reduction in the duration of the plasma-treatment, while maintaining the concentration of the reactive species. The subsequent nebulization of the plasma-activated water by the SAW then allows the generation of plasma-activated aerosols, which can be directly sprayed onto the contaminated surface, therefore eliminating the storage of the plasma-activated water and hence circumventing the typical limitation in conventional systems wherein the concentration of the reactive species diminishes over time during storage, resulting in a reduction in the efficacy of bacterial inactivation. In particular, we show up to 96% reduction in Escherichia coli colonies through direct spraying with the plasma-activated aerosols. This novel, low-cost, portable and energy-efficient hybrid system necessitates only minimal maintenance as it only requires the supply of tap water and battery power for operation, and is thus suitable for decontamination in home environments.
Early detection of chronic kidney disease is important to prevent progression of irreversible kidney damage, reducing the need for renal transplantation. Shear wave elastography is ideal as a quantitative imaging modality to detect chronic kidney disease because of its non-invasive nature, low cost and portability, making it highly accessible. However, the complexity of the kidney architecture and its tissue properties give rise to various confounding factors that affect the reliability of shear wave elastography in detecting chronic kidney disease, thus limiting its application to clinical trials. The objective of this review is to highlight the confounding factors presented by the complex properties of the kidney, in addition to outlining potential mitigation strategies, along with the prospect of increasing the versatility and reliability of shear wave elastography in detecting chronic kidney disease.
The application of ultrasound shear wave elastography for detecting chronic kidney disease, namely renal fibrosis, has been widely studied. A good correlation between tissue Young's modulus and the degree of renal impairment has been established. However, the current limitation of this imaging modality pertains to the linear elastic assumption used in quantifying the stiffness of renal tissue in commercial shear wave elastography systems. As such, when underlying medical conditions such as acquired cystic kidney disease, which may potentially influence the viscous component of renal tissue, is present concurrently with renal fibrosis, the accuracy of the imaging modality in detecting chronic kidney disease may be affected. The findings in this study demonstrate that quantifying the stiffness of linear viscoelastic tissue using an approach similar to those implemented in commercial shear wave elastography systems led to percentage errors as high as 87%. The findings presented indicate that use of shear viscosity to detect changes in renal impairment led to a reduction in percentage error to values as low as 0.3%. For cases in which renal tissue was affected by multiple medical conditions, shear viscosity was found to be a good indicator in gauging the reliability of the Young's modulus (quantified through a shear wave dispersion analysis) in detecting chronic kidney disease. The findings show that percentage error in stiffness quantification can be reduced to as low as 0.6%. The present study demonstrates the potential use of renal shear viscosity as a biomarker to improve the detection of chronic kidney disease.
Renal anisotropy is a complex property of the kidney and often poses a challenge in obtaining consistent measurements when using shear wave elastography to detect chronic kidney disease. To circumvent the challenge posed by renal anisotropy in clinical settings, a dimensionless biomarker termed the 'anisotropic ratio' was introduced to establish a correlation between changes in degree of renal anisotropy and progression of chronic kidney disease through an in silico perspective. To achieve this, an efficient model reduction approach was developed to model the anisotropic property of kidneys. Good agreement between the numerical and experimental data were obtained, as percentage errors of less than 5.5% were reported when compared against experimental phantom measurement from the literature. To demonstrate the applicability of the model to clinical measurements, the anisotropic ratio of sheep kidneys was quantified, with both numerical and derived experimental results reporting a value of .667. Analysis of the anisotropic ratio with progression of chronic kidney disease demonstrated that patients with normal kidneys would have a lower anisotropic ratio of .872 as opposed to patients suffering from renal impairment, in which the anisotropic ratio may increase to .904, as determined from this study. The findings demonstrate the potential of the anisotropic ratio in improving the detection of chronic kidney disease using shear wave elastography.