Quantitative study of 18F-(+)DTBZ image: comparison of PET template-based and MRI based image analysis

Hsu Jung Lung, Yi Hsin Weng, Ming Ching Wen, Ing Tsung Hsiao, Kun Ju Lin*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

13 Scopus citations

Abstract

[18F]9-fluoropropyl-(+)-dihydrotetrabenazine (18F-(+)DTBZ) is a recently developed PET tracer to investigate the vesicular monoamine transporter type 2 (VMAT2) activity in measuring dopaminergic degeneration in vivo and monitoring the severity of Parkinson’s disease (PD). However, manual drawing of the striatal regions is time consuming and prone to human bias. In the current study, we developed an automated method to quantify the signals of the striatum on 18F-(+)DTBZ images. 39 patients with PD and 26 controls were enrolled. Traditional brain magnetic resonance imaging (MRI) and 18F-(+)DTBZ PET were acquired. Both indirect normalization of native PET images to the standard space through individual brain MRI and directly coregistration of native images to the transporter-specific PET template in standard space were performed. Specific uptake ratios (SURs) in 10 predefined regions were used as indicators of VMAT2 activities to correlate with motor severity. Our results showed patients with PD had significant lower SURs in the bilateral putamina, caudates and globus pallidi than controls. SURs in the caudate and putamen were significantly correlated with motor severity. The contralateral putaminal region performed best in discriminating between PD patients and controls. Finally, the results from the application of the 18F-(+)DTBZ PET template were comparable to those derived from the traditional MRI based method. Thus, 18F-(+)DTBZ PET imaging holds the potential to effectively differentiate PD patients from controls. The 18F-(+)DTBZ PET template-based method for automated quantification of presynaptic VMAT2 transporter density is easier to implement and may facilitate efficient, robust and user-independent image analysis.

Original languageEnglish
Article number16027
JournalScientific Reports
Volume8
Issue number1
DOIs
StatePublished - 01 12 2018

Bibliographical note

Publisher Copyright:
© 2018, The Author(s).

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