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A Standardized [18F]-FDG-PET Template for Spatial Normalization in Statistical Parametric Mapping of Dementia | Neuroinformatics Skip to main content

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

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Abstract

[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.

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Acknowledgments

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.

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Authors and Affiliations

  1. Institute of Molecular Bioimaging and Physiology, National Research Council, Segrate, MI, Italy

    Pasquale Anthony Della Rosa, Francesca Gallivanone, Isabella Castiglioni & Maria Carla Gilardi

  2. Vita-Salute San Raffaele University, Milan, Italy

    Chiara Cerami & Daniela Perani

  3. Clinical Neurosciences Department, San Raffaele Hospital, Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy

    Chiara Cerami

  4. IRCCS Centre San Giovanni di Dio - Fatebenefratelli, Laboratory of Epidemiology and Neuroimaging, Brescia, Italy

    Annapaola Prestia & Giovanni Frisoni

  5. Medical Imaging Unit, Bioengineering Department, IRCCS Mario Negri Institute for Pharmacological Research, Bergamo, Italy

    Anna Caroli

  6. University of Milan - Bicocca, Department of Health Sciences, Milan, Italy

    Maria Carla Gilardi

  7. Department of Psychiatry, Geneva University Hospital and University of Geneva, Geneva, Switzerland

    Giovanni Frisoni

  8. Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK

    Karl Friston

  9. Wellcome Trust Centre for Neuroimaging, London, UK

    John Ashburner

  10. Nuclear Medicine Unit, San Raffaele Hospital, Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy

    Daniela Perani

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  1. Pasquale Anthony Della Rosa
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  9. Karl Friston
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  10. John Ashburner
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Correspondence to Pasquale Anthony Della Rosa or Daniela Perani.

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*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]

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Della Rosa, P.A., Cerami, C., Gallivanone, F. et al. A Standardized [18F]-FDG-PET Template for Spatial Normalization in Statistical Parametric Mapping of Dementia. Neuroinform 12, 575–593 (2014). https://doi.org/10.1007/s12021-014-9235-4

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