Quantitative MRI and Network Science Applications in Manganese Neurotoxicity

Manganese (Mn) is an essential trace element for humans that functions primarily as a coenzyme in several biological processes such as nerve and brain development, energy metabolism, bone growth and development, as well as cognitive functioning. However, overexposure to environmental Mn via occupational settings or contaminated drinking water can lead to toxic effects on the central nervous systems and cause a Parkinsonian disorder that features symptoms such as fine motor control deficits, dystonia rigidity, speech and mood disturbances, and cognitive deficits summarized under the term “manganism”. Over time, Mn exposure has shifted from acute, high-level instances leading to manganism, to low-level chronic exposure. Considering that Mn exposure is significantly lower than in the past, it is unlikely to expect manganism from chronic Mn exposure under current working conditions. Therefore, there is a need to develop sensitive methods to aid in updating the clinical diagnostic standards for manganism and Mn neurotoxicity as chronic exposure to Mn leads to more subtle symptoms.

Historically, magnetic resonance imaging (MRI) has been used as a non-invasive tool for detecting excess brain Mn accumulation. Specifically, T1-weighted images show bilateral hyperintensities of the globus pallidus (GP) due to the paramagnetic properties of Mn which increases the MR relaxation rate R1. Although the GP is considered the hallmark of excess brain Mn, this brain area is not necessarily associated with symptoms, exposure, or neuropsychological outcomes. Thus, the focus should not be on the GP only but on the entire brain. With recent advances in quantitative MRI (qMRI), whole brain mapping techniques allow for the direct measurement of relaxation rate changes due to Mn accumulation. The work in this dissertation uses such quantitative techniques and network science to establish novel computational in vivo imaging methods to a) visualize and quantify excess Mn deposition at the group and individual level, and b) characterize the toxicokinetics of excess brain Mn accumulation and the role of different brain regions in the development of neurotoxicity effects.

First, we developed a novel method for depicting excess Mn accumulation at the group level using high-resolution R1 relaxation maps to identify regional differences using voxel-based quantification (VBQ) and statistical parametric mapping. Second, we departed from a group analysis and developed subject-specific maps of excess brain Mn to gain a better understanding of the relationship between the spatial distribution of Mn and exposure settings. Third, we developed a novel method that combines network science with MRI relaxometry to characterize the storage and propagation of Mn and Fe in the human brain and the role of different brain regions in the development of neurotoxic effects. Lastly, we explore the application of ultra-short echo (UTE) imaging to map Fe content in the brain and compare it against R2* and quantitative susceptibility mapping (QSM).

Overall, this dissertation is a successful step towards establishing sensitive neuroimaging screening methods to study the effects of occupational Mn exposure. The individual Mn maps offer great potential for evaluating personal risk assessment for Mn neurotoxicity and allow monitoring of temporal changes in an individual, offering valuable information about the toxicokinetics of Mn. The integration of network science provides a holistic analysis to identify subtle changes in the brain’s mediation mechanisms of excess metal depositions and their associations with health outcomes.