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Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns

  • Ninon Burgos
  • Jorge Samper-González
  • Anne Bertrand
  • Marie-Odile Habert
  • Sébastien Ourselin
  • Stanley Durrleman
  • M.  Jorge  Cardoso
  • Olivier Colliot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10555)

Abstract

We introduce a pipeline for the individual analysis of positron emission tomography (PET) data on large cohorts of patients. This pipeline consists for each individual of generating a subject-specific model of healthy PET appearance and comparing the individual’s PET image to the model via a novel regularised Z-score. The resulting voxel-wise Z-score map can be interpreted as a subject-specific abnormality map that summarises the pathology’s topographical distribution in the brain. We then propose a strategy to validate the abnormality maps on several PET tracers and automatically detect the underlying pathology by using the abnormality maps as features to feed a linear support vector machine (SVM)-based classifier.

We applied the pipeline to a large dataset comprising 298 subjects selected from the ADNI2 database (103 cognitively normal, 105 late MCI and 90 Alzheimer’s disease subjects). The high classification accuracy obtained when using the abnormality maps as features demonstrates that the proposed pipeline is able to extract for each individual the signal characteristic of dementia from both FDG and Florbetapir PET data.

Notes

Acknowledgements

The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. PCOFUND-GA-2013-609102, through the PRESTIGE programme coordinated by Campus France, and from the programme “Investissements d’avenir” ANR-10-IAIHU-06.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ninon Burgos
    • 1
    • 2
  • Jorge Samper-González
    • 1
    • 2
  • Anne Bertrand
    • 1
    • 2
    • 3
  • Marie-Odile Habert
    • 4
  • Sébastien Ourselin
    • 5
    • 6
  • Stanley Durrleman
    • 1
    • 2
  • M.  Jorge  Cardoso
    • 5
    • 6
  • Olivier Colliot
    • 1
    • 2
    • 3
    • 7
  1. 1.Inria Paris, Aramis Project-TeamParisFrance
  2. 2.Sorbonne Universités, UPMC Univ Paris 06, Inserm, CNRS, Institut du Cerveau et la Moelle épinière (ICM) - Pitié-Salpêtrière HospitalParisFrance
  3. 3.AP-HP, Department of NeuroradiologyPitié-Salpêtrière HospitalParisFrance
  4. 4.AP-HP, Department of Nuclear MedicineSorbonne Universités, Pitié-Salpêtrière Hospital, UPMC Univ Paris 06, Inserm U 1146,CNRS UMR 7371, UMR 7371, Laboratoire d’Imagerie BiomédicaleParisFrance
  5. 5.Translational Imaging Group, CMICUniversity College LondonLondonUK
  6. 6.Dementia Research CentreUniversity College LondonLondonUK
  7. 7.AP-HP, Department of NeurologyPitié-Salpêtrière HospitalParisFrance

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