Diffusion functional MRI reveals global brain network functional abnormalities driven by targeted local activity in a neuropsychiatric disease mouse model.

Diffusion functional magnetic resonance imaging (DfMRI) has been proposed as an alternative functional imaging method to detect brain activity without confounding hemodynamic effects. Here, taking advantage of this DfMRI feature, we investigated abnormalities of dynamic brain function in a neuropsychiatric disease mouse model (glial glutamate transporter-knockdown mice with obsessive-compulsive disorder [OCD]-related behavior). Our DfMRI approaches consisted of three analyses: resting state brain activity, functional connectivity, and propagation of neural information. We detected hyperactivation and biased connectivity across the cortico-striatal-thalamic circuitry, which is consistent with known blood oxygen-level dependent (BOLD)-fMRI patterns in OCD patients. In addition, we performed ignition-driven mean integration (IDMI) analysis, which combined activity and connectivity analyses, to evaluate neural propagation initiated from brain activation. This analysis revealed an unbalanced distribution of neural propagation initiated from intrinsic local activation to the global network, while these were not detected by the conventional method with BOLD-fMRI. This abnormal function detected by DfMRI was associated with OCD-related behavior. Together, our comprehensive DfMRI approaches can successfully provide information on dynamic brain function in normal and diseased brains.

In Vivo and Post-mortem Comparisons of IVIM/Time-dependent Diffusion MR Imaging Parameters in Melanoma and Breast Cancer Xenograft Models.

PURPOSE: We aimed to investigate the changes in intravoxel incoherent motion (IVIM) and diffusion parameters between in vivo and post-mortem conditions and the time dependency of these parameters using two different mouse tumor models with different vessel lumen sizes. METHODS: Six B16 and six MDA-MB-231 xenograft mice were scanned using 7 Tesla MRI under both in vivo/post-mortem conditions. Diffusion weighted imaging with 17 b-values (0-3000 s/mm2) were obtained at two diffusion times (9 and 27.6 ms). The shifted apparent diffusion coefficient (sADC) using 2 b-values (200 and 1500 s/mm2), non-Gaussian diffusion and IVIM parameters (ADC0, K, fIVIM) were estimated at each of the diffusion times. The results were evaluated by repeated measures two-way analysis of variance and post hoc Bonferroni test. RESULTS: In B16 tumors, fIVIM significantly decreased with post-mortem conditions (from 12.6 ± 6.5% to 5.2 ± 1.9%, P < 0.05 at long diffusion time; from 11.0 ± 2.4% to 4.6 ± 2.7%, P < 0.05 at short diffusion time). In MDA-MB-231 tumors, fIVIM also significantly decreased (from 8.8 ± 3.8% to 2.6 ± 1.1%, P < 0.05 at long; from 7.9 ± 5.4% to 2.9 ± 1.1%, P < 0.05 at short). No diffusion time dependency was observed (P = 0.59 in B16 and P = 0.77 in MDA-MB-231). The sADC and ADC0 values tended to decrease and the K value tended to increase after sacrificing and when increasing the diffusion time. CONCLUSION: The fIVIM values dropped after sacrificing, confirming that IVIM MRI is a promising quantitative parameter to evaluate blood microcirculation. The presence of residual post-mortem fIVIM values suggested that the influence of water molecule diffusion in the blood lumen may contribute to the IVIM effect. Diffusion MRI parameter's time dependency and those changes after sacrificing could possibly provide additional insights into diffusion hindrance mechanisms.