Maximizing quantitative accuracy of lung airway lumen and wall measures obtained from X-ray CT imaging.
To objectively quantify airway geometry from three-dimensional computed tomographic (CT) images, an idealized (circular cross section) airway model is parameterized by airway luminal caliber, wall thickness, and tilt angle. Using a two-dimensional CT slice, an initial guess for the airway center, and the full-width-half-maximum principle, we form an estimate of inner and outer airway wall locations. We then fit ellipses to the inner and outer airway walls via a direct least squares fit and use the major and minor axes of the ellipses to estimate the tilt and in-plane rotation angles. Convolving the airway model, initialized with these estimates, with the three-dimensional scanner point-spread function forms the predicted image. The difference between predicted and actual images is minimized by refining the model parameter estimates via a multidimensional, unconstrained, nonlinear minimization routine. When optimization converges, airway model parameters estimate the airway inner and outer radii and tilt angle. Results using a Plexiglas phantom show that tilt angle is estimated to within +/-4 degrees and both inner and outer radii to within one-half pixel when a "standard" CT reconstruction kernel is used. By opening up the ability to measure airways that are not oriented perpendicular to the scanning plane, this method allows evaluation of a greater sampling of airways in a two-dimensional CT slice than previously possible. In addition, by combining the tilt-angle compensation with the deconvolution method, we provide significant improvement over the previous full-width-half-maximum method for assessing location of the luminal edge but not the outer edge of the airway wall.
Saba
Osama I
OI
Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.
Hoffman
Eric A
EA
Reinhardt
Joseph M
JM
D000465:Algorithms; D003196:Computer Graphics; D006801:Humans; D008168:Lung / Q000033:anatomy & histology / Q000000981:diagnostic imaging* / Q000502:physiology; D008953:Models, Anatomic; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D014057:Tomography, X-Ray Computed