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

doi:10.1016/j.ultrasmedbio.2022.07.007

Review

. 2022 Dec;48(12):2398-2416.

doi: 10.1016/j.ultrasmedbio.2022.07.007. Epub 2022 Sep 23.

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

Federico Mento¹, Umair Khan¹, Francesco Faita², Andrea Smargiassi³, Riccardo Inchingolo³, Tiziano Perrone⁴, Libertario Demi⁵

Affiliations

¹ Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.
² Institute of Clinical Physiology, National Research Council, Pisa, Italy.
³ Department of Cardiovascular and Thoracic Sciences, Pulmonary Medicine Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
⁴ Emergency Department, Humanitas Gavazzeni, Bergamo, Italy.
⁵ Department of Information Engineering and Computer Science, University of Trento, Trento, Italy. Electronic address: libertario.demi@unitn.it.

PMID: 36155147
PMCID: PMC9499741
DOI: 10.1016/j.ultrasmedbio.2022.07.007

Review

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

Federico Mento et al. Ultrasound Med Biol. 2022 Dec.

. 2022 Dec;48(12):2398-2416.

doi: 10.1016/j.ultrasmedbio.2022.07.007. Epub 2022 Sep 23.

Authors

Federico Mento¹, Umair Khan¹, Francesco Faita², Andrea Smargiassi³, Riccardo Inchingolo³, Tiziano Perrone⁴, Libertario Demi⁵

Affiliations

¹ Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.
² Institute of Clinical Physiology, National Research Council, Pisa, Italy.
³ Department of Cardiovascular and Thoracic Sciences, Pulmonary Medicine Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
⁴ Emergency Department, Humanitas Gavazzeni, Bergamo, Italy.
⁵ Department of Information Engineering and Computer Science, University of Trento, Trento, Italy. Electronic address: libertario.demi@unitn.it.

PMID: 36155147
PMCID: PMC9499741
DOI: 10.1016/j.ultrasmedbio.2022.07.007

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.

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Conflict of interest statement

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

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.

See this image and copyright information in PMC

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References

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1. Almeida A, Bilbao A, Ruby L, Rominger MB, Lopez-De-Ipina D, Dahl J, Elkaffas A, Sanabria SJ. Lung ultrasound for point-of-care COVID-19 pneumonia stratification: Computer-aided diagnostics in a smartphone. First experiences classifying semiology from public datasets. Proc IEEE Int Ultrason Symp. 2020:1–4.
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1. Awasthi N, Dayal A, Cenkeramaddi LR, Yalavarthy PK. Mini-COVIDNet: Efficient lightweight deep neural network for ultrasound based point-of-care detection of COVID-19. IEEE Trans Ultrason Ferroelectr Freq Control. 2021;68:2023–2037. - PMC - PubMed

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[1] Allinovi M, Parise A, Giacalone M, Amerio A, Delsante M, Odone A, Franci A, Gigliotti F, Amadasi S, Delmonte D, Parri N, Mangia A. Lung ultrasound may support diagnosis and monitoring of COVID-19 pneumonia. Ultrasound Med Biol. 2020;46:2908–2917. - PMC - PubMed

[2] Allinovi M, Parise A, Giacalone M, Amerio A, Delsante M, Odone A, Franci A, Gigliotti F, Amadasi S, Delmonte D, Parri N, Mangia A. Lung ultrasound may support diagnosis and monitoring of COVID-19 pneumonia. Ultrasound Med Biol. 2020;46:2908–2917. - PMC - PubMed

[3] Almeida A, Bilbao A, Ruby L, Rominger MB, Lopez-De-Ipina D, Dahl J, Elkaffas A, Sanabria SJ. Lung ultrasound for point-of-care COVID-19 pneumonia stratification: Computer-aided diagnostics in a smartphone. First experiences classifying semiology from public datasets. Proc IEEE Int Ultrason Symp. 2020:1–4.

[4] Almeida A, Bilbao A, Ruby L, Rominger MB, Lopez-De-Ipina D, Dahl J, Elkaffas A, Sanabria SJ. Lung ultrasound for point-of-care COVID-19 pneumonia stratification: Computer-aided diagnostics in a smartphone. First experiences classifying semiology from public datasets. Proc IEEE Int Ultrason Symp. 2020:1–4.

[5] Anantrasirichai N, Hayes W, Allinovi M, Bull D, Achim A. Line detection as an inverse problem: Application to lung ultrasound imaging. IEEE Trans Medical Imaging. 2017;36:2045–2056. - PMC - PubMed

[6] Anantrasirichai N, Hayes W, Allinovi M, Bull D, Achim A. Line detection as an inverse problem: Application to lung ultrasound imaging. IEEE Trans Medical Imaging. 2017;36:2045–2056. - PMC - PubMed

[7] Avruch L, Cooperberg PL. The ring-down artifact. J Ultrasound Med. 1985;4:21–28. - PubMed

[8] Avruch L, Cooperberg PL. The ring-down artifact. J Ultrasound Med. 1985;4:21–28. - PubMed

[9] Awasthi N, Dayal A, Cenkeramaddi LR, Yalavarthy PK. Mini-COVIDNet: Efficient lightweight deep neural network for ultrasound based point-of-care detection of COVID-19. IEEE Trans Ultrason Ferroelectr Freq Control. 2021;68:2023–2037. - PMC - PubMed

[10] Awasthi N, Dayal A, Cenkeramaddi LR, Yalavarthy PK. Mini-COVIDNet: Efficient lightweight deep neural network for ultrasound based point-of-care detection of COVID-19. IEEE Trans Ultrason Ferroelectr Freq Control. 2021;68:2023–2037. - PMC - PubMed

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

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

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Affiliations

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Conflict of interest statement

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