AUTHOR=Liu Xiu-Lin , Liu Shu-Ying , Barret Olivier , Tamagnan Gilles D. , Qiao Hong-Wen , Song Tian-Bin , Lu Jie , Chan Piu TITLE=Diagnostic value of striatal 18F-FP-DTBZ PET in Parkinson’s disease JOURNAL=Frontiers in Aging Neuroscience VOLUME=14 YEAR=2022 URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.931015 DOI=10.3389/fnagi.2022.931015 ISSN=1663-4365 ABSTRACT=Background

18F-FP-DTBZ has been proven as a biomarker for quantifying the concentration of presynaptic vesicular monoamine transporter 2 (VMAT2). However, its clinical application is still limited.

Objectives

To evaluate the difference in dopaminergic integrity between patients with Parkinson’s disease (PD) and healthy controls (HC) using 18F-FP-DTBZ PET in vivo and to determine the diagnostic value of standardized uptake value ratios (SUVRs) using the Receiver Operating Characteristic (ROC) curve.

Methods

A total of 34 PD and 31 HC participants were enrolled in the PET/MR derivation cohort, while 89 PD and 18 HC participants were recruited in the PET/CT validation cohort. The Hoehn–Yahr Scale and the third part of the MDS-Unified Parkinson’s Disease Rating Scale (MDSUPDRS-III) were used to evaluate the disease staging and severity. All assessments and PET scanning were performed in drug-off states. The striatum was segmented into five subregions as follows: caudate, anterior dorsal putamen (ADP), anterior ventral putamen (AVP), posterior dorsal putamen (PDP), and posterior ventral putamen (PVP) using automatic pipeline built with the PMOD software (version 4.105). The SUVRs of the targeted subregions were calculated using the bilateral occipital cortex as the reference region.

Results

Regarding the diagnostic value, ROC curve and blind validation showed that the contralateral PDP (SUVR = 3.43) had the best diagnostic accuracy (AUC = 0.973; P < 0.05), with a sensitivity of 97.1% (95% CI: 82.9–99.8%), specificity of 100% (95% CI: 86.3–100%), positive predictive value (PPV) of 100% (95% CI: 87.0–100%), negative predictive value (NPV) of 96.9% (95% CI: 82.0–99.8%), and an accuracy of 98.5% for the diagnosis of PD in the derivation cohort. Blind validation of 18F-FP-DTBZ PET imaging diagnosis was done using the PET/CT cohort, where participants with a SUVR of the PDP <3.43 were defined as PD. Kappa test showed a consistency of 0.933 (P < 0.05) between clinical diagnosis and imaging diagnosis, with a sensitivity of 98.9% (95% CI: 93.0–99.9%), specificity of 94.4% (95% CI: 70.6–99.7%), PPV of 98.9% (95% CI: 93.0–99.9%), NPV of 94.4% (95% CI: 70.6–99.7%), and a diagnostic accuracy of 98.1%.

Conclusions

Our results showed that an SUVR threshold of 3.43 in the PDP could effectively distinguish patients with PD from HC.