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Metabolic MRI at Ultra-High Fields — From Systems Architecture to Application

September 9, 2022

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Host: Dr. Erin MacMillan
Speaker: Dr. Anke Henning, University of Texas

Metabolic MRI allows observing energy metabolism, neurotransmission, second messaging, endocrine signaling, antioxidants, protein metabolism and dynamic membrane processes in the human brain. Related quantitative metabolic imaging biomarkers are beneficial for differential diagnostics, monitoring of treatment response and patient stratification in various neurological and psychiatric disorders and yield complementary information to structural and functional imaging. To visualize related metabolic processes my research group develops methodology for highly spatially and temporally resolved metabolic imaging exploiting magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST) and non-proton spectroscopic imaging (31P, 13C, 2H) at 3T, 7T and 9.4T with application in the human brain, spinal cord and myocardium. These methods allows for non-invasive and non-ionizing determination of tissue concentrations and metabolic turn-over rates of more than 20 metabolites and ions and specifically benefits from ultrahigh field strength with regard to spectral resolution and signal-to-noise ratio.

However, specific physical and technical challenges have to be overcome to fully exploit the advantages of ultrahigh field MR at 7T and 9.4T for human MRI and MRS. Hence my laboratory invests into the development of enabling technology for ultrahigh field MRI including scan hardware such as radiofrequency coils and static magnetic field shimming, numerical optimization of these setups and is able to perform respective safety assessment to allow for application in humans. The lab also develops scan software including MRI sequences and is able to design tailored radiofrequency pulse including such dedicated to parallel transmission systems. Specifically for metabolic MRI we also develop tailored data analysis methods such as image reconstruction, post-processing and quantification pipelines and recently started to explore machine-learning based approaches.

This presentation gives an overview over our recent research activities.

Zoom option if unable to attend in person

  • Zoom link here (click on “Join a meeting”)
  • Meeting ID: 99412 188589
  • Passcode: 188589


September 9
11:00 am - 12:00 pm


Rudy North Lecture Theatre, Djavad Mowafaghian Centre for Brain Health & Online
2215 Wesbrook Mall
Vancouver, BC V6T 1Z3 Canada


Djavad Mowafaghian Centre for Brain Health