Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification.
Sci Rep. 2019-09-25; 9(1):
DOI: 10.1038/s41598-019-49970-9
Lire sur PubMed
Hett K(1)(2)(3), Ta VT(4)(5)(6), Catheline G(7)(8), Tourdias T(9)(10)(11), Manjón JV(12), Coupé P(4)(5)(6); Alzheimer’s Disease Neuroimaging Initiative.
Author information:
(1)Univ. Bordeaux, LaBRI, UMR 5800, PICTURA, F-33400, Talence, France. .
(2)Bordeaux INP, LaBRI, UMR 5800, PICTURA, F-33405, Talence, France. .
(3)CNRS, LaBRI, UMR 5800, PICTURA, F-33400, Talence, France. .
(4)Univ. Bordeaux, LaBRI, UMR 5800, PICTURA, F-33400, Talence, France.
(5)Bordeaux INP, LaBRI, UMR 5800, PICTURA, F-33405, Talence, France.
(6)CNRS, LaBRI, UMR 5800, PICTURA, F-33400, Talence, France.
(7)Univ. Bordeaux, INCIA, UMR 5287, F-33400, Talence, France.
(8)CNRS, INCIA, UMR 5287, F-33400, Talence, France.
(9)CHU de Bordeaux, Service de neuroimagerie diagnostique et thérapeutique, F-33076, Bordeaux, France.
(10)Neurocentre Magendie, INSERM U1215, F-33077, Bordeaux, France.
(11)Univ. Bordeaux, F-33000, Bordeaux, France.
(12)Universitat Politècnia de València, ITACA, 46022, Valencia, Spain.
Numerous studies have proposed biomarkers based on magnetic resonance imaging
(MRI) to detect and predict the risk of evolution toward Alzheimer’s disease
(AD). Most of these methods have focused on the hippocampus, which is known to be
one of the earliest structures impacted by the disease. To date, patch-based
grading approaches provide among the best biomarkers based on the hippocampus.
However, this structure is complex and is divided into different subfields, not
equally impacted by AD. Former in-vivo imaging studies mainly investigated
structural alterations of these subfields using volumetric measurements and
microstructural modifications with mean diffusivity measurements. The aim of our
work is to improve the current classification performances based on the
hippocampus with a new multimodal patch-based framework combining structural and
diffusivity MRI. The combination of these two MRI modalities enables the capture
of subtle structural and microstructural alterations. Moreover, we propose to
study the efficiency of this new framework applied to the hippocampal subfields.
To this end, we compare the classification accuracy provided by the different
hippocampal subfields using volume, mean diffusivity, and our novel multimodal
patch-based grading framework combining structural and diffusion MRI. The
experiments conducted in this work show that our new multimodal patch-based
method applied to the whole hippocampus provides the most discriminating
biomarker for advanced AD detection while our new framework applied into
subiculum obtains the best results for AD prediction, improving by two percentage
points the accuracy compared to the whole hippocampus.