Quantitative features in the computed tomography of healthy lungs.

Fromson, B; Denison, D M

doi:10.1136/thx.43.2.120

Cited by 23 publications

(9 citation statements)

References 9 publications

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“…Even better results were obtained when correlating the relative changes between inspiration and expiration of both MLD and CSA L . These findings are in good agreement with reports in the literature based on normal subjects [25,39]. This indicates that the air content of the lung and the air/tissue ratio which are major contributors to lung attenuation (MLD) also determine CSA L .…”

Section: Discussionsupporting

confidence: 93%

Evaluation of changes in central airway dimensions, lung area and mean lung density at paired inspiratory/expiratory high-resolution computed tomography

Ederle¹,

Heußel²,

Hast³

et al. 2003

Eur Radiol

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The aim of this study was to improve the understanding of interdependencies of dynamic changes in central airway dimensions, lung area and lung density on HRCT. The HRCT scans of 156 patients obtained at full inspiratory and expiratory position were evaluated retrospectively. Patients were divided into four groups according to lung function tests: normal subjects ( n=47); obstructive ( n=74); restrictive ( n=19); or mixed ventilatory impairment ( n=16). Mean lung density (MLD) was correlated with cross-sectional area of the lung (CSA(L)), cross-sectional area of the trachea (CSA(T)) and diameter of main-stem bronchi (D(B)). The CSA(L) was correlated with CSA(T) and D(B). MLD correlated with CSA(L) in normal subjects ( r=-0.66, p<0.0001) and patients with obstructive ( r=-0.62, p<0.0001), restrictive ( r=-0.83, p<0.0001) and mixed ventilatory impairment ( r=-0.86, p<0.0001). The MLD correlated with CSA(T) in the control group ( r=-0.50, p<0.0001) and in patients with obstructive lung impairment ( r-0.27, p<0.05). In patients with normal lung function a correlation between MLD and D(B) was found ( r=-0.52, p<0.0001). CSA(L) and CSA(T) correlated in the control group ( r=0.67, p<0.0001) and in patients with obstructive lung disease ( r=0.51, p<0.0001). The CSA(L) and D(B) correlated in the control group ( r=0.42, p<0.0001) and in patients with obstructive lung disease ( r=0.24, p<0.05). Correlations for patients with restrictive and mixed lung disease were constantly lower. Dependencies between central and peripheral airway dimensions and lung parenchyma are demonstrated by HRCT. Best correlations are observed in normal subjects and patients with obstructive lung disease. Based on these findings we postulate that the dependencies are the result of air-flow and pressure patterns.

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Section: Discussionsupporting

confidence: 93%

Evaluation of changes in central airway dimensions, lung area and mean lung density at paired inspiratory/expiratory high-resolution computed tomography

Ederle¹,

Heußel²,

Hast³

et al. 2003

Eur Radiol

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“…This usually includes the identification of a "region of interest" that incorporates the lung. This can also be done automatically by means of edge tracking or contiguous pixel computing routines that minimise intervention by the operator.2 22 Once the boundaries are defined it is an easier matter to compute the mass and volume of each slice of the scan. The tissue mass and whole lung density is then obtained by scanning the whole lung in contiguous slices and summing the values for each slice.…”

Section: Visual Methodsmentioning

confidence: 99%

Detection and quantification of pulmonary emphysema by computed tomography: a window of opportunity.

Morgan¹

1992

Thorax

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“…However, the most important issue is that the density of the simulated lung tissue in the polystyrene and water phantoms does not match that of either healthy or diseased lung tissue. Depending on inflation, lung tissue is around 0.1 g/cm 3 (−800 HU) when healthy and even lower (−950 HU) when diseased . Past quantitative SPECT measurements have shown that the bias in air‐filled volumes is higher than water‐filled volumes so it is important to get as close a match as possible (unpublished results).…”

Section: Introductionmentioning

confidence: 96%

“…Depending on inflation, lung tissue is around 0.1 g/cm 3 (À800 HU) when healthy and even lower (À950 HU) when diseased. 1,2 Past quantitative SPECT measurements have shown that the bias in air-filled volumes is higher than water-filled volumes so it is important to get as close a match as possible (unpublished results).…”

Section: Introductionmentioning

confidence: 99%

Development and testing of SPECT/CT lung phantoms made from expanding polyurethane foam

et al. 2019

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Purpose Currently, single‐photon emission computed tomography (SPECT)/computed tomography (CT) lung phantoms are commonly constructed using polystyrene beads and interstitial radioactive water. However, this approach often results in a phantom with a density (typically −640 HU) that is considerably higher than that of healthy lung (−750 to −850 HU) or diseased lung (−900 to −950 HU). Furthermore, the polystyrene and water phantoms are often quite heterogeneous in both density and activity concentration, especially when reused. This work is devoted to examining methods for creating a more realistic lung phantom for quantitative SPECT/CT using 99mTc‐laced expanding polyurethane foam (EPF). Methods Numerous aspects of EPF utilization were studied, including stoichiometric mixing to control final foam density and the effect of water during growth. We also tested several ways of molding the foam lung phantoms. The most successful method utilized a three‐part silicone mold that allowed for creation of a two‐lobe phantom, with a different density and activity concentration in each lobe. Results The final phantom design allows for a more anatomically accurate geometry as well as customizable density and activity concentration in the different lobes of the lung. We demonstrated final lung phantom densities between −760 and −690 HU in the “healthy” phantom and −930 to −890 HU in the “unhealthy” phantom tissue. On average, we achieved 15% activity concentration nonuniformity and 12% density nonuniformity within a given lobe. Conclusions Final EPF lung phantoms closely matched the densities of both health and diseased lung tissue and had sufficient uniformities in both density and activity concentration for most nuclear medicine applications. Management of component moisture content is critical for phantom reproducibility.

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Quantitative features in the computed tomography of healthy lungs.

Cited by 23 publications

References 9 publications

Evaluation of changes in central airway dimensions, lung area and mean lung density at paired inspiratory/expiratory high-resolution computed tomography

Evaluation of changes in central airway dimensions, lung area and mean lung density at paired inspiratory/expiratory high-resolution computed tomography

Detection and quantification of pulmonary emphysema by computed tomography: a window of opportunity.

Development and testing of SPECT/CT lung phantoms made from expanding polyurethane foam

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