Hippocampal-amygdalo-ventricular atrophy score: Alzheimer disease detection using normative and pathological lifespan models.
MANJON, Jose V.
ITACA
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
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ITACA
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
MANJON, Jose V.
ITACA
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
ITACA
Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia [UPV]
TOURDIAS, Thomas
Neurocentre Magendie : Physiopathologie de la Plasticité Neuronale [U1215 Inserm - UB]
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Neurocentre Magendie : Physiopathologie de la Plasticité Neuronale [U1215 Inserm - UB]
Langue
EN
Article de revue
Ce document a été publié dans
Human Brain Mapping. 2022-07, vol. 43, n° 10, p. 3270-3282
Résumé en anglais
In this article, we present an innovative MRI-based method for Alzheimer disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. After a full screening of the ...Lire la suite >
In this article, we present an innovative MRI-based method for Alzheimer disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. After a full screening of the most discriminant structures between AD and normal aging based on MRI volumetric analysis of 3,032 subjects, we propose a novel Hippocampal-Amygdalo-Ventricular Atrophy score (HAVAs) based on normative lifespan models and AD lifespan models. During a validation on three external datasets on 1,039 subjects, our approach showed very accurate detection (AUC ≥ 94%) of patients with AD compared to control subjects and accurate discrimination (AUC = 78%) between progressive MCI and stable MCI (during a 3-year follow-up). Compared to normative modeling, classical machine learning methods and recent state-of-the-art deep learning methods, our method demonstrated better classification performance. Moreover, HAVAs simplicity makes it fully understandable and thus well-suited for clinical practice or future pharmaceutical trials.< Réduire
Mots clés en anglais
Alzheimer Disease
Atrophy
Cognitive Dysfunction
Disease Progression
Hippocampus
Humans
Longevity
Magnetic Resonance Imaging
Project ANR
Apprentissage profond pour la volumétrie cérébrale : vers le BigData en neuroscience
Translational Research and Advanced Imaging Laboratory
Initiative d'excellence de l'Université de Bordeaux - ANR-10-IDEX-0003
Translational Research and Advanced Imaging Laboratory
Initiative d'excellence de l'Université de Bordeaux - ANR-10-IDEX-0003