Detecting Dynamic (4D) Profiles of Degenerative Rates in Alzheimer's Disease Patients, Using High-Resolution Tensor Mapping and a Brain Atlas Encoding Atrophic Rates in a Population

Paul M. Thompson1, Greig de Zubicaray2, Andrew L. Janke2, Stephen E. Rose2, Stephanie Dittmer1, James Semple3, David Gravano1, Sue Han1, David Herman1, Michael S. Hong1, Michael S. Mega1, Jeffrey L. Cummings1, David M. Doddrell2, Arthur W. Toga1
1Laboratory of Neuro Imaging, Brain Mapping Division, and UCLA Alzheimer's Disease Center, Department of Neurology, UCLA School of Medicine
2Centre for Magnetic Resonance, University of Queensland, Brisbane 4072, Australia
3SmithKline Beecham Pharmaceuticals plc, UK

Mapping Degenerative Rates


Early detection and monitoring of Alzheimer’s Disease (AD) requires tools with unprecedented sensitivity for mapping its dynamic progression. We developed a dynamic brain atlas to store spatially complex profiles of degenerative rates and gray matter loss throughout the brain. Our goals were to (1) create detailed maps of degenerative change and (2) use high-dimensional flows [1] to compare individual patients' dynamic maps with probabilistic loss rate data in the atlas. We further aimed to define robust measures of change in AD and controls and assess how change rates in different systems are correlated.

A population-based brain atlas containing 6840 anatomical surface models [1] was created from 3D MRI (SPGR) scans of 43 AD patients (age: 68.7+/-1.7 yrs.; 24 females/19 males; MMSE score: 20.0+/-0.8) and 34 controls matched for age, education, gender and handedness (all right-handed). After affine alignment of individual data, gyral pattern and shape variations were encoded using high-dimensional elastic deformation mappings driving each subject’s cortical anatomy into a group average configuration [1]. Dynamic maps of atrophic rates, with millions of degrees of freedom, were then generated for 17 AD patients and 14 demographically-matched controls scanned repeatedly over a 4-year period (interscan interval: 2.6±0.3 yrs.; final age: 71.3±1.8 yrs.). To create maps of change, parametric surface models of cortical, hippocampal, ventricular, and callosal systems drove an elastic warping field reconfiguring the earlier scan’s anatomy onto the later one, and local volume loss was quantified. Annualized 4D maps of tissue loss rates within each subject were elastically realigned for averaging across diagnostic groups. Statistics of local loss rates were computed pointwise and visualized using color-coded maps.

Significant left faster than right hippocampal tissue loss was detected in controls (L:-3.8±1.6%/yr.; R:-0.5±1.2%/yr.; p<0.05). Even faster loss rates were found bilaterally in AD (L: -5.9%±1.7%/yr.; R:-7.1±3.2%/yr.; p<0.03 group difference; no asymmetry). In controls, loss rates peaked at a localized region of the medial surface of the left hippocampal head. In AD, an anterior to posterior shift was detected in the region of peak loss, which broadened to encompass the entire hippocampus, bilaterally. Local atrophic rates were significantly linked to the rate of MMSE decline (r=0.7; p<0.05), but not educational level (r<0.1). Rates of increase in the curvature [2] of the superior surface of the corpus callosum were significantly greater than zero in controls (p<0.05), significantly higher in AD (p<0.05), and strongly correlated with hippocampal loss rates in both AD and controls (pooled p<0.002 left, p<0.000004 right; r=0.54,0.73). In AD, greatest dynamic change rates were found in the inferior ventricular horns (L:+14.7+/-5.8%/yr.; R:+16.3+/-3.5%/yr.), with significant expansion rates bilaterally even in controls (L:+3.7+/-1.2%/yr.; R:+1.7+/-1.2%; p<0.001,p<0.01). Average maps of cortical gray matter loss also revealed a widespread left greater than right deficit in AD (p<0.05).

These disease-specific 4D brain atlasing systems are the first to store information on degenerative rates in a population, and may help to chart disease progression in genetic, demographic, and drug studies of dementia.

References: [1]. Thompson et al.: Cerebral Cortex 11:1-16(2001). [2]. J. Neurosci. 16(13):4261-4274(1996).

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    Paul Thompson, Ph.D.
    Assistant Professor of Neurology
    4238 Reed Neurology
    UCLA School of Medicine
    710 Westwood Plaza
    Westwood, Los Angeles CA 90095-1769, USA.

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