Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging.
- Premi E Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. zedtower@gmail.com.
- Calhoun VD The Mind Research Network, Albuquerque, NM, 87106, USA.
- Garibotto V Department of Medical Imaging, Geneva University Hospital, Geneva, Switzerland.
- Turrone R Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Alberici A Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Cottini E Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Pilotto A Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Gazzina S Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Magoni M Stroke Unit, Azienda Ospedaliera "Spedali Civili", Spedali Civili Hospital, Brescia, Italy.
- Paghera B Nuclear Medicine Unit, Azienda Azienda Ospedaliera "Spedali Civili", Spedali Civili Hospital, Brescia, Italy.
- Borroni B Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- Padovani A Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
- 2017-02-15
Published in:
- Molecular imaging and biology. - 2017
Parkinson’s disease
Source-based morphometry
Statistical parametric mapping
[123I]FP-CIT imaging
Aged
Case-Control Studies
Demography
Female
Humans
Male
Middle Aged
Multivariate Analysis
Parkinson Disease
Tomography, Emission-Computed, Single-Photon
Tropanes
English
PURPOSE
[123I]FP-CIT (DaTSCAN®) single-photon emission computed tomography (SPECT) imaging is widely used to study neurodegenerative parkinsonism, by measuring presynaptic dopamine transporter (DAT) in striatal regions. Beyond DAT, [123I]FP-CIT may be considered for other monoaminergic systems, in particular the serotonin transporter (SERT). Independent component analysis (ICA) implemented in source-based morphometry (SBM) could represent an alternative method to explore monoaminergic pathways, studying the relationship among voxels and grouping them into "neurotransmission" networks.
PROCEDURES
One hundred forty-three subjects [84 with Parkinson's disease (PD) and 59 control individuals (CG)] underwent DATSCAN® imaging. The [123I]FP-CIT binding was evaluated by multivariate SBM approach, as well as by a whole-brain voxel-wise univariate (statistical parametric mapping, SPM) approach.
RESULTS
As compared to the univariate whole-brain approach (SPM) (only demonstrating striatal [123I]FP-CIT binding reduction in PD group), SBM identified six sources of non-artefactual origin, including basal ganglia and cortical regions as well as brainstem. Among them, three sources (basal ganglia and cortical regions) presented loading scores (as index of [123I]FP-CIT binding) significantly different between PD and CG. Notably, even if not significantly different between PD and CG, the remaining three non-artefactual sources were characterized by a predominant frontal, brainstem, and occipito-temporal involvement.
CONCLUSION
The concept of source blind separation by the application of ICA (as implemented in SBM) represents a feasible approach to be considered in [123I]FP-CIT (DaTSCAN®) SPECT imaging. Taking advantage of this multivariate analysis, specific patterns of variance can be identified (involving either striatal than extrastriatal regions) that could be useful in differentiating neurodegenerative parkinsonisms.
[123I]FP-CIT (DaTSCAN®) single-photon emission computed tomography (SPECT) imaging is widely used to study neurodegenerative parkinsonism, by measuring presynaptic dopamine transporter (DAT) in striatal regions. Beyond DAT, [123I]FP-CIT may be considered for other monoaminergic systems, in particular the serotonin transporter (SERT). Independent component analysis (ICA) implemented in source-based morphometry (SBM) could represent an alternative method to explore monoaminergic pathways, studying the relationship among voxels and grouping them into "neurotransmission" networks.
PROCEDURES
One hundred forty-three subjects [84 with Parkinson's disease (PD) and 59 control individuals (CG)] underwent DATSCAN® imaging. The [123I]FP-CIT binding was evaluated by multivariate SBM approach, as well as by a whole-brain voxel-wise univariate (statistical parametric mapping, SPM) approach.
RESULTS
As compared to the univariate whole-brain approach (SPM) (only demonstrating striatal [123I]FP-CIT binding reduction in PD group), SBM identified six sources of non-artefactual origin, including basal ganglia and cortical regions as well as brainstem. Among them, three sources (basal ganglia and cortical regions) presented loading scores (as index of [123I]FP-CIT binding) significantly different between PD and CG. Notably, even if not significantly different between PD and CG, the remaining three non-artefactual sources were characterized by a predominant frontal, brainstem, and occipito-temporal involvement.
CONCLUSION
The concept of source blind separation by the application of ICA (as implemented in SBM) represents a feasible approach to be considered in [123I]FP-CIT (DaTSCAN®) SPECT imaging. Taking advantage of this multivariate analysis, specific patterns of variance can be identified (involving either striatal than extrastriatal regions) that could be useful in differentiating neurodegenerative parkinsonisms.
- Language
-
- English
- Open access status
- green
- Identifiers
-
- DOI 10.1007/s11307-017-1052-3
- PMID 28194630
- Persistent URL
- https://folia.unifr.ch/global/documents/103443
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