Dataset Information

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

ABSTRACT:

Objective

We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification.

Methods

We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repeated-measures analysis of variance.

Results

Phantom measurements were more accurate when FOV decreased from 30 to 15 cm (P < 0.05). Decreasing FOV further to 10 cm did not significantly improve accuracy. Human airway measurements similarly decreased by decreasing FOV (P < 0.001). Percent changes in all measurements when reducing FOV from 30 to 15 cm were less than 3%.

Conclusions

Airway measurements at 30-cm FOV are near the limits of CT resolution using a medium-smooth kernel. Reducing reconstructed FOV would minimally increase sensitivity to detect differences in airway dimensions.

SUBMITTER: Sheshadri A

PROVIDER: S-EPMC4504751 | biostudies-literature | 2015 Jul-Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

Sheshadri Ajay A Rodriguez Alfonso A Chen Ryan R Kozlowski James J Burgdorf Dana D Koch Tammy T Tarsi Jaime J Schutz Rebecca R Wilson Brad B Schechtman Kenneth K Leader Joseph K JK Hoffman Eric A EA Castro Mario M Fain Sean B SB Gierada David S DS

Journal of computer assisted tomography 20150701 4

<h4>Objective</h4>We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification.<h4>Methods</h4>We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repe ...[more]

PMID: 25938213

Similar Datasets

Project description:ObjectivesQuantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition.MethodsFor this cross-sectional retrospective study, 234 lung-healthy patients who underwent spectral CT in four different contrast phases (non-enhanced, pulmonary arterial, systemic arterial, and venous phase) were recruited. Virtual monoenergetic images were reconstructed from 40-160 keV, on which attenuations of segmented lung parenchyma and airway walls combined for 5th-10th subsegmental generations were assessed in Hounsfield Units (HU) by an in-house software. The spectral attenuation curve slope between 40 and 100 keV (λHU) was calculated.ResultsMean lung density was higher at 40 keV compared to that at 100 keV in all groups (p < 0.001). λHU of lung attenuation was significantly higher in the systemic (1.7 HU/keV) and pulmonary arterial phase (1.3 HU/keV) compared to that in the venous phase (0.5 HU/keV) and non-enhanced (0.2 HU/keV) spectral CT (p < 0.001). Wall thickness and wall attenuation were higher at 40 keV compared to those at 100 keV for the pulmonary and systemic arterial phase (p ≤ 0.001). λHU for wall attenuation was significantly higher in the pulmonary arterial (1.8 HU/keV) and systemic arterial (2.0 HU/keV) compared to that in the venous (0.7 HU/keV) and non-enhanced (0.3 HU/keV) phase (p ≤ 0.002).ConclusionsSpectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition, and may separate arterial and venous enhancement. Further studies are warranted to analyze spectral CT for inflammatory airway diseases.Key points• Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition. • Spectral CT may separate arterial and venous enhancement of lung parenchyma and airway wall. • The contrast enhancement can be quantified by calculating the spectral attenuation curve slope from virtual monoenergetic images.

Dataset Information

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

Objective

Methods

Results

Conclusions

Publications

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets