State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses

Federico Mento, Umair Khan, Francesco Faita, Andrea Smargiassi, Riccardo Inchingolo, Tiziano Perrone, Libertario Demi, Federico Mento, Umair Khan, Francesco Faita, Andrea Smargiassi, Riccardo Inchingolo, Tiziano Perrone, Libertario Demi

Abstract

Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical relevance of vertical artifacts was first reported. However, the massive spread of LUS is only recent and is associated with the coronavirus disease 2019 (COVID-19) pandemic, during which semi-quantitative computer-aided techniques were proposed to automatically classify LUS data. In this review, we discuss the state of the art in LUS, from semi-quantitative image analysis approaches to quantitative techniques involving the analysis of radiofrequency data. We also discuss recent in vitro and in silico studies, as well as research on LUS safety. Finally, conclusions are drawn highlighting the potential future of LUS.

Keywords: Artificial intelligence; Image processing; In vitro; In vivo; Lung ultrasound; Quantitative lung ultrasound; Review; Signal processing.

Conflict of interest statement

Declaration of Competing Interest All authors declare no conflicts of interest.

Copyright © 2022 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Figures

Fig. 1
Fig. 1
Examples of lung ultrasound images acquired with convex (top) and linear (bottom) probes. Pleural lines, horizontal artifacts, vertical artifacts and consolidations are indicated in blue, orange, red, and green, respectively.
Fig. 2
Fig. 2
Simplified flowchart depicting the different applications of quantitative and semiquantitative LUS techniques. LUS = lung ultrasound; RF = radiofrequency.

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Source: PubMed

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