Development of an Automated Ultrasound Signal Indicator of Lung Interstitial Syndrome

Author:

Khokhlova Tatiana D.12ORCID,Thomas Gilles P.2,Hall Jane3,Steinbock Kyle3,Thiel Jeff2,Cunitz Bryan W.2,Bailey Michael R.2,Anderson Layla3,Kessler Ross3,Hall M. Kennedy3,Adedipe Adeyinka A.3

Affiliation:

1. Department of Medicine University of Washington Seattle Washington USA

2. Center for Industrial and Medical Ultrasound, Applied Physics Laboratory University of Washington Seattle Washington USA

3. Department of Emergency Medicine University of Washington School of Medicine Seattle Washington USA

Abstract

ObjectivesThe 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.MethodsIn 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.ResultsTwo 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).ConclusionA 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.

Funder

National Institute of Biomedical Imaging and Bioengineering

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

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