Diffusion-weighted imaging with multiple diffusion time to assess water-exchange between restricted and hindered diffusion components in vivo
Yasuhiko Tachibana1,2, Takayuki Obata1,2, Hiroki Tsuchiya1, Tokuhiko Omatsu1,2, Riwa Kishimoto1,2, Thorsten Feiweier3, and Hiroshi Tsuji1

1Research Center of Charged Particle Therapy, National Institute of Radiological Science, Chiba, Japan, 2Applied MRI Research, National Institute of Radiological Science, Chiba, Japan, 3Siemens Healthcare GmbH, Erlangen, Germany


We performed multi-b and multi-diffusion-time DWI (MbMdt-DWI) on human brain to visualize the mixture of restricted and hindered diffusion components, and also the water exchange between them. The diffusion parameters including the exchange time were calculated. The observed signal patterns clearly indicated the existence of the inter-compartmental water exchange. The calculated exchange time was within the appropriate range assumed from a previous cell-based study in vitro. MbMdt-DWI may be useful for assessing micro-diffusion in human brain.


To assess the capability of multiple b-value with multiple diffusion-time (DT) diffusion-weighted imaging (MbMdt-DWI) to visualize the mixture of restricted and hindered diffusion-components and the water exchange between them in healthy human brain.

Materials and Methods

Seven healthy female volunteers were recruited for this study (20-33 years, mean 24). Their brain MbMdT-DWIs were acquired by 3T MRI (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) with a proto type sequence (Table 1). 11 b-values from 0 to 4000 sec/mm2 were selected, with two encoding directions, respectively. The separation times of the gradients (Δ) were set at 43.4, 63.4, and 83.4 msec, while the diffusion gradient duration (δ) was fixed at 25.0 msec. Regions-of-interest (ROI) were designated manually at the corticospinal tract of the left internal capsule (PLIC) and deep white matter of the left centrum semiovale (CS). A free-water phantom and a phantom of pure restricted-diffusion (Capillary Plate (CP), Hamamatsu Photonics, Japan) were scanned as well as references.

1. DT dependency was assessed by plotting the intra-ROI signal intensity (the mean of the two encoding directions) of the subjects.

2. A diffusion model based on the Karger model was assessed (Fig.1) [1-3]. The model consisted of restricted and hindered diffusion components (RDC and HDC: their fractions were fr and fh) with inter-compartment exchange. The measured signal at a certain DT was expressed as the sum of the signal from RDC (Cr(DT)) and HDC (Ch(DT)) (Fig.2 Eq.1). RDC was defined as the compartment of which the diffusion-coefficient (Dr) was inversely proportional to DT. A supplementary independent variable (A) was set to define this diffusion (A = Dr×DT) [3]. HDC was defined as the compartment with diffusion independent of DT. The diffusion-coefficient of HDC (Dh) was fixed at 0.0012 mm2/sec in this study. The inter-compartment exchange was defined by the exchange time from RDC to HDC (tr) and that from HDC to RDC (th) (Fig.2 Eq.2). The independent variables A, fr, and tr were calculated (Fig.2 Eq.3,4). The variables between PLIC and CS were statistically compared (Wilcoxon signed-rank test; P<0.05 was considered significant).


1. Strong DT dependency nearly linear with the b-value was found in CP, while no DT dependency was found in free water (Fig.3, upper row). In PLIC and CS, DT dependency was found at high b-values. Signal-intensity was elevated or it was slightly decreased when DT was increased from Δ=43.4 to 63.4 msec, and was then decreased by increasing DT further from Δ=63.4 to 83.4 msec (Fig.3, lower row).

2. The observed signal intensities were fit well by the signal-change-curve obtained from the calculated parameters of the proposed model (Fig. 2). The medians of fr and tr in PLIC were larger than those in CS, with significant differences. Statistical difference was not found in A (Table 2).


1. The model of mixed RDC and HDC was reasonable in the DTs applied in this study, because a DT relation was found in high b-values, but not in low b-values in vivo. Furthermore, the fact that the signal was first elevated (or slightly decreased) and then decreased as DT increased may prove the existence of inter-compartment water exchange, because if the compartments were independent, the difference between different DTs should have increased monotonically (as adding the signal of CP and free water).

2. The significantly larger fr in PLIC than CS may suggest larger intra-axonal space, and the small difference in A may suggest a relatively consistent axon diameter by the analogy of the assessment of corticospinal tract by q-space imaging [4]. The significant difference found in tr (larger in PLIC) may possibly reflect myelin density. However, the results do not provide sufficient evidence to prove these hypotheses at this moment. Further study with larger numbers of MPG encoding directions, as well as longer diffusion time (requiring larger gradient strength to maintain TE) may support our results. A study of myelin-water fraction may also help. On the other hand, another previous in vitro study that assessed water exchange in aquaporin-4-expressing and -non-expressing cells reported the exchange times from intra- to extra-cellular space as 43.1 msec and 100.7 msec, respectively [5]. The range included tr of PLIC and CS in this study, which may somewhat support the appropriateness of our results, as RDC may mostly belong to intracellular water.


MbMdt-DWI may be useful for visualizing the exchange between RDC and HDC in human brain.


This work was partially supported by grants from the Ministry of Education, Culture, Sports, and Science.

The authors appreciate H. Kamata for her general assistance, and K. Murata for his technical advice.


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5. Ibata K, Takimoto S, Morisaku T, Miyawaki A, Yasui M (2011) Analysis of aquaporin-mediated diffusional water permeability by coherent anti-stokes Raman scattering microscopy. Biophys J 101: 2277-2283.


Figure 1: Schema of the model of restricted and hindered diffusion components (RDC and HDC) with inter-compartment exchange

Figure 2: Calculation of the independent parameters of the model

Diffusion time and b-value dependent signal change of the phantoms and human brain. The stars and the dotted lines indicate the observed signal intensities and the signal-change-curve obtained from the calculated diffusion parameters, respectively. The model fits the observed data well.

Table 1: Major parameters of multiple b-value with multiple diffusion-time diffusion-weighted imaging (MbMdT-DWI) sequence

Table 2: Calculated diffusion parameters and the results of statistical comparisons

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)