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, we 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 our study, five observers read 200 images per test condition, divided equally over two 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 performance in our experiment was achieved using reconstruction with 8 iterations of MLEM followed by a 3D Gaussian filter with a 4-pixel (1.3 cm) FWHM