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Purpose To demonstrate the feasibility of multidimensional diffusion MRI to probe and quantify microscopic fractional anisotropy (µFA) in human kidneys in vivo. Methods Linear tensor encoded (LTE) and spherical tensor encoded (STE) renal diffusion MRI scans were performed in 10 healthy volunteers. Respiratory triggering and image registration were used to minimize motion artefacts during the acquisition. Kidney cortex–medulla were semi‐automatically segmented based on fractional anisotropy (FA) values. A model‐free analysis of LTE and STE signal dependence on b‐value in the renal cortex and medulla was performed. Subsequently, µFA was estimated using a single‐shell approach. Finally, a comparison of conventional FA and µFA is shown. Results The hallmark effect of µFA (divergence of LTE and STE signal with increasing b‐value) was observed in all subjects. A statistically significant difference between LTE and STE signal was found in the cortex and medulla, starting from b = 750 s/mm2 and b = 500 s/mm2, respectively. This difference was maximal at the highest b‐value sampled (b = 1000 s/mm2) which suggests that relatively high b‐values are required for µFA mapping in the kidney compared to conventional FA. Cortical and medullary µFA were, respectively, 0.53 ± 0.09 and 0.65 ± 0.05, both respectively higher than conventional FA (0.19 ± 0.02 and 0.40 ± 0.02). Conclusion The feasibility of combining LTE and STE diffusion MRI to probe and quantify µFA in human kidneys is demonstrated for the first time. By doing so, we show that novel microstructure information—not accessible by conventional diffusion encoding—can be probed by multidimensional diffusion MRI. We also identify relevant technical limitations that warrant further development of the technique for body MRI.

Purpose: Double diffusion encoding (DDE) MRI enables the estimation of microscopic diffusion anisotropy, yielding valuable information on tissue microstructure. A recent study proposed that the acquisition of rotationally invariant DDE metrics, typically obtained using a spherical "5-design", could be greatly simplified by assuming Gaussian diffusion, facilitating reduced acquisition times that are more compatible with clinical settings. Here, we aim to validate the new minimal acquisition scheme against the standard DDE 5-design, and to quantify the proposed method's noise robustness to facilitate future clinical use.Methods: DDE MRI experiments were performed on both ex vivo and in vivo rat brains at 9.4 T using the 5-design and the proposed minimal design and taking into account the difference in the number of acquisitions. The ensuing microscopic fractional anisotropy (μFA) maps were compared over a range of b-values up to 5000 s/mm2. Noise robustness was studied using analytical calculations and numerical simulations. Results:The minimal protocol quantified μFA at an accuracy comparable to the estimates obtained via the more theoretically robust DDE 5-design. μFA's sensitivity to noise was found to strongly depend on compartment anisotropy and tensor magnitude in a non-linear fashion. When μFA < 0.75 or when mean diffusivity is particularly low, very high signal to noise ratio (SNR) is required for precise quantification of µFA. Conclusion:Our work supports using DDE for quantifying microscopic diffusion anisotropy in clinical settings but raises hitherto overlooked precision issues when measuring μFA with DDE and typical clinical SNR.

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture is a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. However, the sources of the contrasts observed in conventional dMRI in general and in ischemia in particular are still highly debated since the markers are only surrogate reporters of the underlying microstructure. Here, we present Correlation Tensor MRI (CTI), a method that rather than measuring diffusion, harnesses diffusion correlations as its source of contrast. We show that CTI can resolve the sources of diffusional kurtosis, which in turn, provide dramatically enhanced specificity and sensitivity towards ischemia. In particular, the sensitivity towards ischemia nearly doubles, both in grey matter and white matter, and unique signatures for neurite beading, cell swelling, and edema are inferred from CTI. The enhanced sensitivity and specificity endowed by CTI bodes well for future applications in biomedicine, basic neuroscience, and in the clinic.