Therapeutic response to bronchial thermoplasty: toward feasibility of patient selection based on modeling predictions

Bronchial thermoplasty (BT) is a treatment for moderate-to-severe asthma in which the airway smooth muscle layer is targeted directly using thermal ablation. Although it has been shown to be safe and effective in long-term follow-up, questions remain about its mechanism of action, patient selection, and optimization of protocol based on structural phenotype. Using a cohort of 20 subjects who underwent thermoplasty and assessment by computed tomography (CT), we demonstrate that response to BT can be feasibly predicted based on pretreatment airway dimensions that inform a subject-specific computational model. Analysis revealed the need for CT assessment at total lung capacity, rather than functional residual capacity, which was less sensitive to the effects of BT. Final model predictions compared favorably with observed outcomes in terms of airway caliber and asthma control, suggesting that this approach could form the basis of improved clinical practice.

NEW & NOTEWORTHY Bronchial thermoplasty is a treatment for asthma that targets the airway smooth muscle directly. We demonstrate the feasibility and constraints of predicting patient-specific response to thermoplasty using a computational model informed by pretreatment CT scans at different lung volumes. Predictions are compared with functional outcomes and posttreatment CT scans. This has the potential to form the basis for improved clinical practice.