Evaluation of an automated atlas-based method for DaTscan™ analysis

Objectives To evaluate an automated method for the differentiation of Parkinson's Disease (PD) from healthy controls (HC) using DaTscan SPECT.

Methods 30 PD and 30 HC subjects with DaTscan SPECT imaging data were selected from the Parkinson's Progression Markers Initiative database. Ten PD and ten HC subjects were selected for each of the following age ranges: 50-59, 60-69, and 70-79. Images were automatically aligned to a PD and HC template simultaneously using a 9-parameter affine registration. Pre-defined atlas volumes of interest (VOIs) were then transferred to the patient image using the registration. Uptake ratios were computed, including occipital normalized putamen (P), anterior putamen (AP), posterior putamen (PP), caudate (C), and striatum (STR), caudate normalized putamen (P/C), and asymmetry indices for the putamen (ASYM_P) and striatum (ASYM_S). The asymmetry indices were computed as the absolute difference between the left (L) and right (R) sides divided by the mean of both sides: 2*ABS(L-R) / (L+R). Two-tailed T-tests were performed to determine the most significant ratio for each age range, and the most significant ratios were tested for their accuracy in separating HC from PD.

Results For the 50-59 age range, all ratios were significant (p < 0.05), with the exception of C (L, R, and combined) and AP (L). ASYM_S was the most powerful ratio and separated HC from PD with 95% accuracy. For the 60-69 age range, all ratios were significant (p < 0.05), with the exception of PP (L), C (combined), and ASYM_P. P/C was the most powerful ratio and separated HC from PD with 90% accuracy. For the 70-79 age range, all ratios were significant (p < 0.05), with the exception of ASYM_P and ASYM_S. AP was the most powerful ratio and separated HC from PD with 95% accuracy.

Conclusions An automated method for DaTscan analysis demonstrated the potential for 90-95% accuracy for differentiating PD from HC using uptake ratios. Future studies with a larger cohort are planned.