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Development of a clinically feasible [11C]PE2I PET method for differential diagnosis of parkinsonism using reduced scan duration and automated reference region extraction.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Neurology.ORCID iD: 0000-0001-9776-7715
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2017 (English)In: American Journal of Nuclear Medicine and Molecular Imaging, ISSN 2160-8407, Vol. 7, no 6, p. 263-274Article in journal (Refereed) Published
Abstract [en]

[11C]PE2I is a highly selective dopamine transporter PET ligand. Parametric images based on dynamic [11C]PE2I scans, showing dopamine transporter availability (BPND) and relative cerebral blood flow (R1), can be used in differential diagnosis of parkinsonism. This work aimed to investigate a shortened scan duration and automated generation of parametric images which are two prerequisites for routine clinical application. Twelve subjects with parkinsonism and seventeen healthy controls underwent 80 min dynamic [11C]PE2I PET scans. BPND and R1 images were generated using cerebellum reference region defined on a co-registered MRI, as well as a supervised cluster analysis (SVCA)-based reference. Initial 20, 30 and 40 min of the scans were extracted and images of standardized uptake value ratio (SUVR) and R1 were computed using MRI- and SVCA-based reference. Correlation was high between striatal 80 min MRI-based BPND and 40 min SVCA-based SUVR-1 (R2=0.95). High correlation was also found between R1 values in striatal and limbic regions (R2≥0.91) whereas correlation was moderate for cortical regions (R2=0.71). The results indicate that dynamic [11C]PE2I scans can be restricted to 40 min and that SVCA can be used for automatic extraction of a reference region. These outcomes will support routine applications of [11C]PE2I PET in clinical settings.

Place, publisher, year, edition, pages
2017. Vol. 7, no 6, p. 263-274
Keywords [en]
PET, [11C]PE2I, parametric images, parkinsonism, supervised clustering
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-340790ISI: 000419593300003PubMedID: 29348981OAI: oai:DiVA.org:uu-340790DiVA, id: diva2:1179814
Funder
Swedish Research CouncilSwedish Society for Medical Research (SSMF)Available from: 2018-02-02 Created: 2018-02-02 Last updated: 2018-02-21Bibliographically approved
In thesis
1. Towards Clinical Implementation of Dynamic Positron Emission Tomography in Neurodegenerative Diseases
Open this publication in new window or tab >>Towards Clinical Implementation of Dynamic Positron Emission Tomography in Neurodegenerative Diseases
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common neurodegenerative disorders worldwide. Positron emission tomography (PET), together with suitable biomarkers, can aid in the clin-ical evaluation as well as in research investigations of these diseases. Straightforward and quantitative assessments of the parameters of inter-est estimated on a voxel-level, as parametric images, are possible when PET data is acquired over time. Prerequisites to facilitate clinical use of dynamic PET are simplified analysis methods and scan protocols suita-ble for clinical routine.

The aim of this thesis was to validate simplified analysis methods, suitable for clinical use, for quantification of dopamine transporter (DAT) availability in patients with parkinsonism using [11C]PE2I PET and tau accumulation in AD patients with [18F]THK5317 PET.

The included subjects comprised of both healthy controls and pa-tients with parkinsonism, AD or mild cognitive impairment and each subject underwent a dynamic PET scan with either [11C]PE2I or [18F]THK5317. Models for quantitative voxel-based analysis, resulting in parametric images of tracer binding and overall brain function, were validated in both patients and controls. These parametric methods were compared to region-based values acquired using both plasma- and refer-ence-input models. Clinically feasible scan durations were evaluated for both [11C]PE2I and [18F]THK5317, and a clustering method to obtain a reference time activity curve directly from the dynamic PET data was validated. Furthermore, images of DAT availability and overall brain functional activity, generated from one single dynamic [11C]PE2I PET scan, were compared to a dual-scan approach using [123I]FP-CIT single photon emission computed tomography (SPECT) and [18F]FDG PET, for differential diagnosis of patient with parkinsonism.

Study I-III supply valuable information on the feasibility of dynamic [11C]PE2I in a clinical setting for differential diagnosis of parkinsonian disorders, by having easily accessible images of DAT availability and overall brain functional activity. The work in study IV-V showed that reference methods can be used for quantification of tau accumulation, and suggests that simplified analysis methods and shorter scan durations can be applied to further facilitate applications of dynamic [18F]THK5317 PET.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 55
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1429
Keywords
Positron emission tomography, PET, Molecular imaging, Quantification, Kinetic modelling, Parametric images, Alzheimer’s disease, Parkinson’s disease
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Radiology
Identifiers
urn:nbn:se:uu:diva-341786 (URN)978-91-513-0238-6 (ISBN)
Public defence
2018-04-06, Skoogsalen, Akademiska Sjukhuset, Ing 79, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2018-03-14 Created: 2018-02-15 Last updated: 2018-04-24

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