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A new method for the in vivo volumetric measurement of the human hippocampus with high neuroanatomical accuracy.

Accurate and reproducible in vivo measurement of hippocampal volumes using magnetic resonance (MR) imaging is complicated by the morphological complexity of the structure. Additionally, separation of certain parts of the hippocampus from the adjacent brain structures on MR images is sometimes very difficult. These difficulties have led most investigators to either use arbitrary landmarks or to exclude certain parts of the structure from their measurements. Based on three-dimensional MR data, we have developed a reliable in vivo volumetric measurement of the human hippocampus. In contrast to most of the previously described volumetric MR-based methods, we aimed to sample the entire hippocampal formation using its true anatomical definition. This was accomplished by relying on the capacity of the BRAINS software to simultaneously visualize in multiple planes, to "telegraph" tracings or cursor position from one plane to another, and to simultaneously rely on multispectral data from three different image sets (T1, T2, and tissue classified). The methods for identifying boundaries and measuring the hippocampal volume are described. The method has excellent reliability, sensitivity, and specificity. The method may be of use in studies of structure-function relationships in neuropsychiatric disorders such as schizophrenia, temporal lobe epilepsy, and Alzheimer's disease. Future work will use these measurements as training data for a neural net-based technique to identify the anatomical boundaries automatically.

Pubmed ID: 11153720

Authors

  • Pantel J
  • O'Leary DS
  • Cretsinger K
  • Bockholt HJ
  • Keefe H
  • Magnotta VA
  • Andreasen NC

Journal

Hippocampus

Publication Data

January 10, 2000

Associated Grants

None

Mesh Terms

  • Adolescent
  • Adult
  • Female
  • Hippocampus
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Software