The role of tissue anisotropy in quantitative MRI of the human brain

Background: In recent years, the sensitivity of magnetic resonance imaging (MRI) could be dramatically increased and now in principle enables high-resolution quantitative imaging in clinically feasible scan times. In the future, MRI will therefore transform from a mere camera yielding qualitative images to a quantitative instrument that can map tissue composition. However, robust mapping of the human brain tissue structure is currently impaired, because it was observed that the MRI signal also depends on the orientation of the nerve fibers relative to the direction of the main magnetic field of the MRI system. Problematically, this anisotropy was shown to be of similar magnitude as disease-related alterations. Furthermore, it is only poorly understood how tissue composition and anisotropy influence quantitative MRI (qMRI) investigations. These limitations therefore represent major barriers for qMRI becoming a clinically applied tool. Based on the findings of our preliminary work, the proposed project aims on closing these knowledge gaps by combining post mortem in situ, ex situ and in vivo examinations, as well as histological and biochemical assessments in order to elucidate the origin of anisotropy in qMRI and to foster the translation of qMRI into clinics.

Methods: Post mortem in situ subjects, in vivo calibration subjects, in vivo volunteers, patients with aceruloplasminemia and patients with multiple sclerosis will be included in this collaborative study performed at the sites Basel, Switzerland and Innsbruck, Austria. After post mortem in situ MRI, the brains will be extracted and examined ex situ. Different ex situ experiments will be performed to compare qMRI anisotropy indices calculated by actually rotating the brain with estimating the fiber angle using diffusion tensor imaging (DTI) and advanced diffusion modeling. Furthermore, specific experiments are planned to study qMRI anisotropy related to paramagnetic and diamagnetic tissue components. Additionally, histological, biochemical and molecular analyses will be performed to assess tissue composition in specific brain regions. This will allow to correlate qMRI anisotropy with tissue components, such as iron and myelin content, as well as specific lipids and proteins. Linear mixed models and principal component analysis will be applied to identify connections between the multiple parameters. Possible multi-center bias will be detected based on calibration examinations with traveling volunteers. The volunteers and patients will be scanned at two field strengths to detect B₀ dependent susceptibility contributions and disease related effects on qMRI anisotropy. Disease related effects on the anisotropy will be studied in both patient groups for evaluating the use of the anisotropy as clinical biomarker.

Expected results: We expect to observe differences in anisotropy indices between all acquired qMRI parameters and to confirm the validity of estimating qMRI anisotropy using DTI and advanced diffusion modeling. By separating quantitative MRI parameters into paramagnetic and diamagnetic components, we expect to observe increased anisotropy indices related to the diamagnetic tissue components, such as lipids and proteins. In addition, we anticipate that the anisotropy will differ between B₀ field strengths and between patients and healthy volunteers. Importantly, it can further be expected that we will successfully identify the underlying tissue components causing the qMRI anisotropy. By combining results from the post mortem experiments with in vivo observations in patients, we will be able to correlate pathological alterations in qMRI in vivo to the most likely underlying tissue components.

Relevance: Based on our cutting-edge approach that combines post mortem and in vivo examinations, we will be able to thoroughly study the impact of various factors on anisotropic qMRI, including field strengths, different tissue components such as paramagnetic iron and diamagnetic myelin, as well as lipids and proteins. By studying two distinct patient groups, we will be laying a solid foundation for the effective use of the anisotropy index as a simple measure in routine clinical practice. This research holds immense significance for the field of medicine as a whole, as it not only sheds light on the origin of anisotropy in qMRI, but also opens up possibilities for accurate quantitative mapping of tissue composition in patients and elimination of systematic biases in current diagnostic imaging.