Probing airway conditions governing ventilation defects in asthma via hyperpolarized MRI image functional modeling

Abstract

Image functional modeling (IFM) has been introduced as a method to simultaneously synthesize imaging and mechanical data with computational models to determine the degree and location of airway constriction in asthma. Using lung imaging provided by hyperpolarized (3)He MRI, we advanced our IFM method to require matching not only to ventilation defect location but to specific ventilation throughout the lung. Imaging and mechanical data were acquired for four healthy and four asthmatic subjects pre- and postbronchial challenge. After provocation, we first identified maximum-size airways leading exclusively to ventilation defects and highly constricted them. Constriction patterns were then found for the remaining airways to match mechanical data. Ventilation images were predicted for each pattern, and visual and statistical comparisons were done with measured data. Results showed that matching of ventilation defects requires severe constriction of small airways. The mean constriction of such airways leading to the ventilation defects needed to be 70-80% rather than fully closed. Also, central airway constriction alone could not account for dysfunction seen in asthma, so small airways must be involved.