Point-of-Care Diagnostic Device for Traumatic Pneumothorax: Low Sensitivity of the Unblinded PneumoScan™

A wearable microwave instrument can detect and monitor traumatic abdominal injuries in a porcine model

Abdominal injury is a frequent cause of death for trauma patients, and early recognition is essential to limit fatalities. There is a need for a wearable sensor system for prehospital settings that can detect and monitor bleeding in the abdomen (hemoperitoneum). This study evaluates the potential for microwave technology to fill that gap. A simple prototype of a wearable microwave sensor was constructed using eight antennas. A realistic porcine model of hemoperitoneum was developed using anesthetized pigs. Ten animals were measured at healthy state and at two sizes of bleeding. Statistical tests and a machine learning method were used to evaluate blood detection sensitivity. All subjects presented similar changes due to accumulation of blood, which dampened the microwave signal (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p < 0.05$$\end{document}p<0.05). The machine learning analysis yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.93, showing 100% sensitivity at 90% specificity. Large inter-individual variability of the healthy state signal complicated differentiation of bleedings from healthy state. A wearable microwave instrument has potential for accurate detection and monitoring of hemoperitoneum, with automated analysis making the instrument easy-to-use. Future hardware development is necessary to suppress measurement system variability and enable detection of smaller bleedings.

Hemopneumothorax detection through the process of artificial evolution - a feasibility study

BACKGROUND

Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techniques are not fully applicable in field conditions and on the battlefield, where situational and environmental factors may impair clinical capabilities. We aimed to assemble a device able to sample, analyze, and classify the unique acoustic signatures of pneumothorax and hemothorax.

METHODS

Acoustic data was obtained with simultaneous use of two sensitive digital stethoscopes from the chest wall of an ex-vivo porcine model. Twelve second samples of acoustic data were obtained from the in-house assembled digital stethoscope system during mechanical ventilation. The thoracic cavity was injected with increasing volumes of 200, 400, 600, 800, and 1000 ml of air or saline to simulate pneumothorax and hemothorax, respectively. The data was analyzed using a multi-objective genetic algorithm that was used to develop an optimal mathematical detector through the process of artificial evolution, a cutting-edge approach in the artificial intelligence discipline.

RESULTS

The in-house assembled dual digital stethoscope system and developed genetic algorithm achieved an accuracy, sensitivity and specificity ranging from 64 to 100%, 63 to 100%, and 63 to 100%, respectively, in classifying acoustic signal as associated with pneumothorax or hemothorax at fluid injection levels of 400 ml or more, and regardless of background noise.

CONCLUSIONS

We present a novel, objective device for rapid diagnosis of potentially lethal thoracic injuries. With further optimization, such a device could provide real-time detection and monitoring of pneumothorax and hemothorax in battlefield conditions.

Current Trends in the Use of Ultrasound Over Chest X-Ray to Identify Pneumothoraces in ICU, Trauma, and ARDS Patients

Pneumothoraces are a common and potentially fatal complication for critically ill patients in the trauma and intensive care units. Since its use for pneumothorax detection was first reported in 1987, ultrasound has been increasingly used for the detection of thoracic injuries. As ultrasound imaging has improved and operators have potentially become more proficient, it is important to analyze more recent trends in the sensitivities and specificities of ultrasound for the detection of pneumothorax. This literature review and meta-analysis identifies 17 studies that directly compare the sensitivity and specificity of ultrasound and anterior-posterior chest x-ray in the identification of pneumothorax among 2955 patients who developed 793 pneumothoraces as detected by gold standard CT scanning. For the 17 articles analyzed, the pooled sensitivity of trans-thoracic ultrasound was 75.07% (64.92%-85.22%), and the pooled specificity was 98.36% (97.45%-99.26%). The pooled sensitivity of CXR was 45.65% (36.04%-55.26%), and pooled specificity was 99.62% (99.00%-100%). While this review demonstrates an improved sensitivity in the detection of pneumothorax with ultrasound over AP chest x-rays, it did not find a significant trend or improvement in the sensitivity or specificity of ultrasound for detecting pneumothorax over time.