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

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish
Pages (from-to)584-590
Number of pages7
JournalJournal of computer assisted tomography
Volume39
Issue number4
DOIs
StatePublished - Jul 29 2015

Keywords

  • Asthma
  • airway remodeling
  • quantitative CT imaging
  • reconstruction field of view

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