Methods: We present a Sub-Volume Thresholding (SVT) method for analyzing positron emission tomography (PET) and single photon emission computed tomography (SPECT) data and determining separately the statistical significance of the effects of motor stimulation on brain perfusion. Incorporation of a priori anatomical information into the functional SVT model is achieved by selecting a proper anatomically partitioned probabilistic atlas for the data. We use a general Gaussian random field model to account for the intrinsic differences in intensity distribution across brain regions related to the physiology of brain activation, attenuation effects, dead time and other corrections in PET imaging and data reconstruction.
Results: H2 15O PET scans are acquired from six normal subjects under two different activation paradigms: left-hand and right-hand finger tracking task with visual stimulus. Regional (ROI) and local (voxel) group differences between the left and right motor tasks are obtained using non-parametric stochastic variance estimates. As expected from our simple finger movement paradigm, significant activation (Z = 6.7) was identified in the left motor cortex for the right movement task, and significant activation (Z = 6.3) for the left movement task in the right motor cortex.
Conclusions: We propose, test and validate probabilistic sub-volume thresholding method for mapping statistical variability between groups in subtraction paradigm studies of functional brain data. This method incorporates knowledge of, and controls for, anatomic variability contained in modern human brain probabilistic atlases in functional statistical mapping of the brain.