Eoin Finnerty1, Rajiv Ramasawmy2, James O'Callaghan2, Mark F Lythgoe2, Karin Shmueli1, David L Thomas3, and Simon Walker-Samuel2
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2University College London, London, United Kingdom, 3Institute of Neurology, University College London, London, United Kingdom
Synopsis
This work examines the application of
Quantitative Susceptibility Mapping (QSM) in a mouse model of colorectal liver
metastases. It was hypothesised that QSM could provide a novel method of
interrogation of liver tumours based on differences in blood oxygenation.
Results under hyperoxic and normoxic conditions were compared to assess the
response of the liver tissue and tumours. A vascular disrupting agent was then
administered to assess its effect on the QSM measurements. A significant
difference was found between liver and tumour tissue, and regional differences
in susceptibility were found within a tumour. These differences were less
apparent after VDA administration.Introduction
In this study we aimed to evaluate the use of
Quantitative Susceptibility Mapping (QSM) in a mouse model of colorectal carcinoma
metastasis to liver. Tumour blood flow and oxygenation are critical factors for
successful cancer therapy[1], and there is currently no clinically
accepted, non-invasive method of monitoring this[2]. We hypothesised that QSM could provide a novel
mechanism to characterise
the pathophysiology of the tumours based on differences in blood oxygenation. Results
under hyperoxic and normoxic conditions were compared to assess the
differential response of the tumours and normal liver. Lastly, a vascular
disrupting agent (VDA) was administered to evaluate the effect of this vascular
targeting therapy on the QSM measurement.
Methods
MF1
nu/nu mice (n=3) were inoculated with 1x10^6 SW1222
colorectal liver metastases cells via intrasplenic injection. MRI was performed
at approximately 4 weeks post-surgery. Mice were anaesthetised using 4%
isoflurane in 100% O2. During scanning, respiratory rate was
monitored and maintained at ~60-80 breaths per minute by varying isoflurane
concentration between 1.5 and 2%. Hyperoxia was induced with 100% O2,
followed by medical air to induce normoxic conditions. Fully
flow-compensated, respiratory-gated, single-echo 2D T2*-weighted GRE
data were acquired on an Agilent 9.4T scanner using a 39mm birdcage coil (Rapid
biomedical, Rimpar, Germany). Matrix=136x136,
80 slices, 200µm isotropic resolution, TR/TE=1000/4ms, averages=4. A sample of purified
water accompanied each mouse in the scanner to provide a reference for
susceptibility measurements. Acquisition time was approximately 20 minutes for
each gas.
VDA (OXi4503) was administered i.v.
(40 mg/kg) directly after the pre-drug acquisitions; post-drug acquisitions
took place 48 hours later. A binary mask was manually drawn around the entire
liver in each magnitude image using ITK-SNAP[3]. The corresponding phase data was unwrapped
and the background field suppressed using a Laplacian based SHARP algorithm
(TSVD threshold = 0.08, mask erode = 1)[4]. Inversion was carried
out using a TKD algorithm (threshold = 5)[5].
Regions of interest (ROIs) were
manually drawn on the magnitude images and then transferred to the
susceptibility maps. ROIs were drawn in normal liver tissue and all visible
tumours in each mouse on the magnitude images. A large individual tumour in one
mouse was selected to examine the intra-tumoural response to the gas challenge
and VDA. To assess regional differences within the tumour, the mean
susceptibility in the tumour in each transverse slice was plotted against slice
position.
Results
Fig. 1 shows a susceptibility map
of the liver vasculature overlaid with a susceptibility map of the tumours. The
blue and green areas within the tumours represent differences in susceptibility
that may be indicative of regional differences in blood oxygenation.
Both tumour and normal liver were
more paramagnetic under hyperoxia than normoxia (fig. 2). Susceptibility values measured in the liver
tissue were compared to those within the tumours using an unpaired Student’s
t-test, and a significant difference was measured between the liver tissue and
tumours during administration of both gasses (p=0.0083 normoxic, p=0.014
hyperoxic).
Within the individual tumour, the
difference in susceptibility between norm- and hyperoxic states was most
prominent in the tumour periphery, where, during normoxia, the tissue was
relatively diamagnetic, compared to the more paramagnetic centre (fig 3). The
difference in susceptibility between the tumour centre and periphery was
attributed to differences in blood oxygenation between the regions. The
periphery was less diamagnetic under
hyperoxic conditions (fig 3), suggesting a reduction in the amount of oxyhaemoglobin
present. In response to VDA therapy, the
region at the centre of the tumour was more diffuse post-VDA (fig. 4).
Furthermore, the prominent changes in susceptibility caused by the gas
challenge, prior to VDA therapy, no longer occurred post-VDA, suggesting a
reduction in vascular function by the drug (fig 3).
Discussion & Conclusion
This study demonstrates the
feasibility of using QSM to interrogate a mouse model of colorectal liver
metastases. Differences in susceptibility were detected between liver and
tumour tissue. Regional susceptibility variations were measured within a tumour
and differences mediated by the gas challenge were also detected. Heterogeneous
perfusion is a characteristic of tumours [6], and the differences in
susceptibility between the centre and periphery of the tumour may be indicative
of this.
OXi4503 is a vascular disrupting
agent that has been shown to be effective against the vasculature of several
tumour types[7]. The modulation of susceptibility mediated by the
gas challenge was not observed in the post-VDA images. This suggests that the
gas challenge elicited a vasoactive response, and that QSM could be used to detect
changes in the functional vascular volume within an individual tumour, that may
inform on the efficacy of vascular disrupting agents.
Acknowledgements
DLT is supported by the UCL Leonard Wolfson Experimental Neurology Centre (PR/ylr/18575).
SWS is supported by a Wellcome Trust Senior Research Fellowship (grant WT100247MA).
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