Damien J. McHugh^{1,2}, Fenglei Zhou^{1,2,3}, Penny L. Hubbard Cristinacce^{1}, Josephine H. Naish^{1}, and Geoffrey J. M. Parker^{1,2,4}

This work investigates the stability of a water-based biomimetic tumour tissue phantom, and evaluates its potential as a tool for validating diffusion-weighted (DW) MRI measurements. As with biological tissue, and unlike most previous phantoms for tumour DW-MRI, the phantom’s apparent diffusion coefficient depends on diffusion time, with values stable over six months. DW-MRI-based estimates of microstructural parameters exhibited bias, possibly indicating limitations in the analysis model or acquisition scheme. It is envisaged that such phantoms will aid investigation of DW-MRI tumour microstructural models, and more generally will act as realistic test objects for comparing DW-MRI-derived biomarkers obtained from different scanners/sites.

**
Phantom construction and
characterisation**

Coaxial-electrospraying^{7} was
used to generate a collection of approximately spherical, micron-scale hollow
polymer 'cells'.
Two samples of the material were
immersed in deionised water, with one used for longitudinal scanning electron microscope
(SEM) characterisation of the outer sphere radius, *R _{o}*, and the other for MR experiments.

**
MR acquisition and analysis
**

Experiments were carried out at ~6, 24,
72 hours, 1, 2, 3, 4, 9, 16, 20 and 26 weeks post-immersion, on a 7 T Bruker
system (Bruker BioSpin, Ettlingen, Germany). For ADC calculations, data were acquired with *b* = 0, 150, 500, 1000 s/mm^{2},
δ = 4 ms, Δ = 12, 45 ms, with TE = 21.3, 54.3 ms, respectively. For
microstructural modelling, data were acquired with *G* = 0, 70, 140, 210 mT/m, δ = 4 ms, Δ = 12, 23, 45 ms, with TE = 21.3,
32.3, 54.3 ms, respectively. All acquisitions had TR = 2500 ms and 0.23 x 0.23
x 1 mm^{3} resolution.

ADC was calculated separately for the Δ
= 12, 45 ms acquisitions. A two-compartment microstructural model^{6}
was fitted to region of interest (ROI)-averaged multi-*G*, multi-Δ signals, yielding four parameters: sphere radius, *R*, free diffusivity, *D*, intracellular volume fraction, *f _{i}*, and the normalised
unweighted signal,

Coefficients of
variation (CoVs) were calculated to assess repeatability, and two-sample *t*-tests were used for statistical
analyses.

**
SEM characterisation
**

SEM images (Figure 1a) illustrate that the spheres tend to group together,
indicating that the phantom's microstructure is not simply a packing of
discrete idealised spheres. The CoV of mean post-immersion *R _{o}* values was 4.2%, suggesting
that the phantom microstructure shows little variation over six months (Figure 1b). Averaging mean values at
each post-immersion time point gave

**
Phantom ADC
**

Figure
2a shows example DW
images and ADC maps 6 hours post-immersion. ADC was consistently higher at the
shorter diffusion time, with a mean ± SD of ROI median values of 1.44 ± 0.04 μm^{2}/ms
(CoV = 2.5%) and 1.20 ± 0.05 μm^{2}/ms (CoV = 4.5%) for Δ = 12 and 45
ms (Figure 2b). Average median ADCs at the two
diffusion times were significantly different in the phantom (*P* < 0.001), but not in free water (*P* = 0.85), providing evidence of
hindered/restricted diffusion in the phantom, demonstrating that it more
closely reflects diffusion in tissue than previous phantoms. Mean ± SD room
temperature over all scanning sessions was 24 ± 1 °C (CoV = 4.2%).

**
Phantom microstructure
**

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6. McHugh DJ, Zhou F, Hubbard Cristinacce PL, Naish JH, Parker GJM. Estimating microstructural properties of a biomimetic tumour tissue phantom using diffusion-weighted MRI. In Proceedings of the 23rd Annual Meeting of ISMRM, Toronto, Canada, 2015. p. 156.

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Figure 1. SEM characterisation
of phantom microstructure. (a) Example images for different
time points, with mean ±
SD outer radius
values. (b) Box plots of outer radii determined from SEM images, for all
post-immersion time points; solid line shows the mean of all post-immersion
mean values, with dashed lines showing 95% CI limits. Time points are plotted
at the number of days post-immersion, while the labels round to the nearest
week for brevity.

Figure 2. Phantom ADC. (a)
Example DW images and ADC maps for the two diffusion times, acquired 6 hours
post-immersion. (b) Box plots of ADC at Δ = 12 ms (black) and 45 ms (red) at
each time point; solid lines show mean of median values, with dashed lines
showing 95% CI limits. The first two time points have been slightly shifted
along the *x*-axis to aid visualisation.
All other time points are plotted at the number of days post-immersion, while
the labels round to the nearest week for brevity.

Figure 3. Microstructural
estimates. (a) Example fits (dashed lines) for a range of time points, with
model parameters and R^{2} of
fit shown. Signals (circles) are plotted as a function of *G* (*x*-axis) for different Δ
(colours). The
highest *G* and highest Δ data were
excluded from the fitting due to low SNR. (b) Microstructural estimates for all time points. Data
points are the values obtained from fitting to whole-ROI averaged signals, and
error bars represent bootstrapped 95% CI limits. Time points are plotted at the
number of days post-immersion, while the labels round to the nearest week for
brevity.

Table 1. CoVs for each model
parameter. Values are the SD divided by the mean of the fitted values at all
time points, expressed as a percentage.