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Thoracoabdominal asynchrony in a virtual preterm infant: computational modeling and analysis

Monday, July 17 at 6:00pm

SMB2023 SMB2023 Follow Monday during the "PS01" time block.
Room assignment: in The Ohio Union.
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Richard Foster

Virginia Commonwealth University
"Thoracoabdominal asynchrony in a virtual preterm infant: computational modeling and analysis"
Thoracoabdominal asynchrony (TAA), the asynchronous volume changes between the rib cage and abdomen during breathing, is associated with respiratory distress, progressive lung volume loss, and chronic lung disease in the newborn infant. Preterm infants are prone to TAA risk factors such as weak intercostal muscles, surfactant deficiency, and a flaccid chest wall. The causes of TAA in this fragile population are not fully understood and, to date, the assessment of TAA has not included a mechanistic modeling framework to explore the role these risk factors play in breathing dynamics and how TAA can be resolved. We present a dynamic compartmental model of pulmonary mechanics that simulates TAA in the preterm infant under various adverse clinical conditions, including high chest wall compliance, applied inspiratory resistive loads, bronchopulmonary dysplasia, anesthesia-induced intercostal muscle deactivation, weakened costal diaphragm, impaired lung compliance, and upper airway obstruction. Sensitivity analyses performed to screen and rank model parameter influence on model TAA and respiratory volume outputs show that risk factors are additive so that maximal TAA occurs in a virtual preterm infant with multiple adverse conditions, and addressing risk factors individually causes incremental changes in TAA. An abruptly obstructed upper airway caused immediate nearly paradoxical breathing and tidal volume reduction despite greater effort. In most simulations, increased TAA occurred together with decreased tidal volume. Simulated indices of TAA are consistent with published experimental studies and clinically-observed pathophysiology, motivating further investigation into the use of computational modeling for assessing and managing TAA.
Additional authors: Bradford Smith, Ph.D., University of Colorado Denver, Department of Bioengineering (1), School of Medicine, University of Colorado Anschutz Medical Campus, Department of Pediatric Pulmonary and Sleep Medicine (2); Laura Ellwein Fix, Ph.D., Virginia Commonwealth University, Department of Mathematics and Applied Mathematics

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Annual Meeting for the Society for Mathematical Biology, 2023.