Abstract #3707

CEST and AREX data processing based on deep neural network: application to image Alzheimer’s disease at 3T

Jianpan Huang¹, Joseph H. C. Lai¹, Kai-Hei Tse², Gerald W.Y. Cheng², Xiongqi Han¹, Yang Liu¹, Zilin Chen¹, Lin Chen^3,4, Jiadi Xu^3,4, and Kannie W. Y. Chan^1,4,5

¹Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China, ²Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China, ³F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States, ⁴Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁵City University of Hong Kong Shenzhen Research Institute, Shenzhen, China

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a promising molecular imaging technology. Apparent exchange-dependent relaxation (AREX) provides CEST contrast with less influence of T₁. Here, deep neural network based CEST/AREX analysis methods (CESTNet/AREXNet) were applied to analyze the CEST data of normal and AD mouse brains at 3T. Significant lower amide proton transfer/magnetization transfer (APT/MT) signals related to amyloid β-peptide (Aβ) plaque depositions, which were validated by immunohistochemistry results, were detected in Alzheimer’s disease (AD) mouse brains compared to age-matched wild type (WT) mouse brains. The well-established CESTNet/AREXNet have great potential to facilitate AD identification at 3T.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.