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Biomed Opt Express. 2019 May 28;10(6):3041-3060. doi: 10.1364/BOE.10.003041. eCollection 2019 Jun 1.

Supervised learning to quantify amyloidosis in whole brains of an Alzheimer's disease mouse model acquired with optical projection tomography.

Author information

1
Laboratory of Nanoscale Biology, École Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland.
2
Medical Image Processing Lab, École Polytechnique Fédérale de Lausanne, Genève, Genève, Switzerland.
3
Laboratoire d'Optique Biomédicale, École Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland.
4
Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland.
5
European Bioinformatics Institute, EMBL-EBI, Cambridge, United Kingdom.
6
Department of Radiology and Medical Informatics, University of Geneva, Genève, Genève, Switzerland.

Abstract

Alzheimer's disease (AD) is characterized by amyloidosis of brain tissues. This phenomenon is studied with genetically-modified mouse models. We propose a method to quantify amyloidosis in whole 5xFAD mouse brains, a model of AD. We use optical projection tomography (OPT) and a random forest voxel classifier to segment and measure amyloid plaques. We validate our method in a preliminary cross-sectional study, where we measure 6136 ± 1637, 8477 ± 3438, and 17267 ± 4241 plaques (AVG ± SD) at 11, 17, and 31 weeks. Overall, this method can be used in the evaluation of new treatments against AD.

Conflict of interest statement

The authors declare that there are no conflicts of interest related to this article.

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