Towards comprehensive myelin assessment: combining multi-contrast quantitative MRI with spatially resolved lipodomics in the human brain

• Applicant: Dr. Ilona Lipp
• Subject Area: Medical Physics, Biomedical Technology ; Biochemistry
• Term: from 2020 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 446291874

The aim of this project is to establish matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) as a tool for the validation and development of quantitative MRI (qMRI) – based markers of myelin. Myelin is a lipid-rich substance that is crucial for healthy brain functioning. The study of myelin in vivo relies on qMRI. Various qMRI parameters are sensitive to myelination, but specificity can only be achieved by biophysical or data-driven modeling approaches. Both the development and validation of such models rely on reliable ‘ground-truth’ myelin maps from histology. Currently, staining intensity from classical histology or immunohistochemistry is frequently used as an approximation for tissue myelin content. In preliminary research, we have observed that different histological methods differ in the patterns of myelination they yield in the cortex. This difference is likely related to variability in myelin composition across different brain tissue types. Considering this composition is crucial in the context of qMRI, as different lipid species are known to differ in their MR properties. So far, relating lipidomics to qMRI has been limited to studies conducted with phantoms.Here, we want to exploit a method that can capture the biochemical composition of myelin in sections of human brain tissue: MALDI-MSI. Building upon previously collected pilot data, we will develop an optimized workflow for the acquisition and analysis of MALDI-MSI data. Hereby, we will tackle a number of methodological challenges related to lipid quantification with MALDI-MSI: identification of the lipids underlying most important peaks, calibration of the lipid maps through application of internal standards, clustering of the brain tissue based on its lipid composition, and the co-registration of lipid concentration maps with qMRI maps. We will address the following research questions: a) What is the best MALDI-MSI-derived metric for myelin quantification? b) How does the tissue lipid composition impact on different qMR parameters? d) Can tissue lipid composition be inferred from a combination of qMRI parameters? Diagnosis, patient stratification and treatment of demyelinating neurological diseases is constrained by a lack of tools to accurately quantify myelination in vivo. Currently available measures suffer from low specificity and can therefore not easily be compared across individuals or over time. This limits their interpretability in clinical studies and hinders their applicability to personalised medicine. The combination of qMRI data and lipidomics in human brain tissue sections is an important step towards meeting the need for reliable MR markers that are specific to tissue myelination. The data collected in this project will act as unique reference material for future efforts in establishing biophysical and data-driven models.

• DFG Programme: Research Grants