Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study

Introduction Dynamic 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-...

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Main Authors: Matthew Shaw, Thomas Simon FitzMaurice, Paul Stephen McNamara, Dilip Nazareth, Caroline McCann, Martin Walshaw, Scott Hawkes
Format: Article
Language:English
Published: BMJ Publishing Group 2023-12-01
Series:BMJ Open Respiratory Research
Online Access:https://bmjopenrespres.bmj.com/content/10/1/e001309.full
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author Matthew Shaw
Thomas Simon FitzMaurice
Paul Stephen McNamara
Dilip Nazareth
Caroline McCann
Martin Walshaw
Scott Hawkes
author_facet Matthew Shaw
Thomas Simon FitzMaurice
Paul Stephen McNamara
Dilip Nazareth
Caroline McCann
Martin Walshaw
Scott Hawkes
author_sort Matthew Shaw
collection DOAJ
description Introduction Dynamic 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).Methods Lung 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.Results Total 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.Conclusion DCR 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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spelling doaj.art-3d403e9e70e049b59a5771dc14e3ae052024-01-01T02:15:08ZengBMJ Publishing GroupBMJ Open Respiratory Research2052-44392023-12-0110110.1136/bmjresp-2022-001309Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot studyMatthew Shaw0Thomas Simon FitzMaurice1Paul Stephen McNamara2Dilip Nazareth3Caroline McCann4Martin Walshaw5Scott Hawkes6Medical Research Council, the GambiaDepartment of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UKAlder Hey Children`s Hospital, Liverpool, UKAdult CF Unit, Liverpool Heart and Chest Hospital NHS Trust, Liverpool, UKDepartment of Radiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UKDepartment of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UKDepartment of Pulmonary Physiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UKIntroduction Dynamic 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).Methods Lung 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.Results Total 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.Conclusion DCR 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.https://bmjopenrespres.bmj.com/content/10/1/e001309.full
spellingShingle Matthew Shaw
Thomas Simon FitzMaurice
Paul Stephen McNamara
Dilip Nazareth
Caroline McCann
Martin Walshaw
Scott Hawkes
Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
BMJ Open Respiratory Research
title Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
title_full Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
title_fullStr Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
title_full_unstemmed Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
title_short Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study
title_sort feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis a pilot study
url https://bmjopenrespres.bmj.com/content/10/1/e001309.full
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