Physiological swelling imaging in human calf under stocking compression by sparse Bayesian learning implemented into electrical impedance tomography (SBL-EIT)

TL;DR

This study uses a new imaging technique to evaluate how different stocking pressures affect swelling in the human calf.

Contribution

The novel contribution is implementing sparse Bayesian learning in electrical impedance tomography to image physiological swelling under compression.

Findings

Stronger compression pressures resulted in lower spatial-mean conductivity in calves.

Conductivity measurements correlated with bioelectrical impedance analysis during prolonged standing.

Susceptibility to swelling varied based on internal and external factors like SAT and posture.

Abstract

Physiological swelling in human calf has been imaged under stocking compression by the sparse Bayesian learning implemented into electrical impedance tomography (SBL-EIT) to evaluate the in situ treatment effect of various compression pressures. SBL-EIT reconstructs conductivity distribution \documentclass[12pt]{minimal}
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\begin{document}$$\Delta {\boldsymbol{\upsigma}}$$\end{document} to image excessive extracellular fluid in subcutaneous adipose tissue (SAT), indicating the susceptibilities to physiological swelling due to various compression pressures. The SBL-EIT was applied to the imaging of eight-subject calves during prolonged standing under three types of net compression pressures Pnet measured by pressure sensor – strong pressure: Pnet, Strong = 11.9 \documentclass[12pt]{minimal}
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\begin{document}$$\pm $$\end{document} 2.0 mmHg, weak pressure: Pnet, Weak = 4.47 \documentclass[12pt]{minimal}
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\begin{document}$$\pm $$\end{document} 3.1 mmHg, and control pressure: Pnet, Control = 0.00 \documentclass[12pt]{minimal}
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\begin{document}$$\pm $$\end{document} 0.0 mmHg, respectively. From the experimental results, the spatial-mean conductivity ⟨σ⟩α2 with two pre-processing steps to eliminate undesirable effects, i.e., the difference in skin condition and effect of wearing stockings itself, is the highest in the case of stocking with control pressure, followed by weak and strong pressures across all subjects. Moreover, the ⟨σ⟩α2 has a strong positive correlation with the conventional inversed impedance 1/zBIA by bioelectrical impedance analysis (BIA) (a correlation coefficient 0.528 < R < 0.990; n = 19 and p < 0.05), which is mainly increased during the prolonged standing. Moreover, various susceptibilities to physiological swelling are investigated based on the increase in \documentclass[12pt]{minimal}
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\begin{document}$$\Delta {\boldsymbol{\upsigma}}$$\end{document} for each subject, which is associated with subject external factors such as postural changes and circumference and internal factors like SAT.

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