405 - Electrical Impedance Tomography to Monitor Lung Inflation in Bronchopulmonary Dysplasia: A Feasibility Study

Publication Number: 1388.405

William Gravley, Children's National Hospital, Washington, DC, United States; Marykate Higley, Children's National Hospital, Washington, DC, United States; Maria Arroyo, Children's National Health System, Washington, DC, United States; Hallie Morris, Children's National Health System, Washington, DC, United States

Background: Bronchopulmonary dysplasia (BPD) is a leading complication of preterm birth. Despite care advances, extremely premature and low birth weight infants remain at high risk for death and disability due to the disease. Exploring technology that interprets diagnostic and predictive models of BPD can help providers to better understand prognosis, improve management, and improve survival and morbidity. Electrical impedance tomography (EIT) is a technology that allows for real-time assessment of regional lung volume and ventilation. EIT has been studied for several decades to assess clinical utility in neonates, but information about applications for BPD is lacking.

Objective: Our goal in this single center, prospective feasibility study is to perform an exploratory data analysis to determine if EIT can detect progressing lung function in BPD.

Design/Methods: Patients with a clinical diagnosis of BPD per NIH criteria were monitored for 4 to 6 24-hour sessions over 6 weeks. Electrical impedance measurements were obtained using a standard bioimpedance monitoring device (Sentec LuMon EIT). Recorded segments with the highest breath capture percentage were analyzed. End-expiratory lung impedance (EELI) - a reflection of functional residual capacity - was used as the primary measure of lung inflation. Mean EELI from each segment was used in analysis to avoid weighting segments with varying number of breaths or breath capture percentage. STATA SE 19.5 was used for statistical analysis.

Results: Nine patients were enrolled yielding 49 recording sessions (1,176 hours of data capture) with no adverse events. Mean gestational age (GA) at birth was 25.3 weeks; mean corrected GA (CGA) at enrollment was 39.9 weeks. Logistic regression analysis indicated a negative, though non-significant, association between CGA and mean EELI (coefficient -32.3, 95% CI [-69.2, 4.60], p=0.085). Ordinal logistic regression showed that mean EELI had no association with level of respiratory support (coefficient 0.001, 95% CI [-0.002, 0.001], p=0.275) when controlling for CGA.

Conclusion(s): This study demonstrated our ability to safely capture quality breath data and monitor lung function over time in patients with BPD. EELI decreased with increasing CGA, suggesting decreased air trapping over time. However, given the lack of significance, further data capture and analysis is required to confirm this trend. Analyzing EELI together with ventilatory changes or biometric data such as vital signs and lab values may also elucidate clinical evolution of BPD. In the future, EIT could be a useful technology to routinely follow BPD progression in real time.

Mean EELI vs. Ventilatory Support
Ventilatory support as a function of mean end-expiratory lung impedance (EELI). Ventilatory support is recorded as ordinal data: 5 = intubated, mechanical ventilation; 4 = non-invasive positive pressure ventilation; 3 = continuous positive airway pressure; 2 = high flow nasal cannula; 1 = low flow nasal cannula; 0 = no ventilatory support. In our small sample size, ordinal regression analysis showed no significant association between mean EELI and level of ventilatory support (coefficient 0.001, 95% CI [-0.002, 0.001], p=0.275).

CGA vs. Mean EELI
Mean end-expiratory lung impedance (EELI) as a function of corrected gestational age (CGA) in weeks. Regression analysis indicated a negative, though non-significant, association between CGA and mean EELI (coefficient -32.3, 95% CI [-69.2, 4.60], p=0.085).