Vanessa Wiggermann1,2, Simon Hametner3, Enedino Hernandez-Torres2,4, Verena Endmayr3, Christian Kames5, and Alexander Rauscher2
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 2Pediatrics, University of British Columbia, Vancouver, BC, Canada, 3Neuroimmunology, Medical University of Vienna, Vienna, Austria, 4UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada, 5Engineering Physics, University of British Columbia, Vancouver, BC, Canada
Synopsis
Quantitative Susceptibility Mapping has shown great potential to be used
for clinical diagnoses due to its high sensitivity to change and high
spatial resolution. Notably, the ability to quantify damage has been
appealing. However, attributing susceptibility increases or decreases to
certain mechanisms has been challenging. In particular, interpretation of
MR signal changes during multiple sclerosis lesion formation is lacking
consistency and histological validation. Here, we investigated the
hypothesis that apparent changes of the lesion tissue may be in fact due
to changes in the lesions vicinity and caution is required when
interpreting the quantitative susceptibility signal in multiple sclerosis
lesions.Purpose
Susceptibility-weighted
imaging has become an important tool for the detection of hemorrhages
and iron accumulation in the brain
1,2. In its quantitative
form, R2*, MR frequency shift imaging and quantitative susceptibility
mapping (QSM) have been used for the assessment of tissue damage in
multiple sclerosis (MS) lesions
3,4,5. Increases in the
frequency and susceptibility signal have been attributed to iron
accumulation
5,6,7, with demyelination as a potential
confounder and not always supported by corresponding histology
8.
A recent study utilized non-local magnetic field changes
around bulk susceptibility inclusions as a measure of iron content in
MS lesions
9 and concluded that iron is a rare source of
contrast in agreement with histological studies
10. While
these results are in qualitative agreement, MR-histology correlations
showed little overlap between non-local effects and actual iron
content
11. We hypothesize that this discrepancy may be
resolved by considering susceptibility changes in the surrounding
normal appearing white matter (NAWM).
Methods
Single
Gradient-echo MR images of 4 fixed post-mortem samples were acquired
at 3T at TR/TE=40/20ms, flip angle=30 and acquisition voxel
size=0.5x0.5x1mm
3, reconstructed to 0.42x0.42x0.5mm
3. Subsequently,
the tissue blocks were embedded in paraffin and cut according to MRI
planes. Luxol-fast blue-periodic-acid Schiff myelin and turnbull blue
iron staining was performed on adjacent slices. We estimated average
iron and myelin densities in the center of MS lesions and their
vicinity on the digitalized histological sections. Additionally, we
performed simulations of MR frequency shifts using a simple spherical
model in a box with changes in the tissue's magnetic susceptibility
affecting independently only the sphere ('lesion'
,
upper row in each part of the simulation
) or only the
surrounding box (NAWM
,
bottom row of each simulation
). All susceptibility maps were forward field
calculated with independent addition of gaussian noise to the real
and imaginary parts of the signal. All MR images and simulated field
maps were unwrapped using a Laplacian unwrapping algorithm
12,
followed by background field removal using PDF
13.
Susceptibility maps were computed by solving of the inversion problem
using an LSQR approach
12.
Results
Our
simulations demonstrated that with changes in the surrounding NAWM
alone (Fig. 1, susceptibility model), the lesional tissue will appear
more paramagnetic, creating the same dipolar field modification as
observed for actual iron accumulation (Fig. 1, PDF frequency), which
is in turn reflected as falsely elevated magnetic susceptibility on
QSM. Such a diamagnetic shift of the surrounding tissue can occur
through strong demyelination of the lesion and maintained myelin of
the WM (Δ
myelin↑=Myelin
WM-Myelin
Lesion).
Accounting for iron, the lesion will appear less paramagnetic the
more iron is lost (Δ
iron↑=Iron
WM-Iron
Lesion),
while iron loss of the NAWM will strengthen the dipolar appearance
(Δ
iron↓). However, demyelination of the NAWM is
expected to a certain degree.
Our
post mortem study showed little correlation between frequency shifts
observed in MS lesions with either diffuse or cellular iron content
(R= -0.17 & R= 0.37). In contrast, 13/15 lesions demonstrated
iron loss compared to the surrounding NAWM.
Figure
2 shows two lesions with comparable iron and myelin densities in
their centers, but in different scenarios regarding their NAWM state.
The upper row (A/B) corresponds to a lesions that showed dipolar
field modifications, while the lesion in the bottom row (C/D) did not
show any non-local features. Lesion 1 (A/B) shows high Δ
myelin,
while Δ
iron is low compared to most other lesions. In
contrast, Lesion 2 (C/D) shows complete demyelination and iron loss,
with partial myelin and iron loss of the NAWM causing Δmyelin
to be lower than in Lesion 1, while Δiron was
approximately the double compared to Lesion 1.
Discussion
While
increases in resonance frequency within MS lesions are also
concordant
with the theory of microstructural changes during myelin debris
formation and during the presence of myelin debris
3,14,
debris formation is mainly expected in younger, more active lesions.
Local frequency shifts due to iron-rich marcophages can occur,
however we observed that local accumulation of such macrophages
causes the MR signal to change in only parts of the lesions, rather
than throughout.
Conclusion
MR
frequency shift data and QSM of MS lesions need to be interpreted
with caution. Apparent increases in the MR susceptibility signal in MS lesions
rarely relate to actual increases in magnetic susceptibility, and may
in fact be the result of changes of non-local origin, such as demyelination of NAWM tissue.
Acknowledgements
No acknowledgement found.References
[1] Deistung et al., Z Med Phys
16; 2006 [2] Langkammer et al., NeuroImage 62; 2012 [3] Wiggermann et
al., Neurology 81; 2013 [4] Sati et al., NeuroImage 51; 2010 [5]Chen
et al., Radiology 271; 2014 [6] Wisnieff et al., Magn Res Med 74;
2015 [7] Rudko
et al., Future Neurology 9;
2014 [8]
Walsh et al., Radiology 267; 2013 [9]
Wiggermann et al., Proc
Intl Soc Mag Reson Med 0894;
2014
[10]
Hametner et al., Annals of Neurology 74; 2013 [11] Elkady et al.,
Proc Intl Soc Mag Reson Med 0281; 2015 [12] Li et al., NeuroImage 55;
2011 [13] Liu et al., NMR in Biomed 24; 2011
[14] Yablonskiy et al., PNAS 109;
2012