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The effect of increasingly more sophisticated attenuation correction methods on image homogeneity has been studied in seven healthy subjects. The subjects underwent computed tomography (CT), single photon emission computed tomography (SPECT) and transmission computed tomography (TCT) of the thorax region in the supine position. Density maps were obtained from the CT and TCT studies. Attenuation corrections were performed using five different methods: (1) uniform correction using only the body contour, (2) TCT based corrections using the average lung density, (3) TCT based corrections using the pixel density, (4) CT based corrections using average lung density, and (5) CT based corrections using the pixel density. The isolated attenuation effects were assessed on quotient images generated by the division of images obtained using various attenuation correction methods divided by the non-uniform attenuation correction based on CT pixel density (reference method). The homogeneity was calculated as the coefficient of variation of the quotient images (CVatt), showing the isolated attenuation effects. Values of CVatt were on average 12.8% without attenuation correction, 10.7% with the uniform correction, 8.1% using TCT map using the average lung density value and 4.8% using CT and average lung density corrections. There are considerable inhomogeneities in lung SPECT slices due to the attenuation effect. After attenuation correction the remaining inhomogeneity is considerable and cannot be explained by statistical noise and camera non-uniformity alone.

Emphysema is characterized by destruction of lung tissue with development of small or large holes within the lung. These areas will have Hounsfield values (HU) approaching -1000. It is possible to detect and quantificate such areas using simple density mask technique. The edge enhancement reconstruction algorithm, gravity and motion of the heart and vessels during scanning causes artefacts, however. The purpose of our work was to construct an algorithm that detects such image artefacts and corrects them. The first step is to apply inverse filtering to the image removing much of the effect of the edge enhancement reconstruction algorithm. The next step implies computation of the antero-posterior density gradient caused by gravity and correction for that. Motion artefacts are in a third step corrected for by use of normalized averaging, thresholding and region growing. Twenty healthy volunteers were investigated, 10 with slight emphysema and 10 without. Using simple density mask technique it was not possible to separate persons with disease from those without. Our algorithm improved separation of the two groups considerably. Our algorithm needs further refinement, but may form a basis for further development of methods for computerized diagnosis and quantification of emphysema by HRCT.

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