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Diagnostic accuracy of a novel software technology for detecting pneumothorax in a porcine model

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Introduction: Our objective was to measure the diagnostic accuracy of a novel software technology to detect pneumothorax on Brightness (B) mode and Motion (M) mode ultrasonography. Methods: Ultrasonography fellowship‐trained emergency… Click to show full abstract

Introduction: Our objective was to measure the diagnostic accuracy of a novel software technology to detect pneumothorax on Brightness (B) mode and Motion (M) mode ultrasonography. Methods: Ultrasonography fellowship‐trained emergency physicians performed thoracic ultrasonography at baseline and after surgically creating a pneumothorax in eight intubated, spontaneously breathing porcine subjects. Prior to pneumothorax induction, we captured sagittal M‐mode still images and B‐mode videos of each intercostal space with a linear array transducer at 4 cm of depth. After collection of baseline images, we placed a chest tube, injected air into the pleural space in 250 mL increments, and repeated the ultrasonography for pneumothorax volumes of 250 mL, 500 mL, 750 mL, and 1000 mL. We confirmed pneumothorax with intrapleural digital manometry and ultrasound by expert sonographers. We exported collected images for interpretation by the software. We treated each individual scan as a single test for interpretation by the software. Results: Excluding indeterminate results, we collected 338 M‐mode images for which the software demonstrated a sensitivity of 98% (95% confidence interval [CI] 92–99%), specificity of 95% (95% CI 86–99), positive likelihood ratio (LR +) of 21.6 (95% CI 7.1–65), and negative likelihood ratio (LR −) of 0.02 (95% CI 0.008–0.046). Among 364 B‐mode videos, the software demonstrated a sensitivity of 86% (95% CI 81–90%), specificity of 85% (81–91%), LR + of 5.7 (95% CI 3.2–10.2), and LR − of 0.17 (95% CI 0.12–0.22). Conclusions: This novel technology has potential as a useful adjunct to diagnose pneumothorax on thoracic ultrasonography.

Keywords: novel software; pneumothorax; diagnostic accuracy; accuracy novel; technology; software

Journal Title: American Journal of Emergency Medicine
Year Published: 2017

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