Detection of Collateral Ventilation in Pre-Planning for Bronchoscopic Lung Volume Reduction Procedures Using Advanced CT Imaging

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Advanced emphysema is marked by progressive airflow obstruction and hyperinflation, significantly reducing patients’ quality of life. Bronchoscopic lung volume reduction (BLVR) with endobronchial one-way valves (EBVs) has been shown to improve lung function and relieve dyspnea. However, the effectiveness of EBVs depends on achieving lung collapse, which can be hindered by collateral ventilation (CV) resulting from incomplete lobar fissures. This study explores the potential of advanced imaging software to deliver more accurate assessments of CV. In this prospective study at Temple University Hospital, 30 participants (aged 40 and older) were recruited. All underwent a Chartis assessment to determine their CV status. Paired inspiratory-expiratory CT scans were used to generate advanced ventilation images (CT LVAS, 4DMedical) and density/emphysema-scored images (LDAf, IMBIO). Ventilation and emphysema distribution within the fissure region were measured and used as predictors of CV in a weighted factor model. The results were further validated using a k-folds cross-validation approach. The weighted model demonstrates that a combination of LDAf density scoring and assessment of ventilation in the fissure region predicted CV with accuracy of 0.97, AUC of 0.94, sensitivity of 0.9 and specificity of 1. Repeated stratified k-folds yielded a mean accuracy of 94%. This study demonstrates that the novel method for CV detection is highly accurate. By providing a more efficient and less invasive alternative, this method has the potential to improve diagnostic accuracy and patient outcomes.

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