PURPOSE: Dynamic CT (dCT) allows visualization and quantification of ventilated lung and atelectases with high temporal resolution during continuous ventilation. This study compares a quantitative image analysis in a subcarinal single slice dCT series versus a whole lung spiral-CT, in order to analyze, whether the distribution of atelectasis of a single dCT series is representative for the whole lung. MATERIALS AND METHODS: dCT in sliding windows technique (slice thickness 1 mm, temporal increment 100 ms) was performed in 8 healthy pigs 3 cm caudal to the carina during continuous mechanical ventilation. Subsequently, a spiral-CT of the whole lung (slice thickness 2 mm; pitch 1.5; increment 2 mm) was acquired during inspiratory breath hold (airway pressure 20 mbar). Lung segmentation and planimetry of predefined density ranges were achieved using a dedicated software tool in both data-sets. Thus, the fractions of the following functional lung compartments were averaged over time: hyperinflated lung (- 1024 to - 910 HE), normal ventilated lung -900 to -300 HE) and atelectasis (-300 to +200 HE). RESULTS: Quantitative analysis of dCT-series during continuous respiration correlated with the density analysis in spiral-CT as follows: hyperinflated lung r = 0.56; normal ventilated lung r = 0.83 and atelectases r = 0.84. Analysis of spiral-CT showed the following distribution of functional lung compartments: hyperinflated lung 3.1% normal ventilated lung 77.9% and atelectasis 19.0%. In dCT, hyperinflated lung represented 6.4%, normal ventilated lung 65.2% and atelectasis 28.4% of total the lung area. CONCLUSION: The results of our study demonstrate that dCT allows monitoring of atelectasis formation in response to different ventilatory strategies. However, a deviation between dCT and spiral-CT has to be taken into account. In subcarinal dCT series, hyperinflated lung areas and atelectases were overestimated due to a craniocaudal gradient of atelectases, whereas normal ventilated lung was underestimated.
PURPOSE: Dynamic CT (dCT) allows visualization and quantification of ventilated lung and atelectases with high temporal resolution during continuous ventilation. This study compares a quantitative image analysis in a subcarinal single slice dCT series versus a whole lung spiral-CT, in order to analyze, whether the distribution of atelectasis of a single dCT series is representative for the whole lung. MATERIALS AND METHODS:dCT in sliding windows technique (slice thickness 1 mm, temporal increment 100 ms) was performed in 8 healthy pigs 3 cm caudal to the carina during continuous mechanical ventilation. Subsequently, a spiral-CT of the whole lung (slice thickness 2 mm; pitch 1.5; increment 2 mm) was acquired during inspiratory breath hold (airway pressure 20 mbar). Lung segmentation and planimetry of predefined density ranges were achieved using a dedicated software tool in both data-sets. Thus, the fractions of the following functional lung compartments were averaged over time: hyperinflated lung (- 1024 to - 910 HE), normal ventilated lung -900 to -300 HE) and atelectasis (-300 to +200 HE). RESULTS: Quantitative analysis of dCT-series during continuous respiration correlated with the density analysis in spiral-CT as follows: hyperinflated lung r = 0.56; normal ventilated lung r = 0.83 and atelectases r = 0.84. Analysis of spiral-CT showed the following distribution of functional lung compartments: hyperinflated lung 3.1% normal ventilated lung 77.9% and atelectasis 19.0%. In dCT, hyperinflated lung represented 6.4%, normal ventilated lung 65.2% and atelectasis 28.4% of total the lung area. CONCLUSION: The results of our study demonstrate that dCT allows monitoring of atelectasis formation in response to different ventilatory strategies. However, a deviation between dCT and spiral-CT has to be taken into account. In subcarinal dCT series, hyperinflated lung areas and atelectases were overestimated due to a craniocaudal gradient of atelectases, whereas normal ventilated lung was underestimated.
Authors: Dietrich Henzler; Andreas H Mahnken; Joachim E Wildberger; Rolf Rossaint; Rolf W Günther; Ralf Kuhlen Journal: Eur Radiol Date: 2005-10-12 Impact factor: 5.315
Authors: Emma Helm; Omid Talakoub; Francesco Grasso; Doreen Engelberts; Javad Alirezaie; Brian P Kavanagh; Paul Babyn Journal: Eur Radiol Date: 2008-07-24 Impact factor: 5.315
Authors: John N Cronin; Douglas C Crockett; Andrew D Farmery; Göran Hedenstierna; Anders Larsson; Luigi Camporota; Federico Formenti Journal: Crit Care Med Date: 2020-03 Impact factor: 7.598
Authors: John N Cronin; João Batista Borges; Douglas C Crockett; Andrew D Farmery; Göran Hedenstierna; Anders Larsson; Minh C Tran; Luigi Camporota; Federico Formenti Journal: Intensive Care Med Exp Date: 2019-11-01