For the quantitative assessment of dopamine transporter (DAT) using [123I]FP-CIT single-photon emission computed tomography (SPECT) (DaTscan), anatomic standardization is preferable for achieving objective and user-independent quantification of striatal binding using a volume-of-interest (VOI) template. However, low accumulation of DAT in Parkinson’s disease (PD) would lead to a deformation error when using a DaTscan-specific template without any structural information. To avoid this deformation error, we applied computed tomography (CT) data obtained using SPECT/CT equipment to anatomic standardization.Methods
We retrospectively analyzed DaTscan images of 130 patients with parkinsonian syndromes (PS), including 80 PD and 50 non-PD patients. First we segmented gray matter from CT images using statistical parametric mapping 12 (SPM12). These gray-matter images were then anatomically standardized using the diffeomorphic anatomical registration using exponentiated Lie algebra (DARTEL) algorithm. Next, DaTscan images were warped with the same parameters used in the CT anatomic standardization. The target striatal VOIs for decreased DAT in PD were generated from the SPM12 group comparison of 20 DaTscan images from each group. We applied these VOIs to DaTscan images of the remaining patients in both groups and calculated the specific binding ratios (SBRs) using nonspecific counts in a reference area. In terms of the differential diagnosis of PD and non-PD groups using SBR, we compared the present method with two other methods, DaTQUANT and DaTView, which have already been released as software programs for the quantitative assessment of DaTscan images.Results
The SPM12 group comparison showed a significant DAT decrease in PD patients in the bilateral whole striatum. Of the three methods assessed, the present CT-guided method showed the greatest power for discriminating PD and non-PD groups, as it completely separated the two groups.Conclusion
CT-guided anatomic standardization using the DARTEL algorithm is promising for the quantitative assessment of DaTscan images.
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