Serveur d'exploration sur les relations entre la France et l'Australie

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Increasing Power to Predict Mild Cognitive Impairment Conversion to Alzheimer’s Disease Using Hippocampal Atrophy Rate and Statistical Shape Models

Identifieur interne : 007262 ( Main/Exploration ); précédent : 007261; suivant : 007263

Increasing Power to Predict Mild Cognitive Impairment Conversion to Alzheimer’s Disease Using Hippocampal Atrophy Rate and Statistical Shape Models

Auteurs : Kelvin K. Leung [Royaume-Uni] ; Kai-Kai Shen [Australie, France] ; Josephine Barnes [Royaume-Uni] ; Gerard R. Ridgway [Royaume-Uni] ; Matthew J. Clarkson [Royaume-Uni] ; Jurgen Fripp [Australie] ; Olivier Salvado [Australie] ; Fabrice Meriaudeau [France] ; Nick C. Fox [Royaume-Uni] ; Pierrick Bourgeat [Australie] ; Sébastien Ourselin [Royaume-Uni]

Source :

RBID : ISTEX:223B88570996CDF4E0206C6323DE3E49C0E6BF61

English descriptors

Abstract

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.

Url:
DOI: 10.1007/978-3-642-15745-5_16


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">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.</div>
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