Exploring the relationship between larmor-frequency electrical conductivity, diffusivity, and tissue volume in the aging brain

Abstract

Background: The aging brain undergoes various microstructural changes that influence its electrical properties. Conductivity, a measure of ion mobility, is particularly sensitive to these changes and can be assessed non-invasively using magnetic resonance electrical properties tomography (MREPT). Despite advancements in imaging techniques, the relationship between brain conductivity, diffusivity, and tissue volume in the context of aging and neurodegeneration remains incompletely understood. This study explores the relationships between electrical conductivity, diffusivity, and brain tissue volume in the aging brain, which is crucial for early diagnosis and monitoring of neurodegenerative diseases such as Alzheimer's, where these parameters could serve as potential biomarkers for disease progression.

Methods: In this cross-sectional, prospective study, 77 patients were assessed brain MREPT and diffusion tensor imaging with multiple shells and gradient directions (b=0, 800, and 2,000 s/mm²). High-frequency conductivity (HFC) was calculated and separated into extra-neurite (EC) and intra-neurite conductivities (IC). We analyzed correlations between these conductivity indices and other magnetic resonance imaging (MRI) metrics, controlling for age, and explored the relationship between conductivity, diffusion, and Mini-Mental State Examination (MMSE) scores using multiple regression analysis.

Results: EC within the insular region negatively correlated with MMSE scores (r=-0.3027, P=0.0079). HFC in the hippocampus was positively associated with mean diffusivity (MD; β=192.4, P=0.008) and radial diffusivity (RD; β=207.6, P=0.004). HFC in the insula was positively associated with axial diffusivity (AxD; β=356.9, P=0.0004), MD (β=314.4, P=0.004), RD (β=275.5, P=0.012). EC in the hippocampus was positively associated with AxD (β=309.3, P=0.0001), MD (β=333.7, P<0.001), RD (β=341.8, P<0.001). EC in the insular was positively associated with AxD (β=324.1, P=0.0009) and MD (β=270.4, P=0.01). IC was positively correlated with intra-neurite diffusivity (ID) in the amygdala, thalamus, and insula.

Conclusions: These findings suggest that increased conductivity is associated with altered diffusivity and reduced cognitive performance, suggesting the use of MREPT to differentiate between conductivity changes due to ion mobility versus proton density, and how this approach contributes to understanding the aging brain and neurodegeneration. MREPT-derived measurements primarily reflect ion mobility and caution that clinical interpretations should consider the direct relationships between conductivity and diffusion changes.

Keywords: Magnetic resonance imaging (MRI); aging brain; brain tissue volume; conductivity; diffusivity.

Figure 1

Representative conductivity maps calculated with MREPT and the corresponding diffusion maps calculated with MC-SMT obtained from two participants who had MMSE score =30 and MMSE score =22. EC, extra-neurite conductivity; ED, extra-neurite diffusivity; EV, extracelluar volume; HFC, high-frequency conductivity; IC, intra-neurite conductivity; ID, intra-neurite diffusivity; IV, intracellular volume; MC-SMT, multi-compartment spherical mean technique; MMSE, Mini-Mental State Examination; MREPT, magnetic resonance electrical properties tomography; WM, white matter.

Figure 2

Results of voxel-based multiple regression analysis between conductivity or diffusion maps and MMSE score with age as a covariate. We evaluated the following multiple-regression model for age: Conductivity or diffusivity maps ≈β1*age + error and for MMSE score: Conductivity or diffusivity maps ≈β1*age + β2*MMSE score + error. The red and blue colors represent positive and negative associations, respectively. Age did not correlate with any conductivity indices. AxD (ADC), axial diffusivity; EC, extra-neurite conductivity; ED, extra-neurite diffusivity; EV, extracellular volume; FA, fractional anisotropy; HFC, high-frequency conductivity; MD, mean diffusivity; MMSE, mini-mental state examination; RD, radial diffusivity; WM, white matter.

Figure 3

Result of correlation analysis between conductivity values and diffusion or BTV values in each ROI using the heatmap method. The Y-axis indicates conductivity indices and the X-axis indicates brain tissue volume indices of CSF, GMV, and WMV (left side) and diffusion indices (middle and right side). The red color indicates a positive correlation and the blue color indicates a negative correlation. The number indicates the atlas-based ROI areas as the hippocampus [0102], amygdala [0506], thalamus [1314], insular [2425], and corpus callosum [28] without separate left and right brain sides. AxD (ADC), axial diffusivity; BTV, brain tissue volume; CSF, cerebrospinal fluid volume; EC, extra-neurite conductivity; ED, extra-neurite diffusivity; EV, extracellular volume; FA, fractional anisotropy; GMV, gray matter volume; HFC, high-frequency conductivity; IC, intra-neurite conductivity; ID, intra-neurite diffusivity; IV, intracellular volume; MD, mean diffusivity; RD, radial diffusivity; ROI, region of interest; WM, white matter; WMV, white matter volume.