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The aim of this preliminary study was to evaluate the accuracy of left and right ventricular output computed from a semi-automatic processing of tomographic radionuclide ventriculography data (TRVG) in comparison with the conventional thermodilution method. Twenty patients with various heart diseases were prospectively included in the study. Thermodilution and TRVG acquisitions were carried out on the same day for all patients. Analysis of gated blood pool slices was performed using a watershed-based segmentation algorithm. Right and left ventricular output measured by TRVG correlated well with the measurements obtained with thermodilution (r = 0.94 and 0.91 with SEE = 0.38 and 0.46 l/min, respectively, P < 0.001). The limits of agreement for TRVG and thermodilution measurements were -0.78-1.20 l/min for the left ventricle and -0.34-1.16 l/min for the right ventricle. No significant difference was found between the results of TRVG and thermodilution with respect to left ventricular output (P = 0.09). A small but significant difference was found between right ventricular output measured by TRVG and both left ventricular output measured by TRVG (mean difference = 0.17 l/min, P = 0.04) and thermodilution-derived cardiac output (mean difference = 0.41 l/min, P = 0.0001). It is concluded that the watershed-based semi-automatic segmentation of TRVG slices provides non-invasive measurements of right and left ventricular output and stroke volumes at equilibrium, in routine clinical settings. Further studies are necessary to check whether the accuracy of these measurements is good enough to permit correct assessment of intracardiac shunts.

Tomographic multi-gated blood pool scintigraphy (TMUGA) is a widely available method which permits simultaneous assessment of right and left ventricular ejection fractions. However, the widespread clinical use of this technique is impeded by the lack of segmentation methods dedicated to an automatic analysis of ventricular activities. In this study we evaluated how a watershed algorithm succeeds in providing semi-automatic segmentation of ventricular activities in order to measure right and left ejection fractions by TMUGA. The left ejection fractions of 30 patients were evaluated both with TMUGA and with planar multi-gated blood pool scintigraphy (PMUGA). Likewise, the right ejection fractions of 25 patients were evaluated with first-pass scintigraphy (FP) and with TMUGA. The watershed algorithm was applied to the reconstructed slices in order to group together the voxels whose activity came from one specific cardiac cavity. First, the results of the watershed algorithm were compared with manual drawing around left and right ventricles. Left ejection fractions evaluated by TMUGA with the watershed procedure were not significantly different (p=0. 30) from manual outlines whereas a small but significant difference was found for right ejection fractions (p=0.004). Then right and left ejection fractions evaluated by TMUGA (with the semi-automatic segmentation procedure) were compared with the results obtained by FP or PMUGA. Left ventricular ejection fractions evaluated by TMUGA showed an excellent correlation with those evaluated by PMUGA (r=0. 93; SEE=5.93%; slope=0.99; intercept = 4.17%). The measurements of these ejection fractions were significantly higher with TMUGA than with PMUGA (P<0.01). The interoperator variability for the measurement of left ejection fractions by TMUGA was 4.6%. Right ventricular ejection fractions evaluated by TMUGA showed a good correlation with those evaluated by FP (r = 0.81; SEE = 6.68%; slope = 1.00; intercept = 0.85%) and were not significantly different (P = 0.42). The interoperator variability with TMUGA was 6.7% for the right ventricle. Thus, the watershed algorithm proposed is an efficient segmentation tool for the semi-automatic analysis of right and left ventricular ejection fractions by TMUGA. Further studies are necessary to check whether this procedure can be used to evaluate ventricular volumes and cardiac outflow.

The purpose of this study was to define an optimal strategy for the tomographic reconstruction procedure in routine brain single-photon emission tomography (SPET) studies, including the number of projections, filter function and matrix size. A set of projection data with different count densities was obtained from a technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) brain SPET acquisition from one volunteer. The projections were reconstructed with different filters and the quality of the reconstructed images was determined using both a subjective observer rating score and the Gilbert index. For each count density, the observers' choice corresponded to images with the lowest Gilbert index. The noise level in brain SPET sections was estimated and correlated with the fractal dimension. The results of this study indicate that although noise represents a fundamental component of brain SPET imaging, image quality also depends on the reconstructed spatial resolution. Image quality is satisfactorily described by fractal dimension. In addition the optimal filter function depends on the available count density. For high count levels, optimal reconstruction may be obtained by using a high-resolution matrix and a slightly smoother reconstruction filter. When count densities are low, best results are obtained by using a low-resolution matrix and a sharper filter. Finally, this study suggests that image quality is not influenced by the number of projections for equivalent count densities. These results were confirmed by 30 HMPAO brain SPET studies acquired in a routine clinical setting.

A new method for centering and reorienting automatically the left ventricle in thallium-201 myocardial single photon emission computed tomography (SPET) is proposed. The processing involves the following steps: (a) the transverse sections of the left ventricle are segmented, (b) the three-dimensional skeleton of the left ventricle is extracted using tools of mathematical morphology, (c) the skeleton is fitted to a quadratic surface by the least-squares method, (d) the left ventricle is reoriented and centered using the long axis and the coordinates of the centre of the quadratic surface. A series of 30 consecutive exercise and redistribution 201Tl SPET studies were centered and reoriented by two operators twice with this method, and twice manually. There was no significant difference in the mean realignment performed by the automatic and the manual methods while centering differed moderately in some instances. In all cases and for all parameters, the reproducibility of the automatic method was 1.00, while it ranged between 0.74 and 0.98 with the manual centering and reorientation. This automatic approach provides a fast and highly reproducible method for the reconstruction of short- and long-axis sections of the left ventricle in 201Tl SPET.