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Article Dans Une Revue Human Brain Mapping Année : 2022

HAVAs : Alzheimer disease detection using normative and pathological lifespan models

Résumé

In this paper, we present an innovative MRI-based method for Alzheimer's 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 3032 subjects, we propose a novel Hippocampal-Amygdalo-Ventricular Alzheimer score (HAVAs) based on normative lifespan models and AD lifespan models. During a validation on three external datasets on 1039 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 years follow-up). Compared to normative modelling, 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.
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Dates et versions

hal-03693875 , version 1 (13-06-2022)

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Pierrick Coupé, José V. Manjón, Boris Mansencal, Thomas Tourdias, Gwénaëlle Catheline, et al.. HAVAs : Alzheimer disease detection using normative and pathological lifespan models. Human Brain Mapping, 2022, ⟨10.1002/hbm.25850⟩. ⟨hal-03693875⟩
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