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The aim of this study was to evaluate a method for quantification of inhomogeneity in ventilation single-photon emission tomography (SPET). Nine emphysematous patients, nine life-long non-smokers and nine smokers were included in the study. The SPET investigation was performed after 50 MBq (99m)Tc-Technegas had been inhaled by each subject in the supine position. A single-head gamma camera, equipped with a general-purpose parallel-hole collimator using 64 projections (20 s each) over 360 degrees, was used. Data were acquired in 128x128 matrices. Attenuation correction was applied based upon computed tomography (CT) density maps. Lung regions of interest were delineated manually on CT images and then positioned on SPET images. Several attenuation-corrected transaxial SPET slices (thickness 1 cm, spacing 3.5 cm) were reconstructed. Each SPET slice was divided into several 2x2x1 cm(3) elements. Inhomogeneity was assessed by the coefficient of variation (CV) of the pixel counts within these elements (micro-level) and the CV of the total counts of the elements (macro-level). Micro-level CVs in non-smokers varied between 1% and 41%, whereas they were dispersed over a wide range (1%-600%) in emphysematous patients. In seven smokers, the frequency distribution of micro-level CVs was within the normal range, whereas in the other two smokers the values were between the normal range and the range in emphysematous patients. The pooled mean values of micro-level CVs and macro-level CVs in each subject clearly separated the patients from the others. Parametric images of micro-level CV indicated the localisation and severity of ventilation inhomogeneity. We conclude that the present method enables quantification and localisation of regional inhomogeneity in ventilation SPET images.

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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 (CV(att)), showing the isolated attenuation effects. Values of CV(att) 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.

Quantitative evaluation of renal function in 99mTc-DTPA isotope renography is hampered by high background activity. This study compares various background regions of interest (ROIs) to obtain the most accurate estimate of the extra-renal background, taking both total counts (integral value) and change by time (slope) into account. Gamma camera renography was performed in 21 patients with a single kidney. Time-activity histograms obtained from 8 different background ROIs were compared in the time interval corresponding to the uptake phase of the renogram with the histogram obtained from a ROI over the empty kidney area. A significant difference could be demonstrated between the slope values of the histograms of the right and left empty kidney ROIs, but not for the integral values. Backgrounds taken over the heart, liver, between the kidneys, and under the kidneys had significantly different characteristics than the one in the empty kidney area. Only background ROIs surrounding each kidney area gave integral and slope values with close resemblance to those recorded over the empty kidney area. The results emphasize the necessity for an individual background ROI for each kidney and the need to separate extra- and intra-renal background activities before subtraction.