Johanna Kramme1, Eberhard D. Pracht1, Gerard Sanroma1, Tony Stöcker1, and Monique M.B. Breteler1,2
1German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 2Faculty of Medicine, University of Bonn, Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Bonn, Germany
Synopsis
Within
the Rhineland Study we investigated and report normative brain T1-rho values
and their change over age, for a large cohort of 547 participants. Investigated
regions were GM, WM, deep gray matter and selected white matter tracts. All
investigated regions, except amygdala and accumbens, show a positive trend with
age. Total scan time was under six minutes (whole brain), showing the
feasibility to provide normative values for a wide range of brain regions in a
reasonable amount of time.
INTRODUCTION
T1-rho
mapping is sensitive to slow macromolecular interactions. It has the potential
to detect pathological changes in neurodegenerative diseases [1] or help with
tumor differentiation [2]. So far there is only one study focusing on normative
values [3] and to our knowledge no data on a large cohort of a few hundreds
participants. Therefore within the Rhineland Study [4,5], we investigated and
report normative brain T1-rho values and their changes over age for a large
cohort of 547 participants.METHODS
T1-rho (1.3mm
isotropic) as well as structural T1 weighted (MPRAGE 0.8mm isotropic) whole
brain data was acquired for 547 participants (≥30 years, mean 54±13, 302
women, 245 men) at a 3T Siemens Prisma scanner. A whole brain T1-rho weighted
fluid suppressed, three dimensional turbo spin echo sequence was used to
generate a decaying time-series (TSL = 10, 30, 50, 70, 90 ms), total scan time
of 5.50min, TR= 2600ms [6]. The time-series was denoised [7] and
afterwards fitted voxel-wise to an exponential decay, as follows: $$S(t) = S_0·e(−TSL/T1rho)$$ to obtain
T1-rho and T1-rho_error maps. For a better numerical stability, fitted voxel
values exceeding 150ms were discarded in the later posterior analysis.
Structural
T1 images were processed using Freesurfer 6.0 [8] and registered to the T1-rho maps
in order to extract the T1-rho parameters across a number of different brain
regions. The anatomical regions were defined by the aseg Freesurfer atlas. For
the white matter tracts, we used the JHU ICBM-DTI-81 atlas thresholded at 50% [9],
which was registered to each respective T1-rho map. Average T1-rho values were linear
regressed with age for the different anatomical regions. RESULTS
Figure 1
shows a T1-rho map for gray and white matter regions averaged over 10 randomly
selected participants. In the coronal image, the cortico-spinal tract can be clearly
seen. The blue regions correspond to the pallidum, characterized by small T1-rho
values.
Table 1
shows mean T1-rho values (and standard deviation) of the different brain
regions in the left and right hemisphere, as well as slope and intercept of the
regression analysis. Table 2 gives the same information for the selected white
matter tracts.
Figure 2
shows scatter-plots of average T1-rho values for cerebral cortex and pallidum
and figure 3 for cerebral WM and inferior fronto-occipital fasciculus over age.
Red points indicate women and blue points men. The lines show the linear regression
and two times the standard deviation in positive and negative direction.DISCUSSION
We report
normative T1-rho values of different gray and white matter regions in the
brain. Cerebral gray matter shows a small decrease in T1-rho across age, while white
matter shows an increase. Largest changes are found in the forceps minor and
the inferior-fronto-occipital fasciculus. Largest average T1-rho values in WM
tracts are found in the cortico-spinal tract and forceps major, both showing
only slight changes with age. This supports the hypothesis that both structures
are among the earliest to undergo myelination maturation in childhood and
therefore have higher T1-rho values at a younger age [3].
The present
study shows the same trends as Watts et al. [3], except for the Caudate,
Putamen, Pallidum and Hippocampus, where we find opposite trends. Differences
might be due to differences in sample size (larger in our study), sequence
parameters (our TR is almost half) or age range (Watts et al. includes younger
participants, starting at the age of 18). It is worth noting that some
structures, such as the juxtacortical WM, show different trends in younger
subjects (<30) compared to older ones. The strongest decrease in the cortical
GM, seems to be limited to the younger participants.
Further
improvements of our sequence should focus on cortical gray matter and regions adjacent
to CSF, where greater fitting errors occurred due to partial volume effects. As
consequence, T1-rho values in these areas tend to be higher, as seen in Figure
1. Improvements in the fluid suppression might improve the results as well as
using an increased resolution. CONCLUSION
We showed
that it is feasible to obtain whole brain T1-rho values in short scan-times and
provided normative T1-rho values for a wide range of brain regions and their
changes over age. Acknowledgements
No acknowledgement found.References
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