Robust Perfusion Imaging of the Moving Human Liver Using Arterial Spin Labeling MRI for Advanced Modelling of Liver Function

• Applicant: Dr. Daniel Christopher Hoinkiss
• Subject Area: Medical Physics, Biomedical Technology ; Radiology
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 508707144

Medical imaging methods to measure liver perfusion help radiologists in the early detection of primary and metastatic hepatic malignancies and cirrhosis, but also in the post-operative monitoring of liver transplants. The current state of the art in liver perfusion imaging using Magnetic Resonance Imaging (MRI) includes the intravenous injection of contrast agents which, as it was discovered during the last years, can accumulate in the brain. This shows the necessity to explore alternative, contrast-agent free MRI techniques for acquiring quantitative perfusion images of the liver. Arterial Spin Labeling (ASL) MRI, which has already been established in brain imaging, could meet these requirements. It is, however, highly susceptible to motion which is very prominent when measuring the abdomen due to breathing. In a previous DFG project (“ASLiver”) we developed solutions to allow ASL acquisition of the liver under free breathing. Although this preliminary project showed proof-of-principle developments of motion compensation in liver ASL that advance the state-of-the-art, there are many challenges ahead before using ASL as a robust measure for quantitative liver perfusion. In this comprehensive project proposal, the whole workflow of assessing quantitative perfusion, including the visualization of physiological exchange processes by extending the conventional one-compartment model for perfusion modelling by acquiring multi-TE data, will be revised and evaluated. This includes improvements to the ASL sequence itself to benefit from state-of-theart techniques for scan acceleration and segmentation and advancing the current state of background suppression and fat saturation. The final sequence will then be embedded into an automatic workflow covering reference scans and motion correction. This will allow acquisition of liver ASL images with high quality, enabling advances in modeling the physiological processes in the liver, still lacking gold standards today due to the complex liver anatomy. There are many challenges to solve as to how to correctly separate the signal of the two blood supplies, determine the labeling efficiency or make use of multi-TE data that could serve a whole new dimension by incorporating exchange processes into the modelling. This will provide new insights into the physiological processes in the liver without use of contrast agents or ionizing radiation and prepare the use of ASL in the liver for clinical use.

• DFG Programme: Research Grants
• Co-Investigator: Professor Dr. Matthias Günther