Predicting tracheal work of breathing in neonates based on radiological and pulmonary measurements

Tracheomalacia is an airway condition in which the trachea excessively collapses during breathing. Neonates diagnosed with tra-cheomalacia require more energy to breathe, and the effect of tracheomalacia can be quantified by assessing flow-resistive work of breathing (WOB) in the trachea using computational fluid dynamics (CFD) modeling of the airway. However, CFD simula-tions are computationally expensive; the ability to instead predict WOB based on more straightforward measures would provide a clinically useful estimate of tracheal disease severity. The objective of this study is to quantify the WOB in the trachea using CFD and identify simple airway and/or clinical parameters that directly relate to WOB. This study included 30 neonatal intensive care unit subjects (15 with tracheomalacia and 15 without tracheomalacia). All subjects were imaged using ultrashort echo time (UTE) MRI. CFD simulations were performed using patient-specific data obtained from MRI (airway anatomy, dynamic motion, and airflow rates) to calculate the WOB in the trachea. Several airway and clinical measurements were obtained and compared with the tracheal resistive WOB. The maximum percent change in the tracheal cross-sectional area (p = 0.560, P = 0.001), average glottis cross-sectional area (p = -0.488, P = 0.006), minute ventilation (p = 0.613, P < 0.001), and lung tidal volume (p = 0.599, P < 0.001) had significant correlations with WOB. A multivariable regression model with three independent variables (minute ventilation, average glottis cross-sectional area, and minimum of the eccentricity index of the trachea) can be used to estimate WOB more accurately (R2= 0.726). This statistical model may allow clinicians to estimate tracheal resistive WOB based on air-way images and clinical data.NEW & NOTEWORTHY The work of breathing due to resistance in the trachea is an important metric for quantifying the effect of tracheal abnormalities such as tracheomalacia, but currently requires complex dynamic imaging and computational fluid dy-namics simulation to calculate it. This study produces a method to predict the tracheal work of breathing based on readily avail-able imaging and clinical metrics.