Pulsed and oscillating gradient MRI for assessment of cell size and Extracellular space (POMACE) in mouse gliomas - Reynaud, Olivier (NMR Biomed, 2016)
Solid tumor microstructure is related to aggressiveness of tumor, interstitial pressure and drug delivery pathways that are closely associated with treatment response, metastatic spread and prognosis. In this study, we introduce a novel diffusion MRI data analysis framework, Pulsed and Oscillating gradient MRI for Assessment of Cell size and Extracellular space (POMACE), and demonstrate its feasibility in a mouse tumor model. In vivo and ex vivo POMACE experiments were performed on mice bearing the GL261 murine glioma model (n=8). Since the complete diffusion time-dependence is in general non-analytical, the tumor microstructure was modeled in an appropriate time/frequency regime by impermeable spheres (radius R(cell), intracellular diffusivity D(ics)) surrounded by extracellular space (approximated by constant apparent diffusivity D(ecs) in volume fraction ECS). POMACE parametric maps (ECS, R(cell), D(ics), D(ecs)) were compared with conventional diffusion weighted imaging metrics, electron microscopy (EM), alternative ECS determination based on effective medium theory (EMT), and optical microscopy performed on the same samples. It was shown that D(ecs) can be approximated by its long-time tortuosity limit in the range [1/(88 Hz) - 31 ms]. ECS estimations (44±7% in vivo and 54±11% ex vivo) were in agreement with EMT-based ECS and literature on brain gliomas. Ex vivo, ECS maps correlated well with optical microscopy. Cell sizes (R(cell)=4.8±1.3 in vivo and 4.3±1.4 μm ex vivo) were consistent with EM measurements (4.7±1.8 μm). In conclusion, R(cell) and ECS can be quantified and mapped in vivo and ex vivo in brain tumors using the proposed POMACE method. Our experimental results support that POMACE provides a way to interpret the frequency- or time-dependence of the diffusion coefficient in tumors in terms of objective biophysical parameters of neuronal tissue, which can be used for non-invasive monitoring of preclinical cancer studies and treatment efficacy.