Patient-specific targeted bronchial thermoplasty: predictions of improved outcomes with structure-guided treatment

Abstract

Bronchial thermoplasty is a recent treatment for asthma in which ablative thermal energy is delivered to specific large airways according to clinical guidelines. Therefore, current practice is effectively “blind,” as it is not informed by patient-specific data. The present study seeks to establish whether a patient-specific approach based on structural or functional patient data can improve outcomes and/or reduce the number of procedures required for clinical efficacy. We employed a combination of extensive human lung specimens and novel computational methods to predict bronchial thermoplasty outcomes guided by structural or functional data compared with current clinical practice. Response to bronchial thermoplasty was determined from changes in airway responses to strong bronchoconstrictor simulations and flow heterogeneity after one or three simulated thermoplasty procedures. Structure-guided treatment showed significant improvement over current unguided clinical practice, with a single session of structure-guided treatment producing improvements comparable with three sessions of unguided treatment. In comparison, function-guided treatment did not produce a significant improvement over current practice. Structure-guided targeting of bronchial thermoplasty is a promising avenue for improving therapy and reinforces the need for advanced imaging technologies. The functional imaging-guided approach is predicted to be less effective presently, and we make recommendations on how this approach could be improved. NEW & NOTEWORTHY Bronchial thermoplasty is a recent treatment for asthma in which thermal energy is delivered via bronchoscope to specific airways in an effort to directly target airway smooth muscle. Current practice involves the treatment of a standard set of airways, unguided by patient-specific data. We consider the potential for guided treatments, either by functional or structural data from the lung, and show that treatment guided by structural data has the potential to improve clinical practice.