Paula Ramos Delgado1, Andre Kuehne2, Jason M. Millward1, Joao Periquito1, Thoralf Niendorf1,3, Sonia Waiczies1, and Andreas Pohlmann1
1Berlin Ultrahigh Field Facility (B.U.F.F), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, 2MRI.tools GmbH, Berlin, Germany, 3Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
Synopsis
Fluorine MR methods support quantification but have
inherently low SNR. To enhance
sensitivity, SNR-efficient imaging techniques such as RARE and
cryogenically-cooled surface RF coils are
used. However, transceive
surface RF coils show variation in the excitation field, impairing quantification and T1 contrast.
We previously showed improved homogeneity using a novel B1
correction method developed for 1H imaging that uses experimental data acquired with a volume
resonator. Here, we
compared it to a sensitivity-only correction and a combination of both, to evaluate
which approach yields the most accurate contrast and concentration
quantification. This work is applicable to different nuclei.
Introduction
Fluorine (19F) MRI methods have
demonstrated promising results for the non-invasive monitoring of exogenous
fluorinated labels in vivo1-8.
Given the lack of organic 19F in living tissues, the obtained signal
is highly specific and supports quantification, but it is severely reduced due
to the low signal-to-noise ratio (SNR) provided by the acquisition methods9-10.
A way to overcome the sensitivity limitations is to use a combination of
SNR-efficient imaging techniques such as RARE11 and state-of-the-art
cryogenically-cooled probes (CRP)12. However, CRPs are only
available as transceive surface coils and thus show substantial variation in
the excitation (B1+) and sensitivity (B1-)
fields12-14. This characteristic makes them impractical for
achieving meaningful quantification and tissue contrast. Previous research has
focused on retrospective B1+ correction methods which use
analytical equations that describe the relationship of signal intensity (SI)
and flip angle (FA) of particular MRI sequences. While this approach has been
successfully applied to gradient echo techniques like FLASH15-16, it is not feasible for RARE due to its more
complex train of spin-echoes and stimulated echoes for which no analytical SI
equation exists17-18. Previously we demonstrated the efficacy of a novel
method developed for 1H
imaging to correct B1
inhomogeneities in transceive surface RF coils with RARE using a numerical
model which described SI as a function of the FA and T119.
Here, we evaluate performance of this method compared to a sensitivity-only
correction method and a hybrid combination of both, to determine which approach
yields the most accurate contrast and concentration quantification. This work
is applicable to different nuclei.Methods
Sample
preparation and MR measurements
Four phantoms (50ml flasks) were prepared with two
different 1H-atom concentrations (100% water, 50%-50%
water/deuterium oxide) and two different T1 (490ms, 1525ms; achieved
via added gadolinium-based contrast agent).
Experiments were performed on a
9.4T animal MR scanner (Bruker BioSpin, Ettlingen, Germany). RARE images (TE/TR=5.1/1000ms, ETL=8, BW=50kHz,
centric encoding, resolution=(273x273)mm2, 3 axial
slices of 2mm thickness with 0.5mm gap, 30min) were acquired using a 1H
transceive surface loop RF coil. Reference power adjustments were performed on
a 2mm slice parallel to the RF coil surface. Reference images and T1 maps (RARE: 8 TRs, 200-9000ms)
were acquired using a volume resonator.
Correction
methods
Fig.1 shows a summary of the three processing
pipelines:
Model-based B1 correction: A phantom with a short T1 of 280ms was
utilized to compute a B1+ map using the double angle
method20-21 and a B1- map using the low FA approximation22-23.
A SI model was calculated from RARE scans (same parameters as above, FA between
5º-110º) of 19 NMR tubes (gadolinium-doped water mixtures, T1: 170–2600ms)
using a volume resonator. The corrected images were calculated as described
previously19.
Sensitivity correction: A RARE image
(same parameters) was acquired using the above phantom and its SI normalized. The
sensitivity of each of the remaining phantom images was corrected multiplying
by the inverse of this normalized image.
Hybrid B1 correction: B1+ correction was performed using
the model-based approach, followed by B1- correction using
the sensitivity correction method.
Performance
assessment
Concentration
quantification: the proportionality of the SI to the number of atoms was evaluated using
pairs of phantoms with different water content and the same T1 value
(Fig.2). Six random ROIs were drawn (Fig. 3C) and applied to the images (Fig. 3)
to calculate mean SI ratios ($$$\overline{SI}$$$) for 18 combinations of two ROIs for each
image. The error in
quantification was computed as $$$\frac{\overline{SI_{reference}}-\overline{SI_{corrected}}}{\overline{SI_{reference}}}\cdot100$$$ (%).
Finally, the mean error and mean standard deviation were
calculated.
T1 contrast: the same
procedure was followed using pairs of phantoms with the same water content and
different T1 values.
Results
While uncorrected images showed substantial
errors (35-44%) and variabilities in all cases, the correction methods reduced
the mean errors to less than 10% for both quantification and contrast (Fig.4-5). Sensitivity correction performed
well when calculating water content proportions at low T1 values (4.6±3.5%), closely followed by
the hybrid (5.3±3.1%) and model-based (6.4±4.8%) methods. All three methods
behaved similarly for higher T1 values, with mean errors of approximately
10%. When measuring T1 contrast, the hybrid method performed best
for both water content phantoms (2.4±1.6% high, 4.5±3.9% low). The sensitivity
correction method performed better than the model-based method for the high
water content phantom (3.1±2.8% vs. 5.7±5.1%). However for the low water
content phantom the model-based correction method performed better than the sensitivity correction method (4.7±4%
vs. 9.2±2.6%).Conclusions
Here we showed a comparison of two B1+/B1-
correction methods (model-based, hybrid) and a simple B1-
(sensitivity) correction method. All three methods performed similarly for quantifying
concentration, and all performed better for low T1 values compared
to high T1 values. One explanation for this is that with low T1
there was effectively less T1-weighting for the used TR, and thus
less correction was needed. For preserving T1 contrast, the hybrid
correction method performed better than the other two. Therefore, we suggest
using a simple sensitivity correction when quantifying the number of atoms
(e.g. of 19F-loaded nanoparticles). However, when T1
contrast is essential (e.g. 1H imaging) a hybrid B1
correction provides more accurate results.Acknowledgements
This work was supported by the Deutsche
Forschungsgemeinschaft to S.W. (DFG-WA2804) and A.P. (DFG-PO1869).References
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