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Brain Topography

, Volume 27, Issue 3, pp 329–337 | Cite as

Multivariate Pattern Recognition for Diagnosis and Prognosis in Clinical Neuroimaging: State of the Art, Current Challenges and Future Trends

  • Sven HallerEmail author
  • Karl-Olof Lovblad
  • Panteleimon Giannakopoulos
  • Dimitri Van De Ville
Review

Abstract

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Keywords

MRI Pattern recognition Support vector machines SVM Multivariate Predictive modeling 

Abbreviations

AD

Alzheimer disease

ADNI

Alzheimer disease neuroimaging initiative

DTI

Diffusion tensor imaging

fMRI

Functional magnetic resonance imaging

MCI

Mild cognitive impairment

MRI

Magnetic resonance imaging

SVM

Support vector machines

VBM

Voxel based morphometry

Notes

Acknowledgments

This work was supported in parts by the Swiss National Science Foundation (SNF) grants 320030_147126/1 and PP00P2-146318

Conflict of interest

No conflicts of interest.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sven Haller
    • 1
    Email author
  • Karl-Olof Lovblad
    • 1
  • Panteleimon Giannakopoulos
    • 2
  • Dimitri Van De Ville
    • 3
    • 4
  1. 1.Department of Imaging and Medical InformaticsUniversity Hospitals of Geneva and Faculty of Medicine of the University of GenevaGenevaSwitzerland
  2. 2.Department of Mental Health and PsychiatryUniversity Hospitals of Geneva and Faculty of Medicine of the University of GenevaGenevaSwitzerland
  3. 3.Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
  4. 4.Institute of BioengineeringEcole Polytechnique Fédérale de LausanneLausanneSwitzerland

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