Marta Brigid Maggioni1, Martin Krämer1, and Jürgen R. Reichenbach1,2,3,4
1Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University, Jena, Germany, 2Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University, Jena, Germany, 3Abbe School of Photonics, Friedrich Schiller University, Jena, Germany, 4Center of Medical Optics and Photonics, Friedrich Schiller University, Jena, Germany
Synopsis
Tendons
are highly ordered tissues, mainly composed of collagen, and
characterized by very short transverse T2*
relaxation times. Even when using ultra-short echo-time imaging
sequences, quantification of T2*
is challenging as the origin and characteristics of the signal decay
in tendons is still under debate. In this work, we finely sampled the
decay of the transverse magnetization using an echo-train shifted
multi-echo ultra-short echo-time sequence with 55 echoes and applied
a complex tri-exponential model to extract T2*
constants.
Introduction
Tendons
are characterised
by a highly ordered, anisotropic structure of collagen fibers, which
results in short values of the decay of the transversal magnetization
T2*
and requires ultra-short echo-time (UTE) sequences for direct imaging
and parameter quantification. However, the sources of the signal
detected with UTE sequences are still under discussion. So far, three
possible contributions have been proposed: protons that are part of
the collagen molecule; “bound water” or protons linked with the
collagen molecule but not inherently part of it; and “free water”
or water present in the interstitial matrix and between the collagen
fibers1,2,3,4.
Recently, the possibility that the signal could originate directly
from the collagen molecules has also been investigated5
with contrasting results5,6.
Different models have been proposed and used to quantify T2*
in tendons, including mono-exponential1,
bi-exponential1,4,
three-component exponential fitting4 as wells as multi-components
models2,3.
In
this work, we applied an echo-train shifted multi-echo UTE sequence,
which finely sampled the T2*
decay with overall 55 echoes. As the signal decay curves showed clear
oscillations, possibly from multiple components with different
chemical shifts, we propose a tri-component exponential complex model
for fitting such finely sampled TE series. Methods
Fresh
Achilles tendons from four healthy sheep were excised after
euthanasia in compliance with the ethical guidelines of the legal,
local animal rights protection authorities. A 3D center-out radial
multi-echo UTE sequence7
and two 8-channels flexible NORAS Variety coils were used for the
measurements on a 3T clinical whole-body MRI scanner (Magnetom
PRISMA, Siemens Healthineers, Erlangen, Germany).
The echoes were acquired with an echo train shift technique8
that allows the acquisition of 3 echoes per repetition time while the
echoes are shifted for successive echo times. This echo-train shifted
multi-echo protocols acquired 55 TEs ranging from 0.15 ms to 11.6 ms.
Other imaging parameters were repetition-time: 20 ms, flip-angle: 18°, isotropic resolution (0.83x0.83x0.83) mm3 and the total acquisition time was 7.5 h.
Due
to the oscillatory pattern observed in the acquired data (see Fig.
1), the following tri-component exponential model was used for
voxel-wise data fitting: $$S(TE)=(S_{bw} e^{(-TE/T_{2bw}^*)}e^{(-i2πΔf_{bw}TE)}+S_{fw}e^{(-TE/T_{2fw}^*)} +\\+S_{fat} e^{(-TE/T_{2fat}^*)}e^{(-i2πΔf_{fat}TE)})e^{(-i2πΔf_{g}TE+φ_{0})}$$
where
the first component represents the short water bound to the collagen
fibers, the second the long free water and the third the contribution
of fat or fat-like components to the signal. Finally, the $$$e^{(-i2πΔf_{g}TE+φ_{0})}$$$ component takes into account the global influence of off-resonance
with $$$φ_{0}$$$ representing the initial phase offset. The choice of a complex model
and a complex fit allowed us to not only include chemical shift
information, but also to double the number of data points used for
the fit, thus adding to the robustness of the obtained results. Prior
to fitting, the reconstructed complex 3D UTE data was spatially
smoothed with a 4x4 Gaussian filter to reduce noise contributions.Results
Regions-of-interest
were chosen in the tendon, muscle and enthesis regions, as depicted
in Figure 3. The signal decays with increasing echo times in these
ROIs are plotted in Figure 1, showing clear oscillations of
multiple components with different chemical shifts. Figure 2 displays
the signal fraction maps for the three components, $$$(S_{bw}, S_{fw},S_{fat})$$$ which match the expected distribution within the tendon: more
bound-water in the mid-tendon without much free-water. Interestingly,
also the third component, supposedly describing a fat-like component
at a chemical shift of around 3.5 ppm, shows contributions within the
tendon, which when comparing with Figure 1 is responsible for the
observed major oscillation. Calculated T2*
maps for the three components are shown in Figure 3. The results of
the quantification of the T2* relaxation parameters in ROIs in the muscle, tendon and enthesis
regions are reported as means over the four samples in Table 1.Discussion and conclusion
The signal decay curves shown in Figure 1
demonstrate that the proposed complex tri-component model is able to
fit the data points acquired in the different tissues areas. The
obtained average T2*
of the tendons’ short component of 0.27±0.02
ms is
much smaller than other values reported in the literature9,10.
Reasons for this difference might be related to magic angle effects
or the used animal model compared to human studies. One further
reason for this very short T2*
might be the very fine sampling used in the current study. With the
strong oscillation observed in our study, conventional non echo-train
shifted T2*
measurements can greatly under-sample the true tri-compartment signal
decay in tendons and therefore greatly overestimate T2*.
The oscillation in the tendon signal decay appears to be caused by
fat-like components with a chemical shift of 3.5 ppm that could be
related to proteoglycans/glycosaminoglycans between the collagen
fibers. However, more detailed studies are required to investigate
further the origin of this oscillation.Acknowledgements
No acknowledgement found.References
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