Artificial Intelligence Based Key Technique Developments for Hyperpolarized 13C MRI
Grant Data
Project Title
Artificial Intelligence Based Key Technique Developments for Hyperpolarized 13C MRI
Principal Investigator
Dr Cao, Peng
(Project Coordinator (PC))
Co-Investigator(s)
Professor Li Ye
(Co-Investigator)
Dr Chu Zhiqin
(Co-Investigator)
Duration
24
Start Date
2021-12-31
Amount
2436961
Conference Title
Artificial Intelligence Based Key Technique Developments for Hyperpolarized 13C MRI
Presentation Title
Keywords
Artificial Intelligence, Based Key Technique Developments, Hyperpolarized 13C MRI
Discipline
Imaging
HKU Project Code
MHP/070/20
Grant Type
Innovation and Technology Support Programme (Platform Project)
Funding Year
2021
Status
On-going
Objectives
Hyperpolarized 13C is a novel molecular imaging methodology that can enhance the MRI 13C signal by 1000-fold. Compared with the wildly used PET imaging, the hyperpolarized 13C tracer is not radioactive, showing great potential in clinical imaging applications. This study aims to develop a hyperpolarized 13C MRI preclinical and clinical experiment platform. This platform will include a 5T clinical MRI with a 13C multi-channel head coil and a 3T small animal MRI with a single-channel coil, as well as hyperpolarized 13C data acquisition and analysis software. Firstly, we will use the 3T small animal MRI platform for verifying the nano-diamond hyperpolarized 13C method in vivo. In the 5T clinical validation experiment, we will use the pig as an animal model to test the in vivo performance of the proposed method. For the large animal 13C MRI data acquisition and analysis software, we will also develop a deep learning-based 13C image reconstruction and 13C coil electromagnetic field analysis method. The application of deep learning will focus on improving the 13C imaging signal-to-noise ratio.