Mechanical ventilation (MV) is the primary intervention used to assist neonatal and adult acute pulmonary failure patients, however, rapid and accurate assessment of patient function during ventilation remains an ongoing challenge. A primary cause of decreased lung efficiency in MV-assisted patients is ventilation/perfusion mismatch (V/Q mismatch): a mismatch between alveolar ventilation and pulmonary perfusion (blood supply). Intervention methods exist which can help to resolve V/Q mismatch, however effective application of these would benefit from a continuous monitoring method to guide successful therapy. In patients with pulmonary shunt, lack of ventilation at the alveoli, Positive End Expiratory Pressure (PEEP) is used with MV to maximize lung volume. If not monitored, lung damaging over-distention can occur. Surfactant replacement therapy can be used in neonates to resolve lung collapse (atelectasis) and patient maneuvering can be used to assist blood redistribution in patients with dead space - ventilation without perfusion. All of these methods would benefit from knowledge of what and how much therapy to administer, and to continuously monitor V/Q responses. No non-invasive continuous real-time clinical monitoring solution currently exists. We propose to develop a noninvasive, real-time, continuous Electrical Impedance Tomography (EIT) lung function monitoring system. EIT has been studied previously, however here we identify and address the technical limitations that have prevented clinical adoption. Upon successful completion, the clinician will have access to a device that will provide a 3-D regional ventilation/perfusion (V/Q) mismatch data, a 3-D regional indicator of atelectasis, and regional perfusion data.
Mechanical ventilation (MV) is a primary support mechanism for acute lung disease patients, both adult and neonatal. At present, there is no method for real-time noninvasive monitoring of lung recruitment and ventilation/perfusion mismatch (V/Q mismatch) at the bedside, making MV management a challenge. We propose to develop and validate a noninvasive, real-time lung function monitor that can guide therapy at the bedside, resulting in reduction of lung injury incidents and improved patient outcomes.
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