SNIPE: A New Method to Identify Imaging Biomarker for Early Detection of Alzheimers DiseaseReportar como inadecuado

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* Corresponding author 1 MNI - McConnell Brain Imaging Centre 2 LaBRI - Laboratoire Bordelais de Recherche en Informatique 3 Aarhus University Aarhus 4 ITACA 5 INCIA - Institut de Neurosciences cognitives et intégratives d-Aquitaine

Abstract : While the automatic detection of AD has been widely studied, the problem of the prediction of AD or its early detection has been less investigated. This might be explained by the fact that the prediction problem is clearly more challenging since the anatomical changes are more subtle. However, from a clinical point of view the prediction of AD is the key question since it is in that moment when treatment is possible. The potential use of structural MRI as imaging biomarker for Alzheimer-s disease AD for early detection has become generally accepted, especially the use of atrophy of entorhinal cortex EC and hippocampus HC. Therefore, in this study, we analyze the capabilities of the recently proposed method, SNIPE Scoring by Nonlocal Image Patch Estimator, for the early detection of AD to analyze EC and HC atrophy over the entire ADNI database 834 subjects. During validation, the detection AD vs. CN and the prediction pMCI vs. sMCI efficiency of SNIPE were studied. The obtained results showed that SNIPE obtained competitive or better results than HC volume, cortical thickness and TBM. Moreover, results indicated that MRI grading-based biomarkers are more relevant than volume-based biomarkers. Finally, the success rate obtained by SNIPE was 90% for detection AD vs. CN and 74% for prediction pMCI vs. sMCI.

Autor: Pierrick Coupé - Simon Eskildsen - José Manjón - Vladimir Fonov - Jens Pruessner - Michèle Allard - Louis Collins -



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