Impact of expectation-maximization reconstruction iterations on the diagnosis of temporal lobe epilepsy with PET.

There is a well known tradeoff between image noise and image sharpness that is dependent on the number of iterations performed in ordered subset expectation maximization (OSEM) reconstruction of PET data. We aim to evaluate the impact of this tradeoff on the sensitivity and specificity of (18)F-FDG PET for the diagnosis of temporal lobe epilepsy. A retrospective blinded reader study was performed on two OSEM reconstructions, using either 2 or 5 iterations, of 32 (18)F-FDG PET studies acquired at our institution for the diagnosis of temporal lobe epilepsy. The sensitivity and specificity of each reconstruction for identifying patients who were ultimately determined to be surgical candidates was assessed using an ROC analysis. The sensitivity of each reconstruction for identifying patients who showed clinical improvement following surgery was also assessed. Our results showed no significant difference between the two reconstructions studied for either the sensitivity and specificity of (18)F-FDG PET for predicting surgical candidacy, or its sensitivity for predicting positive surgical outcomes. This implies that the number of iterations performed during OSEM reconstruction will have little impact on a reader based interpretation of (18)F-FDG PET scans acquired for the diagnosis of temporal lobe epilepsy, and can be determined by physician and institutional preference.