On two methods of statistical image analysis

The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activatio n studies. Each includes spatial standardization of image volumes, computat ion of a statistic, and evaluation of its significance. In addition, smooth ing and correcting for differences of global means are commonly performed i n SPM before statistical analysis. We report a comparison of methods in an analysis of regional cerebral blood flow (rCBF) in 10 human volunteers and 10 simulated activations. For the human studies, CBA or linear SPM standari zation methods were followed by smoothing and computation of a statistic wi th the paired t-test of CBA or general linear model of SPM. No standardizat ion, linear, and nonlinear SPM standardization were applied to the simulati ons. Significance of the statistic was evaluated using the cluster-size met hod common to SPM and CBA. SPM employs the theory of Gaussian random fields to estimate the cluster size distributions; simulations described in the A ppendix provided empirical distributions derived from t-maps. The quantitie s evaluated were number and size of functional regions (FRs), maximum stati stic, average resting rCBF, and percentage change. For the simulations, the efficiency of signal detection and rate of false positives could be evalua ted as well as the distributions of statistics and cluster size in the abse nse of signal. The similarity of the results yielded by similar methods of analysis for the human studies and the simulated activations substantiates the robustness of the methods for selecting functional regions. However, th e analysis of simulated activations demonstrated that quantitative evaluati on of significance of a functional region encounters important obstacles at every stage of the analysis. (C) 1999 Wiley-Liss, inc.