(1246) Novel Regional Ventilation Evaluation of Abnormalities of the Lung In Advanced Lung Disease (REVEAL Study)
The Journal of Heart and Lung Transplantation(2023)
Abstract
PurposeAdvanced lung diseases are a heterogeneous group of pathologically distinct processes that share similar symptoms and clinical features. Pulmonary function tests [PFTs] are a standard method for assessing advanced lung disease, yet it can be limited in this cohort due to insensitivity to marginal changes, inability to reveal spatial distribution of abnormalities, and spurious preservation of metrics in mixed disease states. This highlights the need among this group for additional diagnostic tests. We aim to assess whether X-ray Velocimetry [XV] (4DMedical Limited, Australia), a radiomics software-as-a-medical device for quantification and visualisation of regional lung function, could further characterise advanced lung disease.MethodsWe compared XV metrics for patients with advanced lung disease referred for lung transplant assessment with healthy subjects, and assessed correlations with PFT. XV utilised fluoroscopic lung images co-registered to each subject's CT chest to quantify specific ventilation, voxel-wise tidal ventilation according to 8mm3 regions (local tidal volume), ventilation heterogeneity index (interquartile range of local tidal volume divided by mean local tidal volume) and low ventilation areas [LVA] (proportion of lung volume with local tidal volume <50μL).ResultsIn 24 patients (mean age: 62 years; 38% females) with advanced lung disease (12 non-obstructive and 12 obstructive, based on spirometry) and 12 healthy subjects (mean age: 45 years, 33% females), XV metrics significantly differed between groups (see Figure 1a). Further, LVA strongly correlated (r=-0.796, R2=0.63, p<0.001) with predicted FEV1%, suggesting that it may serve as a surrogate marker for airflow limitations, which can additionally be spatially visualised for better assessment of disease (see Figure 1b).ConclusionAdvanced lung disease can be further characterised according to regional ventilation heterogeneity and defects, while strongly correlating to spirometry. Advanced lung diseases are a heterogeneous group of pathologically distinct processes that share similar symptoms and clinical features. Pulmonary function tests [PFTs] are a standard method for assessing advanced lung disease, yet it can be limited in this cohort due to insensitivity to marginal changes, inability to reveal spatial distribution of abnormalities, and spurious preservation of metrics in mixed disease states. This highlights the need among this group for additional diagnostic tests. We aim to assess whether X-ray Velocimetry [XV] (4DMedical Limited, Australia), a radiomics software-as-a-medical device for quantification and visualisation of regional lung function, could further characterise advanced lung disease. We compared XV metrics for patients with advanced lung disease referred for lung transplant assessment with healthy subjects, and assessed correlations with PFT. XV utilised fluoroscopic lung images co-registered to each subject's CT chest to quantify specific ventilation, voxel-wise tidal ventilation according to 8mm3 regions (local tidal volume), ventilation heterogeneity index (interquartile range of local tidal volume divided by mean local tidal volume) and low ventilation areas [LVA] (proportion of lung volume with local tidal volume <50μL). In 24 patients (mean age: 62 years; 38% females) with advanced lung disease (12 non-obstructive and 12 obstructive, based on spirometry) and 12 healthy subjects (mean age: 45 years, 33% females), XV metrics significantly differed between groups (see Figure 1a). Further, LVA strongly correlated (r=-0.796, R2=0.63, p<0.001) with predicted FEV1%, suggesting that it may serve as a surrogate marker for airflow limitations, which can additionally be spatially visualised for better assessment of disease (see Figure 1b). Advanced lung disease can be further characterised according to regional ventilation heterogeneity and defects, while strongly correlating to spirometry.
MoreTranslated text
Key words
advanced lung disease,novel regional ventilation evaluation
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined