TY - JOUR
T1 - Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging
AU - Premi, Enrico
AU - Calhoun, V. D.
AU - Garibotto, V.
AU - Turrone, R.
AU - Alberici, A.
AU - Cottini, E.
AU - Pilotto, A.
AU - Gazzina, S.
AU - Magoni, M.
AU - Paghera, B.
AU - Borroni, B.
AU - Padovani, A.
N1 - Publisher Copyright:
© 2017, World Molecular Imaging Society.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
KW - Parkinson’s disease
KW - Source-based morphometry
KW - Statistical parametric mapping
KW - [I]FP-CIT imaging
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U2 - 10.1007/s11307-017-1052-3
DO - 10.1007/s11307-017-1052-3
M3 - Article
C2 - 28194630
AN - SCOPUS:85012293391
VL - 19
SP - 772
EP - 778
JO - Molecular Imaging and Biology
JF - Molecular Imaging and Biology
SN - 1536-1632
IS - 5
ER -