Eamon K Doyle, MS1, Jonathan M Chia, MS2, Krishna S Nayak, PhD3,4, and John C Wood, MD, PhD4,5
1Biomedical Engineering, University of Southern California, Sierra Madre, CA, United States, 2Philips Healthcare, Cleveland, OH, United States, 3Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 4Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 5Cardiology, Children's Hospital of Los Angeles, Los Angeles, CA, United States
Synopsis
R2 (1/T2) and R2* (1/T2*) are useful metrics related to tissue iron loads. Clinical iron estimation at 3T is limited by the achievable echo times in Cartesian spin echo and gradient echo imaging. We present a modified CSI spectroscopy sequence robust to motion for high SNR liver R2* estimation with the potential for simultaneous R2 estimation.Introduction
In clinical tissue
iron estimation, R2* (1/T2*) provides important information about iron load.[1] However, the dynamic range of iron
quantitation is limited by the duration of the readout. The effective dynamic
range of iron concentrations is up to 40 mg/g dry weight at 1.5T, and up to 20
mg/g at 3T. Spectroscopic sequences such as CSI may overcome these limitations by
eliminating frequency encoding and allowing complete sampling of the R2* envelope
from a spin echo. We propose a modified CSI sequence that provides high SNR data
for R2* measurement. The proposed
protocol uses 3 free-breathing scans, which improves patient comfort, decreases
scan time, and increases dynamic range relative to standard gradient echo-based
R2* imaging.
Methods
A CSI spectroscopy
sequence with phase encoding in 2 directions with no readout gradient (Figure
1) was modified to use an excitation pulse based on a Dolph-Chebyshev window
function to reduce echo time while maintaining slice selectivity. Scanning was performed in iron-loaded human research
subjects as part of an IRB-approved study.
The following parameters were used in all acquisitions: voxel =
20x20x15mm, 1024 samples, 32/2kHz sampling/spectral BW, 90° slice-selective
excitation, 180° non-selective inversion, matrix=8x7, and TE/TR=[3.1,7.0,13]/1000ms.
Reference liver iron levels were determined from clinically indicated MRI
examinations for iron overload at 1.5 Tesla. Studies were performed on a 1.5T
Achieva (SW R3.2.2, Philips) with a 16 element SENSE Torso XL coil. A 3-slice,
single gradient echo scan was acquired with the following parameters: 16 echoes
linearly spaced echoes with TE/TR=0.96-11.47/50ms, FA=30°, matrix=72x67,
voxel=1.25x1.25x10mm, BW=4409Hz/px.
Voxelwise R2* was estimated from CSI data by fitting
free induction decays (FID) with a mono-exponential plus constant model with
nonnegativity constraints on S0 (signal intensity at t=0), R2*, and
noise bias using nonnegative least squares in MATLAB (Mathworks, Natick, MA). R2*
values for the clinical images was estimated using a truncated exponential
model. CSI-based R2* estimates were compared to clinical R2* estimates to
assess accuracy.
Results
R2* estimates did
not vary systematically across the three spin echoes, allowing them to be
averaged to increase SNR. Averaged CSI
R2* estimates were plotted against reference 1.5T results in four patients (Figure
2). The solid line represents the 3T-1.5T calibration determined empirically
and by Monte Carlo modeling [2]. Overall agreement was within expected
measurement error but we will need to study patients with even greater iron
burden to evaluate the full dynamic range of the CSI sequence. Figure 3 contains
a representative example of an acquired FID and resulting fit output. All
reviewed FIDs reached the noise floor in within the first 10 ms.
Discussion
These pilot data indicate
that a modified CSI sequence may provide robust R2* estimates in heavily iron
loaded tissues. These studies were performed with the patient breathing freely;
however, breath-hold imaging could be achieved using SENSE factors of 2 in two
directions.
The CSI-R2*
measurement in the patient with the highest iron burden was slightly below the
predicted agreement with 1.5T. Further, R2* estimates did not vary systematically
with spin-echo time. We anticipated some prolongation of R2* with increase echo
time because of a length-bias effect i.e. proton species with shorter R2 would
have greater weighting with longer echo time; a similar effect in
CPGM-estimated R2 has previous been described theoretically[3] and shown in simulation.[4] Both the underestimation of high iron
loads and the lack of apparent R2 weighting may have been caused by a failure
to acquire the fasted decay signals with high off-resonance. We believe the
post-acquisition filter bandwidth of 2000 Hz was insufficient to characterize
the rapid decay at high iron burden in spite of sufficient sampling rate. Performing
the spin echo CSI sequence at several spin echo times may allow us to simultaneously
characterize R2 and R2* and potentially probe cellular iron distribution
characteristics.
In subsequent
studies, we hope to achieve robust R2 estimates by adding a longer echo time to
better capture signal decay in patients with low-to-moderate iron
overload. Further, we will increase
readout bandwidth to increase the dynamic range of R2* sensitivity. These changes will increase the dynamic range
of the sequence to measure R2* values over 4000 Hz, or 50 mg FE/g dry tissue,
the upper limit of clinical liver iron loads. Implementation on a 1.5T magnet
would reach iron loads up to 100 mg/g. Additional patient and phantom studies
are ongoing as part of an NIH-funded research study.
Conclusion
R2* estimation
using a modified CSI sequence with a shortened TE shows promise as a robust,
fast, comfortable method of performing spatially localized iron load
assessment.
Acknowledgements
This
work is supported by the National Institute of Health, National Institute of
Diabetes and Digestive and Kidney Diseases, Grant R01-DK097115. Clinical science and research support is provided by Philips Healthcare
in kind.References
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more precise than liver biopsy for assessing total body iron balance: a
comparison of MRI relaxometry with simulated liver biopsy results,” Magn.
Reson. Imaging, vol. 33, no. 6, pp. 761–767, Jul. 2015.
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of a Monte Carlo model,” Magn. Reson. Med., vol. 74, no. 3, pp. 879–883,
Sep. 2014.
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