Positron emission tomography (PET) has evolved into a technique that can accurately determine the distribution of positron-emitting radionuclides. The addition of a coincidence detection mode to a standard dual-head detector system has resulted in the option of single-photon and annihilation coincidence detection. This new device for imaging fluorine-18 2-fluoro-2-deoxy-D-glucose (18F-FDG) accumulation in neoplasms became commercially available in 1994. Besides conventional low-energy imaging in the collimated single-photon mode, it offers a relatively inexpensive opportunity to perform uncollimated PET by switching to the coincidence acquisition mode. This review summarises the clinical value of 18F-FDG detection with a dual-head coincidence camera in oncology. The results are compared with the overall results obtained using dedicated PET scanners. With respect to head and neck tumours, 18F-FDG coincidence mode gamma camera imaging (CGI) yields results that are in agreement with those obtained with dedicated PET scanners. With regard to other malignancies, such as lung cancer, lymphoma and brain tumours, data in the literature are too scarce to draw any definite conclusions. In general, the results of 18F-FDG CGI in tumours >15 mm seem to be comparable to those obtained with dedicated PET scanners, whereas in tumours <15 mm, the relative sensitivity of 18F-FDG CGI is approximately 80%. Using attenuation correction, the diagnostic yield of 18F-FDG CGI may increase. However, further clinical investigation is required to definitely establish its value in staging primary disease, therapy monitoring and assessment of tumour recurrence in clinical oncology.
To delineate the myocardium in planar thallium-201 scintigrams of the left ventricle, a method, based on the Hough transformation, is presented. The method maps feature points (X, Y, Y')-where Y' reflects the direction of the tangent in edge point (X,Y)-into the two-dimensional space of the axis lengths of the ellipse. Within this space, a probability density function (pdf) can be estimated. When the center of the ellipse or its orientation are unknown, the 2-D pdf of the lengths of the axes is extended to a 5-D pdf of all parameters of the ellipse (lengths of the axes, coordinates of the center, and the orientation). It is shown that the variance of the edge-point-based estimates of the axis lengths increases when the location error of the center of the supposed ellipse or its orientation error increases. The likelihood of the estimates is expected to decrease with increasing variance. Therefore, local search algorithms can be applied to find the maximum likelihood estimate of the parameters of the ellipse. Curves describing the convergency of the algorithm are presented, as well as an example of the application of the algorithm to real scintigrams. The method is able to detect contours even if they are only partly visualized, as in thallium scintigrams of the myocardium of patients with ischemic heart disease. As long as the number of parameters describing the contour is relatively low, such an algorithm is also suitable for application to differently curved contours.
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