Abstract
Identifying mild cognitive impairment (MCI) subjects who will convert to clinical Alzheimer’s disease (AD) is important for therapeutic decisions, patient counselling and clinical trials. Hippocampal volume and rate of atrophy predict clinical decline at the MCI stage and progression to AD. In this paper, we create p-maps from the differences in the shape of the hippocampus between 60 normal controls and 60 AD subjects using statistical shape models, and generate different regions of interest (ROI) by thresholding the p-maps at different significance levels. We demonstrate increased statistical power to classify 86 MCI converters and 128 MCI stable subjects using the hippocampal atrophy rates calculated by the boundary shift integral within these ROIs.
This work was undertaken at UCL/UCLH which received a proportion of funding from the Department of Health’s NIHR Biomedical Research Centres funding scheme. The Dementia Research Centre is an Alzheimer’s Research Trust Co-ordinating centre. KKL and MC are supported by TSB grant M1638A, NCF is funded by the Medical Research Council (UK). JB is supported by an Alzheimer’s Research Trust (ART, UK) Research Fellowship partly supported by the Kirby Laing Foundation.
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Keywords
- Mild Cognitive Impairment
- Hippocampal Volume
- Hippocampal Atrophy
- Statistical Shape Model
- Mild Cognitive Impairment Subject
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Leung, K.K. et al. (2010). Increasing Power to Predict Mild Cognitive Impairment Conversion to Alzheimer’s Disease Using Hippocampal Atrophy Rate and Statistical Shape Models. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. MICCAI 2010. Lecture Notes in Computer Science, vol 6362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15745-5_16
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DOI: https://doi.org/10.1007/978-3-642-15745-5_16
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