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(18)F-FECNT: validation as PET dopamine transporter ligand in parkinsonism.

ABSTRACT: The positron emission tomography (PET) tracer 2?-carbomethoxy-3?-(4-chlorophenyl)-8-(2-[18F]-fluoroethyl)-nortropane ((18)F-FECNT) is a highly specific ligand for dopamine transporter (DAT) that yields higher peak striatum-to-cerebellum ratios and offers more favorable kinetics than most (18)F-radiolabeled DAT ligands currently available. The goal of this study is to validate the use of (18)F-FECNT as a PET radiotracer to assess the degree of striatal dopamine terminals denervation and midbrain dopaminergic cell loss in MPTP-treated parkinsonian monkeys. Three rhesus monkeys received weekly injections of MPTP (0.2-0.5 mg/kg) for 21 weeks, which resulted in the progressive development of a moderate level of parkinsonism. We carried out (18)F-FECNT PET at baseline (twice; 10 weeks apart) and at week 21 post-MPTP injections. Postmortem stereological cell counts of dopaminergic neurons in the ventral midbrain, and intensity measurements of DAT and tyrosine hydroxylase (TH) immunoreactivity in the striatum were performed and correlated with striatal and ventral midbrain PET data. Three additional monkeys were used as controls for midbrain dopaminergic cell counts, and striatal DAT or TH immunoreactivity measurements. The correlation and coefficient of variance between (18)F-FECNT test-retest specific uptake ratios were 0.99 (R²) and 2.65%, respectively. The (18)F-FECNT binding potential of the ventral midbrain and striatal regions was tightly correlated with postmortem stereological cell counts of nigral dopaminergic neurons (R²=0.91), and striatal DAT (R²=0.83) or TH (R²=0.88) immunoreactivity intensity measurements. These findings demonstrate that (18)F-FECNT is a highly sensitive PET imaging ligand to quantify both striatal dopamine denervation and midbrain dopaminergic cell loss associated with parkinsonism.

SUBMITTER: Masilamoni G

PROVIDER: S-EPMC3421922 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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(18)F-FECNT: validation as PET dopamine transporter ligand in parkinsonism.

Masilamoni Gunasingh G Votaw John J Howell Leonard L Villalba Rosa M RM Goodman Mark M Voll Ronald J RJ Stehouwer Jeffrey J Wichmann Thomas T Smith Yoland Y

Experimental neurology 20100909 2

The positron emission tomography (PET) tracer 2β-carbomethoxy-3β-(4-chlorophenyl)-8-(2-[18F]-fluoroethyl)-nortropane ((18)F-FECNT) is a highly specific ligand for dopamine transporter (DAT) that yields higher peak striatum-to-cerebellum ratios and offers more favorable kinetics than most (18)F-radiolabeled DAT ligands currently available. The goal of this study is to validate the use of (18)F-FECNT as a PET radiotracer to assess the degree of striatal dopamine terminals denervation and midbrain ...[more]

PMID: 20832405

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Project description:PurposeThis work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.MethodsThis study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning.ResultsThe proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP.ConclusionThis study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis.

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(18)F-FECNT: validation as PET dopamine transporter ligand in parkinsonism.

Publications

(18)F-FECNT: validation as PET dopamine transporter ligand in parkinsonism.

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