Quantitative lung ultrasonography: a putative new algorithm for automatic detection and quantification of B-lines.


Journal

Critical care (London, England)
ISSN: 1466-609X
Titre abrégé: Crit Care
Pays: England
ID NLM: 9801902

Informations de publication

Date de publication:
28 Aug 2019
Historique:
received: 28 02 2019
accepted: 16 08 2019
entrez: 29 8 2019
pubmed: 29 8 2019
medline: 25 2 2020
Statut: epublish

Résumé

This pilot study was designed to develop a fully automatic and quantitative scoring system of B-lines (QLUSS: quantitative lung ultrasound score) involving the pleural line and to compare it with previously described semi-quantitative scores in the measurement of extravascular lung water as determined by standard thermo-dilution. This was a prospective observational study of 12 patients admitted in the intensive care unit with acute respiratory distress and each provided with 12 lung ultrasound (LUS) frames. Data collected from each patient consisted in five different scores, four semi-quantitative (nLUSS, cLUSS, qLUSS, %LUSS) and quantitative scores (QLUSS). The association between LUS scores and extravascular lung water (EVLW) was determined by simple linear regression (SLR) and robust linear regression (RLR) methods. A correlation analysis between the LUS scores was performed by using the Spearman rank test. Inter-observer variability was tested by computing intraclass correlation coefficient (ICC) in two-way models for agreement, basing on scores obtained by different raters blinded to patients' conditions and clinical history. In the SLR, QLUSS showed a stronger association with EVLW (R This study demonstrates that computer-aided scoring of the pleural line percentage affected by B-lines has the potential to assess EVLW. QLUSS may have a significant impact, once validated with a larger dataset composed by multiple real-time frames. This approach has the potentials to be advantageous in terms of faster data analysis and applicability to large sets of data without increased costs. On the contrary, it is not useful in pleural effusion or consolidations.

Sections du résumé

BACKGROUND BACKGROUND
This pilot study was designed to develop a fully automatic and quantitative scoring system of B-lines (QLUSS: quantitative lung ultrasound score) involving the pleural line and to compare it with previously described semi-quantitative scores in the measurement of extravascular lung water as determined by standard thermo-dilution.
METHODS METHODS
This was a prospective observational study of 12 patients admitted in the intensive care unit with acute respiratory distress and each provided with 12 lung ultrasound (LUS) frames. Data collected from each patient consisted in five different scores, four semi-quantitative (nLUSS, cLUSS, qLUSS, %LUSS) and quantitative scores (QLUSS). The association between LUS scores and extravascular lung water (EVLW) was determined by simple linear regression (SLR) and robust linear regression (RLR) methods. A correlation analysis between the LUS scores was performed by using the Spearman rank test. Inter-observer variability was tested by computing intraclass correlation coefficient (ICC) in two-way models for agreement, basing on scores obtained by different raters blinded to patients' conditions and clinical history.
RESULTS RESULTS
In the SLR, QLUSS showed a stronger association with EVLW (R
CONCLUSIONS CONCLUSIONS
This study demonstrates that computer-aided scoring of the pleural line percentage affected by B-lines has the potential to assess EVLW. QLUSS may have a significant impact, once validated with a larger dataset composed by multiple real-time frames. This approach has the potentials to be advantageous in terms of faster data analysis and applicability to large sets of data without increased costs. On the contrary, it is not useful in pleural effusion or consolidations.

Identifiants

pubmed: 31455421
doi: 10.1186/s13054-019-2569-4
pii: 10.1186/s13054-019-2569-4
pmc: PMC6712728
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

288

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Auteurs

Claudia Brusasco (C)

Anaesthesia and Intensive Care Unit, E.O. Ospedali Galliera, Genova, Italy.

Gregorio Santori (G)

Department of Surgical Sciences and Integrated Diagnostics, University of Genoa, Genoa, Italy.

Elisa Bruzzo (E)

Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genova, Genova, Italy.

Rosella Trò (R)

Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genova, Genova, Italy.

Chiara Robba (C)

Anaesthesia and Intensive Care, San Martino Policlinico Hospital, IRCCS for Oncology, Genoa, Italy.

Guido Tavazzi (G)

Department of Clinical, Surgical, Diagnostic and Pediatric Sciences. Intensive Care Unit, Fondazione Policlinico San Matteo IRCCS, University of Pavia, Pavia, Italy.

Fabio Guarracino (F)

Department of Anaesthesia and Critical Care Medicine, Cardiothoracic and Vascular Anaesthesia and Intensive Care, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.

Francesco Forfori (F)

Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy.

Patrizia Boccacci (P)

Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genova, Genova, Italy.

Francesco Corradi (F)

Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy. francescorradi@gmail.com.
Anaesthesia and Intensive Care Unit, E.O. Ospedali Galliera, Via Mura delle Cappuccine 14, Genova, Italy. francescorradi@gmail.com.

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Classifications MeSH