Analysis of Outliers Effects in Voxel-Based Morphometry by means of Virtual Phantoms

  • Federico Nocchi
  • T. Franchin
  • E. Genovese
  • D. Longo
  • G. Fariello
  • V. Cannatà
Part of the IFMBE Proceedings book series (IFMBE, volume 20)

Abstract

Voxel-Based Morphometry (VBM) is a technique for analyzing inter-group neuroanatomic differences, frequently used to study a number of neurologic diseases. An important limit to the diffusion of VBM is related to the length of the recruiting process, due to the need of homogeneous and statistically significant samples. Therefore, quite often the need to search for statistically significant differences between small samples arises. The opportunity of analyzing small samples with VBM should be carefully considered. In each sample there could be one or more subjects with atypical local anatomic characteristics (outliers) that are not identifiable a priori, thus leading to erroneous inferences about the specific structural features correlated to the studied pathology. It follows the need to evaluate the limits within which including a certain number of outliers can be accepted when relying on small samples. The robustness of VBM performed within SPM2 with respect to the inclusion of outliers was studied by implementing in MatLab sets of virtual phantoms with predetermined characteristics. A matrix of voxels cubes was superimposed on the preprocessed gray matter image of each scanned subject. Each cube has a uniform gray level, while its intensity distribution within each group is Gaussian with controlled group mean and variance. Variance and mean difference were chosen according to data from two ongoing clinical studies. The model implemented shows that applying VBM to small samples could lead to erroneous inferences. The minimum number of subjects should be evaluated according to specific variance and group mean difference values of the experimental samples. The implementation of virtual phantoms enabled the quantitative evaluation of outliers effects when performing VBM on small samples. This approach provides the clinicians with a support tool for evaluating the reliability of the results yielded by VBM analyses and for planning the recruiting process.

Keywords

VBM outliers phantoms SPM MRI 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Good C. D., Johnsrude I. S. et al. (2001) A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains. NeuroImage 14: 21–36CrossRefGoogle Scholar
  2. 2.
    Ashburner J., Friston K. J. (2000) Voxel-Based Morphometry — The Methods. NeuroImage 11: 805–821CrossRefGoogle Scholar
  3. 3.
    Mechelli A., Price C. J. et al. (2005) Voxel-Based Morphometry of the Human Brain: Methods and Applications. Current Medical Imaging Vol 1 n.1: 1–9CrossRefGoogle Scholar
  4. 4.
    Salmond C. H., Ashburner J. et al. (2002) Distributional Assumptions in Voxel-Based Morphometry. NeuroImage 17: 1027–1030CrossRefGoogle Scholar
  5. 5.
    Thacker N.A.(2003) Tutorial: A Critical Analysis of Voxel Based Morphometry. Imaging Science and Biomedical Engineering, University of Manchester. TiNA Memo No. 11Google Scholar
  6. 6.
    Senjem M. L., Gunter J. L. et al. (2005) Comparison of Different Methodological Implementations of Voxel-Based Morphometry in Neurodegenerative Disease. NeuroImage 26: 600–608CrossRefGoogle Scholar
  7. 7.
    Tzourio M., Landeau B. et al (2002) Automated Anatomical Labeling of Activations in SPM using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage Vol 15, N. 1: 273–289CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Federico Nocchi
    • 1
  • T. Franchin
    • 1
    • 4
  • E. Genovese
    • 2
  • D. Longo
    • 3
  • G. Fariello
    • 3
  • V. Cannatà
    • 2
  1. 1.“Bambino Gesù” Children’s HospitalRomeItaly
  2. 2.Department of Medical Physics“Bambino Gesù” Children’s HospitalRomeItaly
  3. 3.Department of Paediatric Radiology“Bambino Gesù” Children’s HospitalRomeItaly
  4. 4.Department of BioengineeringPolytechnic of MilanMilanItaly

Personalised recommendations