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Related Experiment Videos

Anatomic validation of spatial normalization methods for PET.

M Sugiura1, R Kawashima, N Sadato

  • 1Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.

Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|February 20, 1999
PubMed
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Statistical Parametric Mapping (SPM) 95 and Human Brain Atlas (HBA) offer effective spatial normalization for PET studies. Nonlinear transformations are crucial for precise brain normalization, outperforming linear methods.

Area of Science:

  • Neuroimaging
  • Medical Physics
  • Radiology

Background:

  • Spatial normalization is essential for intersubject analysis in Positron Emission Tomography (PET) studies.
  • Evaluating the anatomical precision of spatial normalization methods is critical due to the close relationship between brain function and morphology.
  • Current methods require validation for their anatomical accuracy in normalizing functional images.

Purpose of the Study:

  • To validate the anatomical precision of three different spatial normalization methods.
  • To compare the performance of linear normalization, Human Brain Atlas (HBA), and Statistical Parametric Mapping (SPM) 95.
  • To assess the accuracy of brain normalization in PET studies.

Main Methods:

  • Four PET centers in Japan participated, recruiting normal subjects for H2(15)O-PET and high-resolution MRI.

Related Experiment Videos

  • Spatial normalization was performed using three methods: linear transformation, Human Brain Atlas (HBA), and Statistical Parametric Mapping (SPM) 95.
  • Variations in the anterior commissure (AC) location, brain size/contours, and major sulci courses were measured on normalized MR images.

    • Main Results:

    • All methods achieved good registration of the anterior commissure (AC).
    • Statistical Parametric Mapping (SPM) 95 demonstrated significant superiority over the linear method in aligning major sulci.
    • The linear method showed greater variance in brain contours, while SPM95 exhibited greater variation in brain size.

    Conclusions:

    • Statistical Parametric Mapping (SPM) 95 is as effective as Human Brain Atlas (HBA) for spatial normalization, despite not using anatomical images.
    • Nonlinear transformations are necessary for effective spatial normalization, as indicated by the linear method's limitations.
    • Operator dependency is a consideration for the Human Brain Atlas (HBA) method.