Abstract

Mechanical ventilation in the intensive care unit (ICU) is a life-saving technique for patients with acute respiratory failure, but is also associated with a high incidence of complications in the injured lung. Currently, there is no widely used monitoring technique to guide the ventilator setting to facilitate a precision medicine approach or to provide a real-time alert for developing adverse pulmonary conditions. Conventional ultrasound has been used as a thoracic bedside technology, but the lack of signal penetration into lung tissue results in images that often contain more information in their artifacts than in the images themselves. Perhaps the greatest obstacle to using traditional ultrasound in the ICU is the need for highly skilled technicians to perform the data collection. In contrast, low-frequency ultrasound (50-500 kHz) has been shown to penetrate the lung, and can detect air trapping in patients with chronic obstructive pulmonary disease (COPD). Here, we present a method of collecting low-frequency ultrasound computed tomographic (USCT) data in vivo on a mechanically ventilated porcine model and computing tomographic reconstructions of airflow during tidal breathing and induced lung injuries. We evaluate the ability of the novel low-frequency USCT system to image regional changes in sound speed in the thorax due to changes in airflow during tidal breathing and induced lung injuries. This represents the first study of low-frequency tomographic ultrasound imaging in vivo and the first to produce tomographic images of ventilatory changes invivo. USCT and computed tomography (CT) scan data were collected alternately on a mechanically ventilated Landrace pig weighing approximately 75 kg during tidal breathing, induced pneumothorax, atelectasis, and pleural effusion. The pneumothorax was induced by injecting air through a 5 mm thick intrathoracic tube inserted in the 8th posterior intercostal space. After removing the air, atelectasis was induced by ventilating the animal with a high concentration of oxygen and low tidal volumes. The pleural effusion was induced by injecting a saline solution through the tube. The USCT data were collected at 125 kHz using the USCT low-frequency ultrasound tomography (LUFT) system on a transducer belt placed around the animal's thorax. Tomographic reconstructions were computed from the USCT data using a regularized refraction-corrected Gauss-Newton-based time-of-flight reconstructionalgorithm. Cyclic changes in computed lung area during tidal breathing were demonstrated to agree with the respiratory rate on the mechanical ventilator. Reconstructed images computed at time steps during the procedure demonstrate regional changes consistent with what would be expected during the induced lung injury. No ground truth was available for images during the procedures since CT scans could only be taken before and after each established lunginjury. In this work, we have demonstrated in the first in vivo study using a mechanically ventilated porcine animal model that low-frequency ultrasound tomography has the ability to image regional changes in sound speed in the thorax corresponding to changes in airflow during tidal breathing and induced lung injury. The results show promise for using low-frequency USCT as a bedside imaging technique in the future for patients with acute respiratory distresssyndrome.

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