Paul Thompson's Research Publications

Early Cortical Change in Alzheimer's Disease
Detected with a Disease-Specific, Population-Based, Probabilistic Brain Atlas

Annual Meeting of the American Academy of Neurology, 2000 [submitted]

Thompson PM, Mega MS, Woods RP, Zoumalan CI, Lindshield CJ, Blanton RE, Moussai J, Holmes CJ, Dinov ID, Toga AW

Laboratory of Neuro Imaging, Dept. Neurology, Division of Brain Mapping,
UCLA School of Medicine, Los Angeles CA 90095, USA,

and

UCLA Alzheimer's Disease Center

  • (Paul's Platform Talk)

  • (Images of the Alzheimer's Disease Brain Atlas)


    ABSTRACT


    Objective. We report the first, detailed, population-based maps of early gray matter loss across the cortex in Alzheimer's Disease, detected with a disease-specific imaging atlas that stores information on anatomic variability and reflects the unique anatomy of an Alzheimer's Disease population.

    Background. To detect early disease-specific change, assist diagnosis and evaluate therapeutic response in an individual patient or clinical group, spatially-detailed maps of atrophy and gray matter loss are invaluable. To distinguish abnormalities from normal variants, a realistically complex mathematical framework is required to encode information on anatomic variability and gray matter distribution in large populations.

    Design/Methods. High-resolution 3D (256x256x124 resolution) T1-weighted MRI volumes were acquired from 26 Alzheimer's patients (age: 75.81.7 yrs.), and 20 normal elderly controls matched for age (70.93.9 yrs.), sex, handedness and educational level. 84 structures per brain were modeled in all 46 subjects using parametric 3D surface meshes (16 deep sulcal, callosal and hippocampal surfaces, all primary sulci, Sylvian fissures, 14 ventricular regions, and 36 gyral and 3D cytoarchitectural boundaries). High-dimensional elastic transformations reconfigured the anatomy of patients and controls into a mean anatomic configuration, controlling for, and locally encoding, gyral pattern variations. A crisp, disease-specific anatomic image template was created with highly-resolved structures in their mean spatial location. Statistical variations in cortical patterning, asymmetry, atrophy, and gray matter distribution were encoded as a non-stationary Gaussian random tensor field, and used to detect disease-specific differences in individual patients and across clinical groups. Several new types of anatomical maps were created, including detailed spatial maps of average gray matter loss in early AD.

    Results. Population-based statistical maps of average gray matter distribution revealed left greater than right hemisphere gray matter loss, with sharp contrasts between heteromodal and idiotypic cortex. Severe bilateral tissue loss in temporo-parietal association cortices was clearly demarcated from adjacent, comparatively spared sensorimotor and occipital cortices, in a pattern consistent with the cognitive, metabolic and histologic changes early in the disease. In controls, population-based averaging revealed principal directions of gyral pattern variability that demarcated functionally distinct cortical zones. By encoding variations in gyral patterns and tissue distribution, atrophic patterns and gray matter loss were mapped in individual patients and across groups.

    Conclusions. Using a new strategy to generate a population-based, AD-specific brain atlas, disease-specific features, patterns of tissue loss, and asymmetries were localized cortically and subcortically. Comparison of imaging data with a population-based normative atlas holds enormous promise in evaluating therapeutic response in an individual or group, and in uncovering disease-specific patterns not apparent in individual patients' scans.

    Grant Support. This work was supported by a Human Brain Project Grant to the International Consortium for Brain Mapping, funded jointly by NIMH and NIDA (P20 MH/DA52176), by a P41 Resource Grant from the NCRR (RR13642), by NINCDS Grant K08-NS01646, NIA Grant K08-AG100784, and research grants from the National Library of Medicine (LM/MH05639), the National Science Foundation (BIR93-22434), the NCRR (RR05956) and NINCDS/NIMH (NS38753).

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    Contact Information

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    Paul Thompson, Ph.D.
    Assistant Professor of Neurology
    UCLA Lab of Neuro-Imaging and Brain Mapping Division
    Dept. Neurology and Brain Research Institute
    4238 Reed Neurology, UCLA Medical Center
    710 Westwood Plaza
    Westwood, Los Angeles CA 90095-1769, USA.

  • E-mail: thompson@loni.usc.edu
  • Tel: (310)206-2101
  • Fax: (310)206-5518


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