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Estimating local surface complexity maps using spherical harmonic reconstructions.

Rachel Aine Yotter1, Paul M Thompson, Igor Nenadic

  • 1Friedrich-Schiller University, Department of Psychiatry, Jahnstr. 3, 07743 Jena, Germany. Rachel.Yotter@uni-jena.de

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 1, 2010
PubMed
Summary
This summary is machine-generated.

Schizophrenia patients show reduced cortical surface complexity, particularly in the right prefrontal cortex. This fractal dimension (FD) measure may serve as a potential biomarker for the disease.

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Area of Science:

  • Neuroimaging
  • Computational anatomy
  • Psychiatric disorders

Background:

  • Cortical surface complexity is increasingly recognized as a potential neuroimaging biomarker.
  • Alterations in brain structure are associated with psychiatric conditions like schizophrenia.

Purpose of the Study:

  • To develop and apply a novel fractal dimension (FD) measure to quantify cortical surface complexity.
  • To investigate differences in brain surface complexity between individuals with schizophrenia and healthy controls.

Main Methods:

  • Computed global and local fractal dimension (FD) using lowpass-filtered spherical harmonic reconstructions of brain surfaces.
  • Analyzed cortical surface complexity in 87 schizophrenia patients and 108 matched healthy controls.

Main Results:

  • A significantly lower global FD was observed in the right hemisphere of patients with schizophrenia compared to controls.
  • Local FD analysis revealed that reduced complexity in schizophrenia was primarily localized to the prefrontal cortex.

Conclusions:

  • Fractal dimension analysis provides a sensitive measure of cortical surface complexity.
  • Reduced right hemisphere cortical complexity, especially in the prefrontal cortex, may represent a structural characteristic of schizophrenia.