Maximizing the detection and localization of Ga-67 tumors in thoracic SPECT MLEM(OSEM) reconstructions

Iterative reconstruction algorithms are usually regularized by applying a penalty function, by post-filtering, or by halting the algorithm after some number of iterations. It is difficult to know a priori what is the optimal combination of regularization methods. One method of selection is to use a localization receiver operating characteristic (LROC) study. LROC extends ROC analysis by incorporating a search-and-localize component into the task. Using LROC, the authors investigated the combination of iteration number and 3D Gaussian filter which will maximize the detectability and localization accuracy of 1-cm gallium-avid tumors in maximum-likelihood (ordered-subset) expectation-maximization SPECT reconstructions of the chest region. In the authors´ study, 5 observers read 200 images per test condition, divided equally over 2 reading sessions. In each case, the observer indicated the most probable location of the lesion in the image and provided a confidence rating (as in an ROC experiment). The best observer performance was achieved using a reconstruction with 8 iterations of MLEM followed by filtering with a 3D Gaussian filter having a 4-pixel (1.3 cm) FWHM, although the difference between this test condition and others is not significant over a broad range of the parameters considered