The Effect of Microcirculatory Flow on Oscillating Gradient Diffusion MRI and Diffusion Encoding with Dual-Frequency Orthogonal Gradients (DEFOG)

Abstract

Purpose We investigated the effect of microcirculatory flow on oscillating gradient spin echo (OGSE) diffusion MRI at low b-values and developed a diffusion preparation method called diffusion encoding with dual-frequency orthogonal gradients (DEFOG) to suppress the effect. Methods Compared to conventional OGSE sequences, DEFOG adds a pulsed gradient that is orthogonal to the oscillating gradient and has a moderate diffusion weighting (e.g., 300 s/mm2). In vivo MRI data were acquired from adult mouse brains (n = 5) on an 11.7 Tesla scanner, with diffusion times from 23.2 to 0.83 ms and b-values from 50 to 700 s/mm2. Results Apparent diffusion coefficients (ADCs) measured using a conventional OGSE sequence at low b-values (< 200 mm2/s) were significantly higher than those measured at moderate b-values (> 300 mm2/s), potentially due to contributions from microcirculatory flow. In comparison, OGSE ADCs measured using the DEFOG method at low b-values were comparable to those measured at moderate b-values. The effect of microcirculatory flow on diffusion signals was diffusion time-dependent, and this dependency may reflect the capillary geometry and blood flow velocity in the mouse cortex. Conclusion Microcirculatory flow affects OGSE diffusion MRI measurements at low b-values, and this effect can be suppressed using the DEFOG method.

Diffusion dispersion imaging: Mapping oscillating gradient spin‐echo frequency dependence in the human brain

“…For the acquisitions and fitted parameters to be insensitive to perfusion, the perfusion signal must be much less than the tissue signal at all frequencies used. In mice, no dependence on perfusion was observed for frequencies up to 200 Hz for > 300 s/mm 2 (see Wu and Zhang); accordingly, this assumption was likely satisfied here, where ‐values of at least 450 s/mm 2 and a maximum frequency of only 60 Hz were used. On the other hand, at high b‐values, higher order terms in the cumulant expansion of and rotational variance may need to be considered for accurate estimation of and .…”

“…In the long diffusion time regime, coarse graining occurs and the dependence on frequency is related to long‐range structural correlations, where θ is a parameter given by the effective dimension of diffusion and the class of structural disorder . θ = 1/2 has been demonstrated in both healthy and globally ischemic rodent brain tissue. A trend toward θ < 1 can be observed from the data presented in the in vivo human brain, but this behavior was not explicitly explored and only 2 non‐zero frequencies were acquired.…”

Evidence of the diffusion time dependence of intravoxel incoherent motion in the brain

“…Here, we used the apodized cosine‐trapezoid OGSE, FC‐PGSE, and noncompensated (NC)‐PGSE waveforms to access an extended range of T D (Figure A–C). The OGSE waveform is inherently flow compensated with a zero first‐order moment and an effective T D of 1/4 of the oscillating cycle .…”

Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation

“…Oscillating‐gradient spin echo (OGSE) diffusion‐weighted sequences are able to probe shorter diffusion time scales compared with conventional PGSE, and have clearly demonstrated time‐dependent diffusion in the brain, including the observation of time‐dependent diffusivities in vivo in normal and ischemic rat brain cortex, as well as ex vivo in rat WM tracts . By combining OGSE and PGSE, Pyatigorskaya et al observed a time‐dependent diffusion coefficient and nonmonotonic time‐dependent kurtosis (with a maximum value K ≈0.6 at t ≈10 ms) in healthy rat brain cortex at 17.2T, and Wu and Zhang() recently observed time dependence in mouse cortex and hippocampus. In humans, Baron and Beaulieu found that eight major WM tracts and two deep gray matter areas exhibited time‐dependent diffusion using OGSE and PGSE, and Van et al reported a similar effect with OGSE in human corpus callosum.…”