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Proceedings Paper

Evaluation of scoring accuracy for airway wall thickness
Author(s): Benjamin L. Odry; Atilla P. Kiraly; Carol L. Novak; David P. Naidich; Jane P. Ko; Myrna C. B. Godoy
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Paper Abstract

Bronchial wall thickening is commonly observed in airway diseases. One method often used to quantitatively evaluate wall thickening in CT images is to estimate the ratio of the bronchial wall to the accompanying artery, or BWA ratio, and then assign a severity score based on the ratio. Assessment by visual inspection is unfortunately limited to airways perpendicular or parallel to the scanning plane. With high-resolution images from multi-detector CT scanners, it becomes possible to assess airways in any orientation. We selected CT scans from 20 patients with mild to severe COPD. A computer system automatically segmented each bronchial tree and measured the bronchial wall thicknesses. Next, neighboring arteries were detected and measured to determine BWA ratios. A score characterizing the extent and severity of wall thickening within each lobe was computed according to recommendations by Sheehan et al [1]. Two experienced radiologists independently scored wall thickening using visual assessment. Spearman's rank correlation showed a non-significant negative correlation (r=-0.1) between the computer and the reader average (p=0.4), while the correlation between readers was significant at r=0.65 (p=0.001). We subsequently identified 24 lobes with high discrepancies between visual and automated scoring. The readers re-examined those lobes and measured wall thickness using electronic calipers on perpendicular cross sections, rather than visual assessment. Using this more objective standard of wall thickness, the reader estimates of wall thickening increased to reach a significant positive correlation with automated scoring of r=0.65 (p=0.001). These results indicate that subjectivity is an important problem with visual evaluation, and that visual inspection may frequently underestimate disease extent and severity. Given that a manual evaluation of all airways is infeasible in routine clinical practice, we argue that automated methods should be developed and utilized.

Paper Details

Date Published: 27 February 2009
PDF: 9 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72602X (27 February 2009); doi: 10.1117/12.811910
Show Author Affiliations
Benjamin L. Odry, Siemens Corporate Research (United States)
Atilla P. Kiraly, Siemens Corporate Research (United States)
Carol L. Novak, Siemens Corporate Research (United States)
David P. Naidich, New York Univ. Medical Ctr. (United States)
Jane P. Ko, New York Univ. Medical Ctr. (United States)
Myrna C. B. Godoy, New York Univ. Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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