According to recent reports from across the world, the need to continuously evaluate lung edema in critically ill COVID-19 patients is essential. Chest x-ray has reduced sensitivity early in the disease; the contagiousness of the virus and the risk of transporting unstable patients with hypoxemia make chest CT a limited option for the patient with suspected or established COVID-19. Lung ultrasound (LUS) is non-ionizing and safe, and has recently emerged as a useful triage and monitoring tool for lung edema quantification in COVID-19 patients. In LUS, imaging artifacts termed A-lines (periodic horizontal lines parallel to the lung surface indicating a normal aeration pattern) and B-lines (comet-like hyperechoic regions indicating an alveolar or interstitial abnormality) are evaluated. B-lines stem from acoustic reverberations within regions of alveolar edema, and their number and thickness are known to be correlated with edema severity. However, visualization and quantification of B-lines requires substantial training, and even then, are highly operator and machine dependent. This is in part due to a still incomplete understanding of the exact physical mechanism of B-line formation. In this emergency competitive revision to the current award on ultrasound cavitation-aided drug delivery to solid tumors we propose to build on our expertise in dissecting the origins of US imaging artifacts and ultrasound instrumentation capabilities to 1) identify the origins of B-line artifact in LUS and specific associated RF signal features, and 2) based on the attained understanding, develop a single-element, wearable, automated, non-imaging lung ultrasound sensor (LUSS) for continuous monitoring of lung pathology while minimizing provider time, risk of virus exposure, and radiation. Individual adhesive LUSS elements will be attached to patients in specific anatomic locations similarly to ECG leads, and ultrasound signals will be collected and processed with automated algorithms to provide lung edema score that can be used in clinical decision making. We have designed a proof of principle study scaled to the shortest timeline possible to get the device into the clinic quickly, with the following specific aims. In SA1 we will perform standard LUS exams in non-COVID patients with cardiogenic pulmonary edema while collecting raw RF signal data to understand the manifestation of B-lines in raw RF signals and develop automated signal processing algorithm. In SA2 we will design and fabricate single- element LUSS prototype and validate the automated signal processing algorithm against LUS imaging in lung- mimicking sponge-based phantom. By the end of the 9-month project the prototype device will be ready for use in not only COVID19 patients, but other ED patients for whom continuous evaluation of lung condition is essential (bacterial pneumonia, cardiogenic edema, dialysis). Our commercialization approach here is to broadly license this simple technology so that large ultrasound manufacturers with broad sales and distribution capabilities can get the technology to the users.
We propose to develop a single-element, wearable, automated, non-imaging lung ultrasound sensor (LUSS) for continuous monitoring of lung edema in COVID-19 patients. This technology will also be applicable for continuous evaluation of lung edema in a number of conditions including bacterial pneumonia, cardiogenic edema and dialysis. The proposed study will benefit public health by providing actionable information on lung condition while minimizing provider time and risk of virus exposure.
|Khokhlova, Tatiana; Rosnitskiy, Pavel; Hunter, Christopher et al. (2018) Dependence of inertial cavitation induced by high intensity focused ultrasound on transducer F-number and nonlinear waveform distortion. J Acoust Soc Am 144:1160|