Mapping hippocampal and ventricular change in Alzheimer disease.

Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
NeuroImage (Impact Factor: 6.13). 09/2004; 22(4):1754-66. DOI: 10.1016/j.neuroimage.2004.03.040
Source: PubMed

ABSTRACT We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Cortical thickness estimation in magnetic resonance imaging (MRI) is an important technique for research on brain development and neurodegenerative diseases. This paper presents a heat kernel based cortical thickness estimation algorithm, which is driven by the graph spectrum and the heat kernel theory, to capture the gray matter geometry information from the in vivo brain magnetic resonance (MR) images. First, we construct a tetrahedral mesh that matches the MR images and reflects the inherent geometric characteristics. Second, the harmonic field is computed by the volumetric Laplace-Beltrami operator and the direction of the steamline is obtained by tracing the maximum heat transfer probability based on the heat kernel diffusion. Thereby we can calculate the cortical thickness information between the point on the pial and white matter surfaces. The new method relies on intrinsic brain geometry structure and the computation is robust and accurate. To validate our algorithm, we apply it to study the thickness differences associated with Alzheimer's disease (AD) and mild cognitive impairment (MCI) on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Our preliminary experimental results on 151 subjects (51 AD, 45 MCI, 55 controls) show that the new algorithm may successfully detect statistically significant difference among patients of AD, MCI and healthy control subjects. Our computational framework is efficient and very general. It has the potential to be used for thickness estimation on any biological structures with clearly defined inner and outer surfaces. Copyright © 2015 Elsevier B.V. All rights reserved.
    Medical Image Analysis 02/2015; 22(1). DOI:10.1016/ · 3.68 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: On average, the human hippocampus shows structural differences between meditators and non-meditators as well as between men and women. However, there is a lack of research exploring possible sex effects on hippocampal anatomy in the framework of meditation. Thus, we obtained high-resolution magnetic resonance imaging data from 30 long-term meditation practitioners (15 men/15 women) and 30 well-matched control subjects (15 men/15 women) to assess if hippocampus-specific effects manifest differently in male and female brains. Hippocampal dimensions were enlarged both in male and in female meditators when compared to sex- and age-matched controls. However, meditation effects differed between men and women in magnitude, laterality, and location on the hippocampal surface. Such sex-divergent findings may be due to genetic (innate) or acquired differences between male and female brains in the areas involved in meditation and/or suggest that male and female hippocampi are differently receptive to mindfulness practices.
    Frontiers in Psychology 03/2015; 6:186. DOI:10.3389/fpsyg.2015.00186 · 2.80 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Impaired structure and function of the hippocampus is a valuable predictor of progression from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD). As a part of the medial temporal lobe memory system, the hippocampus is one of the brain regions affected earliest by AD neuropathology, and shows progressive degeneration as aMCI progresses to AD. Currently, no validated biomarkers can precisely predict the conversion from aMCI to AD. Therefore, there is a great need of sensitive tools for the early detection of AD progression. In this review, we summarize the specific structural and functional changes in the hippocampus from recent aMCI studies using neurophysiological and neuroimaging data. We suggest that a combination of advanced multi-modal neuroimaging measures in discovering biomarkers will provide more precise and sensitive measures of hippocampal changes than using only one of them. These will potentially affect early diagnosis and disease-modifying treatments. We propose a new sequential and progressive framework in which the impairment spreads from the integrity of fibers to volume and then to function in hippocampal subregions. Meanwhile, this is likely to be accompanied by progressive impairment of behavioral and neuropsychological performance in the progression of aMCI to AD.
    Neuroscience Bulletin 01/2015; 31(1). DOI:10.1007/s12264-014-1490-8 · 1.83 Impact Factor

Full-text (2 Sources)

Available from
Jun 1, 2014