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

Ajay Sheshadri; Alfonso Rodriguez; Ryan Chen; James Kozlowski; Dana Burgdorf; Tammy Koch; Jaime Tarsi; Rebecca Schutz; Brad Wilson; Kenneth Schechtman; Joseph K Leader; Eric A Hoffman; Mario Castro; Sean B Fain; David S Gierada

doi:10.1097/RCT.0000000000000238

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

Journal article

Peer reviewed

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

Ajay Sheshadri, Alfonso Rodriguez, Ryan Chen, James Kozlowski, Dana Burgdorf, Tammy Koch, Jaime Tarsi, Rebecca Schutz, Brad Wilson, Kenneth Schechtman, …

Journal of computer assisted tomography, Vol.39(4), pp.584-590

07/2015

DOI: 10.1097/RCT.0000000000000238

PMCID: PMC4504751

PMID: 25938213

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Abstract

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. 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. 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%. 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.

Multidetector Computed Tomography

Reproducibility of Results

Asthma - physiopathology

Humans

Middle Aged

Male

Lung - diagnostic imaging

Lung - physiopathology

Asthma - diagnostic imaging

Image Processing, Computer-Assisted - methods

Young Adult

Body Weights and Measures - methods

Analysis of Variance

Sensitivity and Specificity

Adult

Female

Phantoms, Imaging

Details

Title: Subtitle: Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma
Creators: Ajay Sheshadri - From the Division of Pulmonary and Critical Care Medicine, Department of Medicine, Washington University School of Medicine, St Louis, MI; †Department of Medical Physics, University of Wisconsin-Madison, Madison, WI; ‡Department of Surgery, University of Louisville School of Medicine, Louisville, KY; §Division of Biostatistics, Washington University School of Medicine, St Louis, MI; ∥Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA; ¶Department of Radiology, University of Iowa College of Medicine, Iowa City, IA; and #Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MI
Alfonso Rodriguez
Ryan Chen
James Kozlowski
Dana Burgdorf
Tammy Koch
Jaime Tarsi
Rebecca Schutz
Brad Wilson
Kenneth Schechtman
Joseph K Leader
Eric A Hoffman
Mario Castro
Sean B Fain
David S Gierada
Resource Type: Journal article
Publication Details: Journal of computer assisted tomography, Vol.39(4), pp.584-590
DOI: 10.1097/RCT.0000000000000238
PMID: 25938213
PMCID: PMC4504751
NLM abbreviation: J Comput Assist Tomogr
ISSN: 0363-8715
eISSN: 1532-3145
Publisher: United States
Grant note: UL1TR000448 / NCATS NIH HHS P30 ES005605 / NIEHS NIH HHS U10 HL109257 / NHLBI NIH HHS U19 AI070489 / NIAID NIH HHS T32HL007317-34 / NHLBI NIH HHS U19 A1070489-08 / PHS HHS U10HL109257-01 / NHLBI NIH HHS T32 HL007317 / NHLBI NIH HHS UL1 TR000448 / NCATS NIH HHS P30 DK054759 / NIDDK NIH HHS
Language: English
Date published: 07/2015
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Health, Sport, and Human Physiology ; Internal Medicine
Record Identifier: 9984051700902771

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