Diffusion time dependence of magnetic resonance diffusion signal decays: an investigation of water exchange in human brain in vivo

Assessment of the effects of mimicking tissue microstructural properties on apparent diffusion coefficient and apparent exchange rate in diffusion MRI via a series of specially designed phantoms

PURPOSE

Diffusion MRI provides a valuable tool for imaging tissue microstructure. However, due to the lack of related experimental methods and specially designed phantoms, no experimental study has been conducted yet to quantitatively assess the effects of membrane permeability, intracellular volume fraction (IVF), and intracellular diffusivity on the apparent diffusion coefficient (ADC) obtained from diffusion weighted imaging (DWI), and the effects of membrane permeability on the apparent exchange rate (AXR) obtained from filter exchange imaging (FEXI).

METHODS

A series of phantoms with three adjustable parameters was designed to mimic tissue microstructural properties including membrane permeability, IVF, and intracellular diffusivity. Quantitative experiments were conducted to assess the effects of these properties on ADC and AXR. DWI scans were performed to obtain axial and radial ADC values. FEXI scans were performed to obtain AXR values.

RESULTS

Axial ADC values range from 1.148 μm² /ms to 2.157 μm² /ms, and radial ADC values range from 0.904 μm² /ms to 2.067 μm² /ms. Radial ADC decreased with a decrease in fiber permeability. Decreased axial and radial ADC values with increased intra-fiber volume fraction, and increased polyvinylpyrrolidone (PVP) concentration of the intra-fiber space were observed. AXR values range from 2.1 s^-1 to 4.9 s^-1 . AXR increases with fiber permeability.

CONCLUSION

The proposed phantoms can quantitatively evaluate the effects of mimicking tissue microstructural properties on ADC and AXR. This new phantom design provides a potential method for further understanding the biophysical mechanisms underlying the change in ADC and diffusion exchange.

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

Background

The use of rigid multi-exponential models (with a priori predefined numbers of components) is common practice for diffusion-weighted MRI (DWI) analysis of the kidney. This approach may not accurately reflect renal microstructure, as the data are forced to conform to the a priori assumptions of simplified models. This work examines the feasibility of less constrained, data-driven non-negative least squares (NNLS) continuum modelling for DWI of the kidney tubule system in simulations that include emulations of pathophysiological conditions.

Methods

Non-linear least squares (LS) fitting was used as reference for the simulations. For performance assessment, a threshold of 5% or 10% for the mean absolute percentage error (MAPE) of NNLS and LS results was used. As ground truth, a tri-exponential model using defined volume fractions and diffusion coefficients for each renal compartment (tubule system: D_tubules , f_tubules ; renal tissue: D_tissue , f_tissue ; renal blood: D_blood , f_blood ;) was applied. The impact of: (I) signal-to-noise ratio (SNR) =40-1,000, (II) number of b-values (n=10-50), (III) diffusion weighting (b-range_small =0-800 up to b-range_large =0-2,180 s/mm²), and (IV) fixation of the diffusion coefficients D_tissue and D_blood was examined. NNLS was evaluated for baseline and pathophysiological conditions, namely increased tubular volume fraction (ITV) and renal fibrosis (10%: grade I, mild) and 30% (grade II, moderate).

Results

NNLS showed the same high degree of reliability as the non-linear LS. MAPE of the tubular volume fraction (f_tubules ) decreased with increasing SNR. Increasing the number of b-values was beneficial for f_tubules precision. Using the b-range_large led to a decrease in MAPE _ftubules compared to b-range_small. The use of a medium b-value range of b=0-1,380 s/mm² improved f_tubules precision, and further b_max increases beyond this range yielded diminishing improvements. Fixing D_blood and D_tissue significantly reduced MAPE _ftubules and provided near perfect distinction between baseline and ITV conditions. Without constraining the number of renal compartments in advance, NNLS was able to detect the (fourth) fibrotic compartment, to differentiate it from the other three diffusion components, and to distinguish between 10% vs. 30% fibrosis.

Conclusions

This work demonstrates the feasibility of NNLS modelling for DWI of the kidney tubule system and shows its potential for examining diffusion compartments associated with renal pathophysiology including ITV fraction and different degrees of fibrosis.

Eliminating the blood-flow confounding effect in intravoxel incoherent motion (IVIM) using the non-negative least square analysis in liver

PURPOSE

Tissue perfusion measurements using intravoxel incoherent motion (IVIM) diffusion-MRI are of interest for investigations of liver pathologies. A confounding factor in the perfusion quantification is the partial volume between liver tissue and large blood vessels. The aim of this study was to assess and correct for this partial volume effect in the estimation of the perfusion fraction.

METHODS

MRI experiments were performed at 3 Tesla with a diffusion-MRI sequence at 12 b-values. Diffusion signal decays in liver were analyzed using the non-negative least square (NNLS) method and the biexponential fitting approach.

RESULTS

In some voxels, the NNLS analysis yielded a very fast-decaying component that was assigned to partial volume with the blood flowing in large vessels. Partial volume correction was performed by biexponential curve fitting, where the first data point (b = 0 s/mm² ) was eliminated in voxels with a very fast-decaying component. Biexponential fitting with partial volume correction yielded parametric maps with perfusion fraction values smaller than biexponential fitting without partial volume correction.

CONCLUSION

The results of the current study indicate that the NNLS analysis in combination with biexponential curve fitting allows to correct for partial volume effects originating from blood flow in IVIM perfusion fraction measurements. Magn Reson Med 77:310-317, 2017. © 2016 Wiley Periodicals, Inc.