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Khokhlova TD, Thomas GP, Hall J, Steinbock K, Thiel J, Cunitz BW, Bailey MR, Anderson L, Kessler R, Hall MK, Adedipe AA. Development of an Automated Ultrasound Signal Indicator of Lung Interstitial Syndrome. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:513-523. [PMID: 38050780 PMCID: PMC10922254 DOI: 10.1002/jum.16383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/26/2023] [Accepted: 11/18/2023] [Indexed: 12/06/2023]
Abstract
OBJECTIVES The number and distribution of lung ultrasound (LUS) imaging artifacts termed B-lines correlate with the presence of acute lung disease such as infection, acute respiratory distress syndrome (ARDS), and pulmonary edema. Detection and interpretation of B-lines require dedicated training and is machine and operator-dependent. The goal of this study was to identify radio frequency (RF) signal features associated with B-lines in a cohort of patients with cardiogenic pulmonary edema. A quantitative signal indicator could then be used in a single-element, non-imaging, wearable, automated lung ultrasound sensor (LUSS) for continuous hands-free monitoring of lung fluid. METHODS In this prospective study a 10-zone LUS exam was performed in 16 participants, including 12 patients admitted with acute cardiogenic pulmonary edema (mean age 60 ± 12 years) and 4 healthy controls (mean age 44 ± 21). Overall,160 individual LUS video clips were recorded. The LUS exams were performed with a phased array probe driven by an open-platform ultrasound system with simultaneous RF signal collection. RF data were analyzed offline for candidate B-line indicators based on signal amplitude, temporal variability, and frequency spectrum; blinded independent review of LUS images for the presence or absence of B-lines served as ground truth. Predictive performance of the signal indicators was determined with receiving operator characteristic (ROC) analysis with k-fold cross-validation. RESULTS Two RF signal features-temporal variability of signal amplitude at large depths and at the pleural line-were strongly associated with B-line presence. The sensitivity and specificity of a combinatorial indicator were 93.2 and 58.5%, respectively, with cross-validated area under the ROC curve (AUC) of 0.91 (95% CI = 0.80-0.94). CONCLUSION A combinatorial signal indicator for use with single-element non-imaging LUSS was developed to facilitate continuous monitoring of lung fluid in patients with respiratory illness.
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Affiliation(s)
- Tatiana D Khokhlova
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Center for Industrial and Medical Ultrasound, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA
| | - Gilles P Thomas
- Center for Industrial and Medical Ultrasound, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA
| | - Jane Hall
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
| | - Kyle Steinbock
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
| | - Jeff Thiel
- Center for Industrial and Medical Ultrasound, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA
| | - Bryan W Cunitz
- Center for Industrial and Medical Ultrasound, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA
| | - Michael R Bailey
- Center for Industrial and Medical Ultrasound, Applied Physics Laboratory, University of Washington, Seattle, Washington, USA
| | - Layla Anderson
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
| | - Ross Kessler
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
| | - M Kennedy Hall
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
| | - Adeyinka A Adedipe
- Department of Emergency Medicine, University of Washington School of Medicine, Seattle, Washington, USA
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