Björn Lampinen1, Ariadne Zampeli2, Filip Szczepankiewicz3,4, Kristina Källén5, Maria Compagno Strandberg2, Isabella Björkman-Burtscher6, and Markus Nilsson3
1Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden, 2Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden, 3Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden, 4Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 5Clinical Sciences Lund, AKVH-Neurology Helsingborg, Lund University, Lund, Sweden, 6Radiology, Sahlgrenska university hospital, Gothenburg, Sweden
Synopsis
MRI is central to
presurgical workup for malformations of cortical development (MCD) but findings
are ambiguous on morphological imaging. For example, assessments on cortical
thickness may disagree with histology. We investigated whether this gap may be
bridged by diffusion MRI (dMRI) with the novel ‘tensor-valued diffusion
encoding’ technique. Results from thirteen patients showed
WM-like content with high microscopic anisotropy within lesions that were uniform and
GM-like in T1- and T2-weighted images and on conventional
dMRI. As a marker of axonal content less confounded by myelination and orientation
dispersion, tensor-valued diffusion encoding may improve MCD characterization
and evaluation of cortical thickness.
Introduction
Malformations of cortical
development (MCD) are disorders of neuronal migration, organization and proliferation
and are an important cause of drug-resistant epilepsy.1 Morphological MRI plays a central role in
surgical treatment workup2 but
its interpretation can be ambiguous. For example, ‘cortical thickening’ is a
commonly reported characteristic of focal cortical dysplasia (FCD) on T1-weighted
images even though it is not described in histopathological studies.3 While T1- and T2-weighted
image intensities depend on myelination, gliosis and ectopic neurons within
subcortical WM,3,4 the
sensitivity of diffusion MRI (dMRI) to the anisotropic diffusion within axons5 could potentially bridge this gap. dMRI
has previously been challenging within incoherent structures such as MCD where microscopic
anisotropy is confounded by orientation dispersion,6,7 but the novel ‘tensor-valued diffusion encoding’ technique
overcomes this limitation.8,9 Here,
we used tensor-valued diffusion encoding in four types of MCD to demonstrate both
GM-like and WM-like content within lesions that were otherwise similar in both morphological
MRI images and on conventional dMRI.Methods
Thirteen
patients with MCD (age 32 ± 13 y, 8 females) were scanned
on an Achieva 7T system (Philips, Best, The Netherlands). Tensor-valued diffusion encoding was
performed with
a prototype
diffusion-weighted spin-echo sequence10
using TR/TE =
3500/89 ms/ms, 2×2×4 mm3 resolution, and linear and
spherical b-tensors with b = 0,0.1,0.5,1.0,1.5,
and 2.0 ms/μm2
distributed over up to 16 directions. T1-weighted images were
acquired with a 3D TFE sequence using TR/TE = 8/2.8 ms/ms, flip angle = 7°
and 0.6 mm3 resolution. T2-FLAIR images were acquired with
a 3D spin-echo sequence using TR/TE = 6000/390 ms/ms, flip angle = 55°
and 1.4 mm3 resolution. dMRI data were analyzed
with the covariance tensor model9
to estimate both the (conventional) fractional anisotropy (FA) and the
microscopic anisotropy (MKA) using the multidimensional dMRI toolbox.11 All
data were coregistered to the T1-weighted images using
Elastix.12Results
Four
types of MCD were identified: periventricular heterotopias (PH), subcortical
heterotopias (SH), focal cortical dysplasias (FCD) and polymicrogyrias (PMG).
Table 1 shows their distribution among the patients and Fig. 1A shows an
overview of typical lesion manifestation per type. On the conventional MRI contrasts of T1-weighted,
T2-FLAIR and FA, the lesions were uniform and visually similar to normal
GM (Fig. 1B). On the contrary, the MKA maps revealed heterogeneity
both between and within lesions. The MKA was low and similar to that of GM in PH and in most ‘intra-cortical’ parts of MCD. Conversely, in the WM-embedded SH, in areas with WM-GM blurring in FCD and in regions
with apparently increased cortical thickness in PMG, the MKA was high
and similar that of WM (Figs. 1B and 2). Figure 3 shows histograms further emphasizing that
all lesions were GM-like on T1-weighted imaging whereas the MKA
revealed both GM- and WM-like content in all lesion types except PH.Discussion
Tensor-valued diffusion encoding revealed varying
levels of microscopic diffusion anisotropy across MCD tissue that was otherwise
similar in morphological images and on conventional dMRI. We hypothesize that
the finding reflects a varying axonal content that is confounded by myelination
and orientation dispersion in conventional contrasts. The passage of axons through
WM-embedded SH is consistent with fiber tracking results in band heterotopias13 and ‘cortex’ that appear blurry in FCD
or thick in PMG may actually represent subcortical WM with myelin pathology.4,14 This and previous studies indicate
that axons rather than dendrites drive microscopic diffusion anisotropy in the
brain (Fig. 2)15-17 and, consequently,
anisotropy was low within the ‘GM parts’ of MCD, where the axonal content
should be similar or lower compared with in normal GM14,18 but high within the ‘WM parts’.Conclusion
Microscopic anisotropy from tensor-valued diffusion
encoding may provide a marker of axonal content unconfounded by the level of myelination,
which strongly affects morphological T1- and T2-weighted
images. As the sequence can be performed in just three minutes19 and is available at common clinical
MRI systems10, the technique may
allow clinically feasible characterization of MCD and adjacent WM useful in presurgical
workup, as well as an improved evaluation of cortical thickness in general. Future
studies will investigate whether the sensitivity to axonal content can be used
to identify ‘MRI-invisible’ lesions.Acknowledgements
We thank Philips for providing access to the
pulse programming environment. The study was supported by grants from the Swedish
Research Council (2016-03443).References
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