Detecting Microglial Density With Quantitative Multi-Compartment Diffusion MRI

Abstract

Neuroinflammation plays a central role in the neuropathogenesis of a wide-spectrum of neurologic and psychiatric disease, but current neuroimaging methods to detect and characterize neuroinflammation are limited. We explored the sensitivity of quantitative multi-compartment diffusion MRI, and specifically neurite orientation dispersion and density imaging (NODDI), to detect changes in microglial density in the brain. Monte Carlo simulations of water diffusion using a NODDI acquisition scheme were performed to measure changes in a virtual MRI signal following modeled cellular changes within the extra-neurite space. 12-week-old C57BL/6J male mice ( n = 48; 24 control, 24 treated with colony stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622) were sacrificed at 0, 1, 3, and 7 days following withdrawal of CSF1R inhibition and were imaged ex-vivo to obtain measures of the orientation dispersion index (ODI). Following imaging, all brains were immunostained with Iba-1, NeuN, and GFAP for quantitative fluorescence microscopy. Cell populations were calculated with the ImageJ particle analyzer tool; correlation between microglial density and mean ODI values were calculated with Kendall's tau. Monte Carlo simulations demonstrate the sensitivity and positive correlation of ODI to increased occupancy in the extra-neurite space. Commensurate with our simulation data, ex-vivo NODDI imaging demonstrates an increase in ODI as microglia repopulate the brain following the withdrawal of CSF1R inhibition. Quantitative immunofluorescence of microglial density reveals that microglial density is positively correlated with ODI and greater hindered diffusion in the extra-neurite space (τ = 0.386, p < 0.05). Our results demonstrate that clinically feasible multi-compartment diffusion weighted imaging techniques such as NODDI are sensitive to microglial density and the cellular changes associated with microglial activation and highlights its potential to improve clinical diagnostic accuracy, patient risk stratification, and therapeutic monitoring of neuroinflammation in neurologic and psychiatric disease.

Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain

“…The NODDI and tensor derived metrics have been applied to different populations including healthy and aging adults (52,53), patients with amyotrophic lateral sclerosis and Alzheimer's disease patients (54,55), and to preclinical models (56,57). In the neonatal MRI field, tensor derived metrics have been widely used to study the effects of prematurity on the brain (5), and several other factors, such as chronic lung disease, nutrition, prenatal drug exposure, among others (11,13,19,58).…”

Advanced mapping of the human white matter microstructure better separates elite sports participation

“…An increase in NDI could be related to exercise-associated increases in synaptogenesis and dendritic spine density (Hötting and Röder, 2013) , or, alternatively, alterations in ionic balance leading to axonal swelling associated with neuroinflammatory mechanisms (Skinner et al, 2015;Wang et al, 2019) . Increased ODI may also reflect increased neuroplastic alterations as well as an increased proliferation of microglia and other neuroinflammatory-related cellular structures (Yi et al, 2019) . Overall, the corresponding increases in NDI, ODI, and ISOVF may be reflective of neuroinflammatory mechanisms related to differences in stress-levels and peripheral inflammation between athletes and non-athletes.…”

“…Specifically, football players had the highest ODI, NDI, and ISOVF estimates suggesting that subconcussive impacts during sport participation may have led to alterations in myelinated neurite tissue associated with a state of stress or repair. A higher ODI, for instance, suggests a loss of coherence in the organization of neurite tissue (Zhang et al, 2012) or increases in microglial density (Yi et al, 2019) in football players relative to other athletes and non-athletes. A higher NDI suggests that the neurites might be swollen (Dowell et al, 2017;Wang et al, 2019) or under a process of remyelination (Jespersen et al, 2010;Luo et al, 2018;Sepehrband et al, 2015) .b Finally, a higher ISOVF suggests that neuroinflammatory processes is occurring (Zhang et al, 2012) .…”

“…NODDI parameters such as orientation dispersion (ODI), neurite density (NDI) and corticospinal fluids volume fraction (ISOVF) provide measures with different degree of sensitivity to the various components of the white matter tissue microstructure. For example, differences in ODI can be attributed to a variety of biophysical or biomechanical factors including formation of new spines, microglial density, and biomechanical pulling of white matter tissue (Alexander et al, 2010;Dyrby et al, 2013;Mayer et al, 2017;Yi et al, 2019;Zhang et al, 2012) . Changes in NDI can be interpreted as changes in the density of myelinated neurites (Zhang et al, 2012) but have also been associated with hyper-phosphorylated tau-deposition in cortex (Colgan et al, 2016) , axonal beading (Skinner et al, 2015) , alterations in ionic balance , and myelin density (Luo et al, 2018;Sepehrband et al, 2015) .…”

Gliosis and Neurodegenerative Diseases: The Role of PET and MR Imaging

“…Changes of iron deposition, quantified using quantitative susceptibility mapping in MR, have been correlated with activated microglia/macrophages at edges of some chronic demyelinated lesions in patients suffering from multiple sclerosis (Dal-Bianco et al, 2017;Gillen et al, 2018;Hametner et al, 2018). Advanced diffusion models, based on neurite orientation dispersion and density imaging (NODDI) in MR, have been proved to be sensitive to microglial density and to the cellular changes associated with microglial activation in a preclinical setting (Yi et al, 2019). Finally, in amyotrophic lateral sclerosis patients, a technique based on diffusion spectroscopy has been applied to identify the increase of the predominantly glial metabolites (unspecific for microglia and astrocytes) tCr (creatine + phosphocreatine) and tCho (cholinecontaining compounds) in the primary motor cortex (Reischauer et al, 2018).…”