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3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
Published on: May 19, 2015
Computational anatomical methods as applied to ageing and dementia
1Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive, Los Angeles, CA 90095-1769, USA. thompson@loni.ucla.edu
The British Journal of Radiology
|May 1, 2008
Summary
Computational methods can map brain changes in Alzheimer's disease (AD) and mild cognitive impairment (MCI) years before symptoms appear. These techniques track disease progression and aid clinical trial development.
Area of Science:
- Neuroimaging
- Computational anatomy
- Neurology
Background:
- Cellular hallmarks of Alzheimer's disease (AD) manifest up to 30 years before clinical dementia symptoms.
- Distinguishing AD and mild cognitive impairment (MCI) brain changes from normal aging is challenging.
- Computational methods offer powerful tools for statistical analysis of subtle brain alterations.
Purpose of the Study:
- To review computational approaches for mapping brain deficits in AD, MCI, and dementia subtypes.
- To explore how these methods reveal disease dynamics and treatment effects.
- To identify computational tools suitable for tracking dementia progression in clinical trials.
Main Methods:
- Review of three computational approaches: cortical thickness mapping, tensor-based morphometry, and hippocampal/ventricular surface modeling.
- Mathematical modeling of anatomical structures as 3D surfaces for cross-subject comparisons.
- Application of concepts from computational surface modeling, fluid mechanics, and multivariate statistics.
Main Results:
- Computational methods can distinguish AD/MCI-related brain changes from normal aging.
- Mapping reveals disease spread, treatment impact, and correlations between brain changes and cognitive/behavioral symptoms.
- Specific cortical and hippocampal changes differentiate dementia subtypes and predict clinical outcomes.
Conclusions:
- Computational neuroimaging provides crucial insights into the early dynamics of AD and MCI.
- These advanced analytical techniques are essential for accurate diagnosis, subtype differentiation, and monitoring disease trajectory.
- The reviewed methods demonstrate potential for sensitive tracking of dementia progression in clinical trials.
