Parkinson's disease (PD) is characterized by a degeneration of nigrostriatal dopaminergic neurons, which can be imaged with 123I-labeled 2 beta-carbomethoxy-3 beta-(4-iodophenyl) tropane ([123I]beta-CIT) and single-photon emission computed tomography (SPECT). However, the quality of the region of interest (ROI) technique used for quantitative analysis of SPECT data is compromised by limited anatomical information in the images. We investigated whether the diagnosis of PD can be improved by combining the use of SPECT images with morphological image data from magnetic resonance imaging (MRI)/computed tomography (CT). We examined 27 patients (8 men, 19 women; aged 55 +/- 13 years) with PD (Hoehn and Yahr stage 2.1 +/- 0.8) by high-resolution [123I]beta-CIT SPECT (185-200 MBq, Ceraspect camera). SPECT images were analyzed both by a unimodal technique (ROIs defined directly within the SPECT studies) and a multimodal technique (ROIs defined within individual MRI/CT studies and transferred to the corresponding interactively coregistered SPECT studies). [123I]beta-CIT binding ratios (cerebellum as reference), which were obtained for heads of caudate nuclei (CA), putamina (PU), and global striatal structures were compared with clinical parameters. Differences between contra- and ipsilateral (related to symptom dominance) striatal [123I]beta-CIT binding ratios proved to be larger in the multimodal ROI technique than in the unimodal approach (e.g., for PU: 1.2 vs. 0.7). Binding ratios obtained by the unimodal ROI technique were significantly correlated with those of the multimodal technique (e.g., for CA: y = 0.97x + 2.8; r = 0.70; P < 0.001). Concerning the correlations between SPECT data and clinical parameters, the significance levels in the multimodal ROI technique, for example, for the correlation between CA and the UPDRScom subscore (r = -0.49 vs. -0.32). These results show that the impact of [123I]beta-CIT SPECT for diagnosing PD is affected by the method used to analyze the SPECT images. The described multimodal approach, which is based on coregistration of SPECT and morphological imaging data, leads to improved determination of the degree of this dopaminergic disorder.