Electrical Conductivity Imaging Is Sensitive to Tumor Aggressiveness and Glycolytic Metabolism In Glioma Cell Models
Abstract
Purpose
To evaluate whether MR-based electrical conductivity imaging can distinguish glioma phenotypes with varying aggressiveness and to investigate the metabolic origins of conductivity differences in glioma cell models.
Methods
MR-based electrical properties tomography (MR-EPT) was performed using an ultrashort echo time (UTE) sequence on a 9.4T preclinical MRI system (United Imaging). Electrical conductivity was reconstructed using a phase-based (PB) algorithm. Conductivity measurements were obtained from glioma cell suspensions prepared in Dulbecco’s Modified Eagle Medium (DMEM), with DMEM alone serving as a reference. Three glioma cell models with increasing aggressiveness and distinct metabolic characteristics were studied: U87, U87-EGFRvIII, and U251, all measured under identical conditions. To explore metabolic contributions, single-voxel MR spectroscopy (SVS; voxel size 8×8×8 mm³) was performed in the U251 model to assess glycolytic activity. Additionally, conductivity measurements were conducted in L-lactate solutions with varying concentrations to directly evaluate the relationship between lactate levels and electrical conductivity.
Results
The electrical conductivity of DMEM alone was 1.60 ± 0.45 S/m. Glioma cell suspensions demonstrated significantly higher conductivity values, measuring 3.86 ± 0.42 S/m for U87, 4.75 ± 1.42 S/m for U87-EGFRvIII, and 4.13 ± 0.46 S/m for U251. Under identical experimental conditions, U87-EGFRvIII cells exhibited higher conductivity than U87 cells. In the U251 model, MR spectroscopy revealed increased lactate-related spectral integrals compared with DMEM, consistent with enhanced glycolytic metabolism. Independent experiments in lactate solutions showed a monotonic increase in electrical conductivity with increasing lactate concentration.
Conclusion
UTE-based MR-EPT with phase-based reconstruction at ultra-high field is sensitive to phenotypic differences among glioma cell models of varying aggressiveness. The observed conductivity variations are consistently associated with glycolytic metabolism and lactate concentration, supporting electrical conductivity imaging as a potential noninvasive biomarker of biologically relevant tumor characteristics.