, Volume 12, Issue 4, pp 575–593 | Cite as

A Standardized [18F]-FDG-PET Template for Spatial Normalization in Statistical Parametric Mapping of Dementia

  • Pasquale Anthony Della Rosa
  • Chiara Cerami
  • Francesca Gallivanone
  • Annapaola Prestia
  • Anna Caroli
  • Isabella Castiglioni
  • Maria Carla Gilardi
  • Giovanni Frisoni
  • Karl Friston
  • John Ashburner
  • Daniela Perani
  • and the EADC-PET Consortium
Original Article


[18F]-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) is a widely used diagnostic tool that can detect and quantify pathophysiology, as assessed through changes in cerebral glucose metabolism. [18F]-FDG PET scans can be analyzed using voxel-based statistical methods such as Statistical Parametric Mapping (SPM) that provide statistical maps of brain abnormalities in single patients. In order to perform SPM, a “spatial normalization” of an individual’s PET scan is required to match a reference PET template. The PET template currently used for SPM normalization is based on [15O]-H2O images and does not resemble either the specific metabolic features of [18F]-FDG brain scans or the specific morphological characteristics of individual brains affected by neurodegeneration. Thus, our aim was to create a new [18F]-FDG PET aging and dementia-specific template for spatial normalization, based on images derived from both age-matched controls and patients. We hypothesized that this template would increase spatial normalization accuracy and thereby preserve crucial information for research and diagnostic purposes. We investigated the statistical sensitivity and registration accuracy of normalization procedures based on the standard and new template—at the single-subject and group level—independently for subjects with Mild Cognitive Impairment (MCI), probable Alzheimer’s Disease (AD), Frontotemporal lobar degeneration (FTLD) and dementia with Lewy bodies (DLB). We found a significant statistical effect of the population-specific FDG template-based normalisation in key anatomical regions for each dementia subtype, suggesting that spatial normalization with the new template provides more accurate estimates of metabolic abnormalities for single-subject and group analysis, and therefore, a more effective diagnostic measure.


18F-FDG PET SPM (RRID:nif-0000-00343) Spatial normalization Template Dementia 



We thank the EADC-PET Consortium (Alexander Drzezga and Robert Perneczky [Munich], Mira Didic and Eric Guedj [Marseilles], Bart N. Van Berckel and Rik Ossenkoppele [Amsterdam], Flavio Nobili and Silvia Morbelli [Genoa], Giovanni Frisoni, Anna Caroli [Brescia]) for kindly providing EADC-PET imaging data for the purposes of the current study. This study was supported in part by the 6th European Framework Program Network of Excellence “DIMI” LSHB-CT-2005-512146, and the 7th Framework Programme for Research and Technological Development “DECIDE” RI-261593 and in part by the Italian Ministry of Education in the framework of the Project of Strategic National Interest “Invecchiamento: innovazioni tecnologiche e molecolari per un miglioramento della salute dell’anziano” allocated to the National Research Council. Karl Friston and John Ashburner are based at The Wellcome Trust Centre for Neuroimaging, which is supported by core funding from the Wellcome Trust [091593/Z/10/Z].

Conflict of Interest

The authors declare that they have no conflict of interest.

Open Access

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Supplementary material

12021_2014_9235_MOESM1_ESM.doc (39 kb)
Supplementary Table 1 (DOC 39 kb)
12021_2014_9235_MOESM2_ESM.docx (468 kb)
ESM 1 (DOCX 470 kb)
12021_2014_9235_MOESM3_ESM.doc (26 kb)
ESM 2 (DOC 25 kb)


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Pasquale Anthony Della Rosa
    • 1
  • Chiara Cerami
    • 2
    • 3
  • Francesca Gallivanone
    • 1
  • Annapaola Prestia
    • 4
  • Anna Caroli
    • 5
  • Isabella Castiglioni
    • 1
  • Maria Carla Gilardi
    • 1
    • 6
  • Giovanni Frisoni
    • 4
    • 7
  • Karl Friston
    • 8
  • John Ashburner
    • 9
  • Daniela Perani
    • 2
    • 10
  • and the EADC-PET Consortium
  1. 1.Institute of Molecular Bioimaging and PhysiologyNational Research CouncilSegrateItaly
  2. 2.Vita-Salute San Raffaele UniversityMilanItaly
  3. 3.Clinical Neurosciences Department, San Raffaele Hospital, Division of Neuroscience, San Raffaele Scientific InstituteMilanItaly
  4. 4.IRCCS Centre San Giovanni di Dio - Fatebenefratelli, Laboratory of Epidemiology and NeuroimagingBresciaItaly
  5. 5.Medical Imaging Unit, Bioengineering Department, IRCCS Mario Negri Institute for Pharmacological ResearchBergamoItaly
  6. 6.University of Milan - Bicocca, Department of Health SciencesMilanItaly
  7. 7.Department of PsychiatryGeneva University Hospital and University of GenevaGenevaSwitzerland
  8. 8.Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College LondonLondonUK
  9. 9.Wellcome Trust Centre for NeuroimagingLondonUK
  10. 10.Nuclear Medicine Unit, San Raffaele Hospital, Division of Neuroscience, San Raffaele Scientific InstituteMilanItaly

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