Quantification and visualization of defects of the functional dopaminergic system using an automatic algorithm.

In SPECT, the binding of radiotracers in brain areas is usually assessed by manual positioning of regions of interest (ROIs). The disadvantages of this method are that it is an observer-dependent procedure and that it may not be sensitive for assessing defects significantly smaller than the ROI. To circumvent these limitations, we developed a fully automatic three-dimensional technique that quantifies neuronal radiotracer binding on a voxel-by-voxel basis. To build a model of normal 123I-labeled N-omega-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl) nortropane (FPCIT) binding, 17 studies of healthy volunteers were registered to the same orientation. After registration, the specific-to-nonspecific binding ratio was calculated for each voxel of the striatal volumes of interest (VOIs). The mean and SD of that binding ratio were then calculated on a voxel-by-voxel basis. For the analysis of 10 healthy volunteer studies (control group) and 21 studies of drug-naive patients with Parkinson's disease, the registration and calculation of the specific-to-nonspecific [123I]FPCIT binding ratio were performed by the same method. Subsequently, a voxel of the striata was classified as a diminished [123I]FPCIT binding ratio if its value was lower than the mean -2 x SD. For each subject, the defect size, the relative number of voxels with a diminished binding ratio and the binding ratio of the whole striatal VOIs were calculated and compared with the binding ratio as assessed by the traditional ROI method. The results of the automatic method correlated significantly with the results of the traditional ROI method. Furthermore, for the ipsilateral side, the automatically calculated defect size had less overlap between the patient and the control group than the traditionally calculated binding ratio. The method presented quantifies [123I]FPCIT binding ratio automatically on a voxel-by-voxel basis, by comparison with a model of healthy volunteers. We have shown that it is appropriate to use the automatic method as a replacement for the traditional manual method, which enables us to study the localized dopaminergic degeneration process in Parkinson's disease more precisely and without any inter- or intraobserver variability