Comparison of the lung ventilation assessed by a full-scale airway network flow model and xenon-enhanced dual-energy CT of patients with COPD
Bildiriler > Özet Bildiri
Yazarlar: Minsuok Kim, Ozkan Doganny, Hae Jeon Hwang, Joon Beom Seo, Fergus Gleeson
Monitoring airway disease, , , Uluslararası, Özet Bildiri, ss 2197-2197
DOI: 10.1183/13993003.congress-2020.2197
Özet
Introduction: The medical image-based computational model technique, full-scale airway network (FAN) flow model, may be able to identify and quantify disease in patients with COPD, and replace techniques such as ventilation scanning. Objectives: We compared ventilation distribution in patients with COPD, scanned using xenon-enhanced dual-energy CT (Xe-DECT) with the computational modelling results obtained using the FAN model. Methods: A total of nineteen patients with COPD underwent Xe-DECT scans at full-inspiration, and their ventilation patterns were quantified. The FAN flow model used anatomical data extracted from CT images and the pulmonary function test results. The percentage lobar ventilation ratios calculated in the FAN models were compared to those estimated from the Xe-DECT imaging. Results: The distribution of pulmonary ventilation shown on the middle cross-sectional transverse and coronal planes of the Xe-DECT data were similar to the FAN modelling results (Fig 1). Spearman correlation of the percentage ventilation ratio between the Xe-DECT images and FAN models was ρ = 0.78, p < 0.001. Figure 1. Ventilations on a mid-transverse and a mid-coronal plane. Conclusions: Using the data derived for an unenhanced breath-hold CT and computational modelling, the FAN model, may provide pulmonary functional ventilation assessments in agreement with Xe-DECT scanning.