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Hum Brain Mapp. 2015 Dec;36(12):4758-70. doi: 10.1002/hbm.22926. Epub 2015 Oct 10.

Detection of Alzheimer's disease signature in MR images seven years before conversion to dementia: Toward an early individual prognosis.

Author information

1
Laboratoire Bordelais De Recherche En Informatique, Unité Mixte De Recherche CNRS (UMR 5800), PICTURA Research Group, Bordeaux, France.
2
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
3
University of Bordeaux, INCIA, UMR 5287, Talence, France.
4
CNRS, INCIA, UMR 5287, Talence, France.
5
École Pratique des Hautes Études, Bordeaux, France.
6
Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark.
7
INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France.
8
Département de Pharmacologie CHU de Bordeaux, University of Bordeaux, Bordeaux, France.
9
INSERM, CIC 14.01, Module EC, Bordeaux, France.
10
Instituto De Aplicaciones De Las Tecnologías De La Información Y De Las Comunicaciones Avanzadas (ITACA), Universitat Politècnica De València, Camino De Vera S/N, Valencia, 46022, Spain.
11
University Hospital, Memory Consultation, CMRR, Bordeaux, France.

Abstract

Finding very early biomarkers of Alzheimer's Disease (AD) to aid in individual prognosis is of major interest to accelerate the development of new therapies. Among the potential biomarkers, neurodegeneration measurements from MRI are considered as good candidates but have so far not been effective at the early stages of the pathology. Our objective is to investigate the efficiency of a new MR-based hippocampal grading score to detect incident dementia in cognitively intact patients. This new score is based on a pattern recognition strategy, providing a grading measure that reflects the similarity of the anatomical patterns of the subject under study with dataset composed of healthy subjects and patients with AD. Hippocampal grading was evaluated on subjects from the Three-City cohort, with a followup period of 12 years. Experiments demonstrate that hippocampal grading yields prediction accuracy up to 72.5% (P < 0.0001) 7 years before conversion to AD, better than both hippocampal volume (58.1%, P = 0.04) and MMSE score (56.9%, P = 0.08). The area under the ROC curve (AUC) supports the efficiency of imaging biomarkers with a gain of 8.4 percentage points for hippocampal grade (73.0%) over hippocampal volume (64.6%). Adaptation of the proposed framework to clinical score estimation is also presented. Compared with previous studies investigating new biomarkers for AD prediction over much shorter periods, the very long followup of the Three-City cohort demonstrates the important clinical potential of the proposed imaging biomarker. The high accuracy obtained with this new imaging biomarker paves the way for computer-based prognostic aides to help the clinician identify cognitively intact subjects that are at high risk to develop AD.

KEYWORDS:

Alzheimer; MRI biomarker; hippocampus

PMID:
26454259
DOI:
10.1002/hbm.22926
[Indexed for MEDLINE]
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