A Biophysical Model of Iron-Induced Transverse MRI Relaxation in Nigrosome 1: Toward an Early Biomarker of Parkinson's Disease
In Parkinson's disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 in substantia nigra precedes first motor symptoms by almost two decades. Methods capable of monitoring this neuronal depletion at an early disease stage are highly desired for diagnosis and treatment monitoring.
MRI is particularly suited for this task, since it is sensitive to iron accumulated in the neuromelanin of dopaminergic neurons (Fig. 1). However, the mechanisms of MRI contrast in substantia nigra are unknown, hindering the development of specific biomarkers. We elucidate the mechanisms of iron-induced transverse relaxation in nigrosome 1 by combining quantitative 3D iron histology, quantitative MRI on post mortem human brain tissue, and biophyiscal modeling.
We developed a comprehensive biophysical model accounting for the chemical form of iron binding and the heterogeneous iron distribution at the cellular scale. This model was informed with 3D quantitative iron concentration maps of nigrosome 1 obtained from combining Proton-Induced X-ray Emission microscopy (PIXE) with iron histochemistry. We showed that iron in dopaminergic neuron is the dominant source of effective transverse relaxation rate R2*. We determined the proper theoretical relaxation regime describing R2*, which was found to be close to static dephasing (Fig. 2). In this regime, R2* is analytically linked to the total iron content in dopaminergic neurons, i. e., the product of neuronal density and mean cellular iron concentration (Yablonskiy and Haacke, MRM, 1994, 32, 6, 749-63). Our model’s predictions were shown to be accurate by comparing them to relaxation rates acquired at 7 T on a specimen before and after chemical iron extraction.
For the first time, we achieved a mechanistic model of iron-induced MR contrast in substantia nigra derived from first principles and based on iron microstructure quantification. This knowledge paves the road toward novel, specific biomarkers for Parkinson's disease.