Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging

Enrico Premi, V. D. Calhoun, V. Garibotto, R. Turrone, A. Alberici, E. Cottini, A. Pilotto, S. Gazzina, M. Magoni, B. Paghera, B. Borroni, A. Padovani

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)772-778
Number of pages7
JournalMolecular Imaging and Biology
Issue number5
StatePublished - Oct 1 2017


  • Parkinson’s disease
  • Source-based morphometry
  • Statistical parametric mapping
  • [I]FP-CIT imaging

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research


Dive into the research topics of 'Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging'. Together they form a unique fingerprint.

Cite this