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Multi-Frequency Approach to Estimate the Roughness of Lung Surface, in silico Study

Lung ultrasound (LUS) represents an important tool to evaluate the state of lung surface. However, LUS is limited to the visual evaluation of imaging artifacts, especially the vertical ones that correlate with pathologies characterized by a reduction of air-spaces (alveoli) dimensions. In contrast, in other pathologies (e.g. chronic obstructive pulmonary diseases) an enlargement of the air-spaces may occur. This causes the lung surface to behave essentially as a perfect reflector, not allowing ultrasound penetration. As air-spaces of different sizes can generate different levels of roughness at the lung surface, the estimation of roughness could provide a way to characterize the state of lung surface. In this in silico study, we present a multi-frequency quantitative approach aiming at estimating the lung surface's roughness by measuring the image intensity variation along the lung surface as a function of frequency.