This study set out to determine whether quantitative features of lung computed tomography scans could be identified that would lead to a tightly defined normal range for use in assessing patients. Fourteen normal subjects with apparently healthy lungs were studied. A technique was developed for rapid and automatic extraction of lung field data from the computed tomography scans. The Hounsfield unit histograms were constructed and, when normalised for predicted lung volumes, shown to be consistent in shape for all the subjects. A three dimensional presentation of the data in the form of a "net plot" was devised, and from this a logarithmic relationship between the area of each lung slice and its mean density was derived (r = 0.9, n = 545, p less than 0.0001). The residual density, calculated as the difference between measured density and density predicted from the relationship with area, was shown to be normally distributed with a mean of 0 and a standard deviation of 25 Hounsfield units (chi 2 test: p less than 0.05). A presentation combining this residual density with the net plot is described.
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