Advertisement

Simulation of Local and Global Atrophy in Alzheimer’s Disease Studies

  • Oscar Camara-Rey
  • Martin Schweiger
  • Rachael I. Scahill
  • William R. Crum
  • Julia A. Schnabel
  • Derek L. G. Hill
  • Nick C. Fox
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

We propose a method for atrophy simulation in structural MR images based on finite-element methods, providing data for objective evaluation of atrophy measurement techniques. The modelling of diffuse global and regional atrophy is based on volumetric measurements from patients with known disease and guided by clinical knowledge of the relative pathological involvement of regions. The consequent biomechanical readjustment of structures is modelled using conventional physics-based techniques based on tissue properties and simulating plausible deformations with finite-element methods. Tissue characterization is performed by means of the meshing of a labelled brain atlas, creating a reference volumetric mesh, and a partial volume tissue model is used to reduce the impact of the mesh discretization. An example of simulated data is shown and a visual evaluation protocol used by experts has been developed to assess the degree of realism of the simulated images. First results demonstrate the potential of the proposed methodology.

Keywords

Simulated Image Regional Atrophy Entorhinal Area Magnetic Resonance Imaging Brain Scan Global Atrophy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Ashburner, J., Csernansky, J., Davatzikos, C., Fox, N., et al.: Computer-assisted imaging to assess brain structure in healthy and diseased brains. Lancet Neurology 2, 79–88 (2003)CrossRefGoogle Scholar
  2. 2.
    Lao, Z., Shen, D., Xue, Z., Karacali, B., et al.: Morphological classification of brains via high-dimensional shape transformations and machine learning methods. Neuroimage 21, 46–57 (2004)CrossRefGoogle Scholar
  3. 3.
    Chen, K., Reiman, E., Alexander, G., Bandy, D., et al.: An automated algorithm for the computation of brain volume change from sequential MRIs using an iterative principal component analysis and its evaluation for the assessment of whole-brain atrophy rates in patients with probable Alzheimer’s disease. Neuroimage 22, 134–143 (2004)CrossRefGoogle Scholar
  4. 4.
    Xue, Z., Shen, D., Davatzikos, C.: CLASSIC: Consistent Longitudinal Alignment and Segmentation for Serial Image Computing. Neuroimage 21, 46–57 (2005)Google Scholar
  5. 5.
    Schnabel, J., Tanner, C., Castellano-Smith, A., Leach, M., et al.: Validation of Non-Rigid Registration using Finite Element Methods. In: Insana, M.F., Leahy, R.M. (eds.) IPMI 2001. LNCS, vol. 2082, pp. 183–189. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  6. 6.
    Freeborough, P., Fox, N., Kitney, R.: Interactive algorithms for the segmentation and quantitation of 3-D MRI brain scans. Computer Methods and Programs in Biomedicine 53, 15–25 (1997)CrossRefGoogle Scholar
  7. 7.
    Lorensen, W., Cline, H.: Marching cube, a high resolution 3D surface reconstruction algorithm. In: International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH 1987), vol. 21, pp. 163–169 (1987)Google Scholar
  8. 8.
    Sermesant, M., Forest, C., Pennec, X., Delingette, H., et al.: Deformable biomechanical models: Application to 4D cardiac image analysis. Medical Image Analysis 7, 475–488 (2003)CrossRefGoogle Scholar
  9. 9.
    McCracken, P., Manduca, A., Felmlee, J., Ehman, R.: Mechanical Transient-Based Magnetic Resonance Elastography. Magnetic Resonance in Medicine 53, 628–639 (2005)CrossRefGoogle Scholar
  10. 10.
    Davies, A.J.: The Finite Element Method: A First Approach. Oxford University Press, Oxford (1980)zbMATHGoogle Scholar
  11. 11.
    Jack Jr., C., Shiung, M., Gunter, J., O’Brien, P., et al.: Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology 62, 591–600 (2004)Google Scholar
  12. 12.
    Schott, J., Price, S., Frost, C., Whitwell, J., et al.: Measuring atrophy in Alzheimer disease: A serial MRI study over 6 and 12 months. Neurology 52, 1687–1689 (1999)Google Scholar
  13. 13.
    Camara, O., Crum, W., Schnabel, J., Lewis, E., Schweiger, M., Hill, D., Fox, N.: Assessing the quality of Mesh-Warping in normal and abnormal neuroanatomy. In: Medical Image Understanding and Analysis (MIUA 2005) (in press)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Oscar Camara-Rey
    • 1
  • Martin Schweiger
    • 1
  • Rachael I. Scahill
    • 2
  • William R. Crum
    • 1
  • Julia A. Schnabel
    • 1
  • Derek L. G. Hill
    • 1
  • Nick C. Fox
    • 2
  1. 1.Center of Medical Image ComputingUnviersity College of LondonUK
  2. 2.Dementia Research Centre, Institute of NeurologyUniversity College of LondonUK

Personalised recommendations