Observational studyBMJ open respiratory research2023
Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study.
Observational study in BMJ open respiratory research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Estimation of pulmonary function from time-resolved dynamic chest radiography using machine learning in patients with respiratory disease.Journal of applied clinical medical physics · 2026Article
- Deep learning-based lung volume estimation with dynamic chest radiography.Journal of applied clinical medical physics · 2026Article
- Clinical utility of dynamic chest radiography as an auxiliary tool for atrial fibrillation detection in heart failure: a pilot study.BMC cardiovascular disorders · 2025Article
- Dynamic chest radiography: moving from basic research to clinical application.Journal of thoracic disease · 2023Article
- Future expectations for respiratory disease assessment in dynamic chest radiography.Journal of thoracic disease · 2023Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDynamic chest radiography (DCR) is a novel, low-dose, real-time digital imaging system where software identifies moving thoracic structures and can automatically calculate lung areas. In an observational, prospective, non-controlled, single-centre pilot study, we compared it with whole-body plethysmography (WBP) in the measurement of lung volume subdivisions in people with cystic fibrosis (pwCF).
methodsLung volume subdivisions were estimated by DCR using projected lung area (PLA) during deep inspiration, tidal breathing and full expiration, and compared with same-day WBP in 20 adult pwCF attending routine review. Linear regression models to predict lung volumes from PLA were developed.
resultsTotal lung area (PLA at maximum inspiration) correlated with total lung capacity (TLC) (r=0.78, p<0.001), functional residual lung area with functional residual capacity (FRC) (r=0.91, p<0.001), residual lung area with residual volume (RV) (r=0.82, p=0.001) and inspiratory lung area with inspiratory capacity (r=0.72, p=0.001). Despite the small sample size, accurate models were developed for predicting TLC, RV and FRC.
conclusionDCR is a promising new technology that can be used to estimate lung volume subdivisions. Plausible correlations between plethysmographic lung volumes and DCR lung areas were identified. Further studies are needed to build on this exploratory work in both pwCF and individuals without CF. TRIAL REGISTRATION NUMBER: ISRCTN64994816.
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