Influence of Pixel Size on Quantification of Airway Wall Thickness in Computed Tomography

Objectives: The purpose of this study was to determine the point where a further decrease in voxel size does not result in better automatic quantification of the bronchial wall thickness by using 2 different assessment techniques. Materials and Methods: The results from the commonly used full-width-at-half-maximum (FWHM) principle and a new technique (integral-based method [IBM]) were compared for thin-section multi-detector computed tomography (MDCT) data sets from an airway phantom containing 10 different tubular airway phantoms and in a human subsegmental bronchus in vivo. Correlation with the actual wall thickness and comparison of the wall thicknesses assessed for different voxel sizes were performed, and the image resolutions were also compared subjectively. Results: The relative error ranged from 0% (biggest phantom) to 330% (smallest phantom, biggest field of view, smaller matrix, and FWHM). Using IBM, the maximum relative error was 10% in the same setting. For FWHM, the improvement was marginal for most settings with a pixel spacing less than 0.195 x 0.195 x 0.8 mm; however, it still decreases the relative error from 290% to 273.6% for a wall thickness of 0.3 mm and a pixel spacing of 0.076 x 0.076 x 0.8 mm. Conclusions: (1) Using a special technique such as IBM to account for computed tomography's blurring effect in assessing airway wall thickness had the greatest impact on correct quantification. (2),The visual impression and the automatic quantification using the FWHM technique improved marginally by decreasing the voxel size to less than 0.195 x 0.195 x 0.8 mm. (3) The FWHM technique as a model for visual quantification is not reliable for airway wall thicknesses less than 1.5 mm.