scholarly journals P3-361: EXPLAINABLE CONVOLUTIONAL NETWORKS AND MULTIMODAL IMAGING DATA: THE NEXT STEP TOWARDS USING ARTIFICIAL INTELLIGENCE AS DIAGNOSTIC TOOL FOR EARLY DETECTION OF ALZHEIMER'S DISEASE

2019 ◽  
Vol 15 ◽  
pp. P1083-P1084 ◽  
Author(s):  
Eman N. Marzban ◽  
Stefan J. Teipel ◽  
Katharina Buerger ◽  
Klaus Fliessbach ◽  
Michael T. Heneka ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Diagnostic Tool ◽  
Multimodal Imaging ◽  
Imaging Data ◽  
Convolutional Networks

scholarly journals Multimodal imaging in Alzheimer's disease: validity and usefulness for early detection

2015 ◽  
Vol 14 (10) ◽  
pp. 1037-1053 ◽  
Author(s):  
Stefan Teipel ◽  
Alexander Drzezga ◽  
Michel J Grothe ◽  
Henryk Barthel ◽  
Gaël Chételat ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Multimodal Imaging

scholarly journals Application of Artificial Intelligence in the Prevention, Diagnosis and Treatment of Alzheimer’s Disease: New Hope for Dealing with Aging in China

2021 ◽  
Author(s):  
Hangtian Wang ◽  
Guofu Wang
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Treatment Outcomes ◽  
Recent Progress ◽  
Diagnosis And Treatment ◽  
Cochrane Library ◽  
Poor Treatment ◽  
The Cochrane Library

Alzheimer’s disease (AD) has become a major issue around world, including China. The two major challenges for AD are the difficulty in early detection and poor treatment outcomes. Over the past decades, artificial intelligence (AI) was more and more widely used in the prevention, diagnosis and treatment of AD, which might be helpful to deal with the aging of population in China. Here, after a systematic literature searching on three English databases (MEDLINE, EMBASE, the Cochrane library), we briefly reviewed recent progress on the utilization of AI in the susceptibility analysis, diagnosis and management of AD. However, it is still in its infancy. More researches should be performed to improve the prognosis of patients with AD in the future.

Retinal multimodal imaging for identification of novel biomarkers for early detection of Alzheimer's disease (Conference Presentation)

2019 ◽  
Author(s):  
Ygal Rotenstreich ◽  
Inbal Sharvit-Ginon ◽  
Michal Schnaider Beeri ◽  
Ramit Ravona-Springer ◽  
Ido Fabian ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Multimodal Imaging ◽  
Novel Biomarkers

[18F]-florbetaben PET/CT Imaging in the Alzheimer’s Disease Mouse Model APPswe/PS1dE9

2018 ◽  
Vol 16 (1) ◽  
pp. 49-55 ◽  
Author(s):  
J. Stenzel ◽  
C. Rühlmann ◽  
T. Lindner ◽  
S. Polei ◽  
S. Teipel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mouse Model ◽  
New Drugs ◽  
Imaging Data ◽  
Wild Type ◽  
Preclinical Research ◽  
Standardized Uptake Values ◽  
Pet Ct

Background: Positron-emission-tomography (PET) using 18F labeled florbetaben allows noninvasive in vivo-assessment of amyloid-beta (Aβ), a pathological hallmark of Alzheimer’s disease (AD). In preclinical research, [<sup>18</sup>F]-florbetaben-PET has already been used to test the amyloid-lowering potential of new drugs, both in humans and in transgenic models of cerebral amyloidosis. The aim of this study was to characterize the spatial pattern of cerebral uptake of [<sup>18</sup>F]-florbetaben in the APPswe/ PS1dE9 mouse model of AD in comparison to histologically determined number and size of cerebral Aβ plaques. Methods: Both, APPswe/PS1dE9 and wild type mice at an age of 12 months were investigated by smallanimal PET/CT after intravenous injection of [<sup>18</sup>F]-florbetaben. High-resolution magnetic resonance imaging data were used for quantification of the PET data by volume of interest analysis. The standardized uptake values (SUVs) of [<sup>18</sup>F]-florbetaben in vivo as well as post mortem cerebral Aβ plaque load in cortex, hippocampus and cerebellum were analyzed. Results: Visual inspection and SUVs revealed an increased cerebral uptake of [<sup>18</sup>F]-florbetaben in APPswe/ PS1dE9 mice compared with wild type mice especially in the cortex, the hippocampus and the cerebellum. However, SUV ratios (SUVRs) relative to cerebellum revealed only significant differences in the hippocampus between the APPswe/PS1dE9 and wild type mice but not in cortex; this differential effect may reflect the lower plaque area in the cortex than in the hippocampus as found in the histological analysis. Conclusion: The findings suggest that histopathological characteristics of Aβ plaque size and spatial distribution can be depicted in vivo using [<sup>18</sup>F]-florbetaben in the APPswe/PS1dE9 mouse model.

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