Abstract

There exist lung pathologies (e.g., COPD) characterized by an enlargement of air-spaces. Since air-spaces of different sizes can generate different levels of roughness along the lung surface, estimating the roughness may provide an indirect characterization of the lung state. This study, thus, analyzes the possibility to develop a multi-frequency quantitative approach forthe estimation of lung surface roughness. Specifically, the presented technique focuses on the analysis of ultrasound image intensity variation along the lung surface as a function of frequency. In silico and in vitro results will be presented. First, k-wave was used to study the effect of different levels of lung surface roughness on numerically generated ultrasound images. Data were simulated with center frequencies from 1 to 10 MHz (bandwidth = 0.5 MHz). The same acquisition strategy was then used to acquire data from 3D printed steel models, made to mimic an acoustic interface with high reflection coefficient (similar to air-tissue interfaces) and realized with different levels of roughness. As expected, due to diffuse scattering, the increase of the “air-spaces” diameter is linked to a decrease of the frequency at which a significant drop of intensity was observed. This ultimately provides a way to indirectly estimate lung source roughness.

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