Quantification of the Volumetric Differences in Progressive Supranuclear Palsy and Corticobasal Dege

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Quantification of the Volumetric Differences in
Progressive Supranuclear Palsy and Corticobasal
Degeneration
Seniha E. Yuksel, Noha El-Zehiry, Irene Litvan,
Aly A. Farag
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Problem

• Progressive Supranuclear Palsy (PSP) and
  Corticobasal Degeneration (CBD) are two
  neurodegenerative parkinsonian disorders.
• Incidence and prevalence rates
• PSP 56.4 per 100,000 1, 2.
• No data on CBD 3.

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Both PSP and CBD

• Start around age 60
• Result in severe disability inability to move
• Current diagnosis depends on the presence and
  progression of clinical features
• Definite diagnosis of these diseases can only be
  made by neuropathological examination.
• Patients have about 5 years life span after
  diagnosis because of the inability to take care
  of themselves

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Our Objective

• Perform a 3D-MRI study to find a characteristic
  pattern of volume loss in brain structures such
  as
• total intracranial volume (TICV),
• total brain volume, brainstem
• midbrain, pons, medulla oblongata,
• cerebellum, corpus callosum,
• white and gray matters of all the lobes.

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Previous Studies

• The only quantitative study comparing PSP and CBD
  is by K. Groschel and I. Litvan et al. 4,
• In this study,
• In PSP patients, a reduction was found in
• average brain, brainstem, midbrain and frontal
  gray matter volumes
• In CBD patients, atrophy was found in
• parietal cortex and corpus callosum
• However, the results showed overlapping and did
  not exactly differentiate PSP and CBD.

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Our method

• More effective classification methods will be
  investigated.
• More advanced segmentation algorithms will be
  applied using the most current techniques.
• The effect of advanced segmentation techniques
  will be investigated by comparing the results to
  the previous studies by Groschel et al. 4
  using linear classifiers.

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General Framework
Brain stem
Cerebellum
Midbrain
Segmentation
Corpus Callosum
Gray Matter
Classification
White Matter
Total Volume

• Expectation Maximization
• Bayesian Classification
• Support Vector Machines
• Artificial Intelligence
• Fuzzy Logic

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References

• J.H. Bower, D.M. Maraganore, S.K. McDonnell, W.A.
  Rocca, Incidence of progressive supranuclear
  palsy and multiple system atrophy in Olmsted
  County, Minnesota, 1976 to 1990, Neurology,
  1997, vol. 49, pp. 12841288.
• Schrag, Y. Ben Shlomo, N.P. Quinn, Prevalence of
  progressive supranuclear palsy and multiple
  system atrophy a cross-sectional study, Lancet,
  1999, vol. 354, pp. 1771 1775.
• M. LeDoux, Animal models of movement disorders,
  Academic Press, Dec. 2004.
• K. Groschel, T.K. Hauser, A. Luft, N. Patronas,
  J. Dichgans, I. Litvan , J.B. Schulz, Magnetic
  resonance imaging-based volumetry differentiates
  progressive supranuclear palsy from corticobasal
  degeneration, Neuroimage, Feb 2004, vol. 21(2),
  pp. 714-24.