123 I-FP-CIT SPECT in dementia with Lewy bodies, Parkinson's disease and Alzheimer's disease: a new quantitative analysis of autopsy confirmed cases.

Purpose: The aim of this study was to re-evaluate the differentiation of patients with dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) and Parkinson's disease (PD) using a quantitative analysis of ¹²³ I-FP-CIT SPECT scans.
Methods: Thirty-six patients with in vivo ¹²³ I-FP-CIT SPECT and neuropathological diagnoses were included. Based on neuropathological criteria, patients were further subclassified into nine AD, eight DLB, ten PD and nine with other diagnoses. An additional 16 healthy controls (HC) scanned with ¹²³ I-FP-CIT SPECT were also included. All images were visually assessed as normal versus abnormal uptake by consensus of five nuclear medicine physicians. Bihemispheric mean was calculated for caudate binding potential (CBP), putamen binding potential (PBP) and putamen-to-caudate ratio (PCR).
Results: Patients with DLB had significantly lower CBP and PBP than patients with AD and significantly higher PCR than patients with PD. Qualitative visual analysis of the images gave an accuracy of 88% in the evaluation of the status of the nigrostriatal pathway considering all individuals, and 96% considering only the patients with PD, AD and DLB. Quantitative analyses provided a balanced accuracy of 94%, 94% and 100% in binary classifications DLB versus AD, DLB versus PD and PD versus AD, respectively, and an accuracy of 93% in the differentiation among patients with DLB, AD and PD simultaneously. No statistically significant differences were observed between the AD and HC.
Conclusions: This study demonstrates a very high diagnostic accuracy of the quantitative analysis of( ¹²³ I-FP-CIT SPECT data to differentiate among patients with DLB, PD and AD.
Competing Interests: Competing interests: ZW and DCC received consultancy fees from GE Healthcare (previously Amersham Health), which also provided the 123I-FP-CIT ligand. ZW also received research support from GE Healthcare.
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