Jesse Ian Hamilton1,2, Imran Rashid3,4, Sanjay Rajagopalan3,4, and Nicole Seiberlich1,2
1Radiology, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 3Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, United States, 4Medicine, Case Western Reserve University, Cleveland, OH, United States
Synopsis
Keywords: Myocardium, MR Fingerprinting, Machine Learning/Artificial Intelligence
This work proposes a high-resolution (1.2x1.2x5 mm
3)
MR Fingerprinting method for T
1, T
2, and M
0
mapping of both left and right ventricles during a breathhold, with
validation in 12 healthy subjects at 1.5T. A key component is the use of a deep
image prior reconstruction for reducing noise and undersampling
artifacts despite the decreased SNR when moving to higher resolution. Comparable myocardial relaxation
times were measured in both ventricles (LV T
1 1061+/-22ms, T
2
42.2+/-3.4ms; RV T
1 1062+/-29ms, T
2 42.7+/-2.5ms).
Higher-resolution MRF yielded slightly smaller intersubject standard deviation (SD) but larger intrasubject SD compared to a lower-resolution (1.6x1.6x8 mm
3)
MRF acquisition.
Introduction
Tissue characterization of the right ventricle (RV) is not
routinely performed as conventional sequences are typically limited to spatial
resolutions on the order of 2x2x8 mm3. While this resolution is sufficient
for imaging the left ventricle (LV), which has an average mid-ventricular wall
thickness of 7-8mm in healthy adults (1),
it is not adequate for the right ventricle (RV) at only 3-5mm thick (2).
Magnetic Resonance Fingerprinting (MRF) has been demonstrated for myocardial
tissue property mapping, although prior studies have focused on the LV due to
the demanding resolution requirements for imaging the RV (3,4).
This study demonstrates initial feasibility of 2D MRF T1, T2,
and M0 mapping of both the LV and RV at high resolution (1.2x1.2x5
mm3) in healthy subjects, enabled by a deep image prior
reconstruction.Methods
MRF Acquisition: A FISP-based sequence was
employed with variable 4-25° flip angles, inversions, and T2-preparations
collected during a 15-heartbeat breathhold with ECG triggering. Data were
acquired using two sequence variants at resolutions of 1.6x1.6x8 mm3,
as in previous work (5),
and 1.2x1.2x5 mm3, with the latter designed for imaging the RV. Table
1 gives additional sequence parameters. Data were sampled using a golden
angle (6)
spiral trajectory with 48 interleaves to fully sample k-space (7).
Due to the longer readout (5.3ms vs 3.4ms) of the higher-resolution spiral, fewer
total TRs (495 vs 705) were collected to maintain the same breathhold and scan
window duration.
MRF Reconstruction: Two reconstructions were
compared for their ability to reduce noise and undersampling artifacts. (Method
1) A dictionary incorporating cardiac rhythm timings from the ECG was generated
using a Bloch simulation with corrections for slice profile and preparation
efficiency (8)
and compressed to rank 8 using the SVD (8).
Images were reconstructed using a low-rank subspace technique with locally
low-rank (8x8 patches) regularization before performing dictionary matching (9).
(Method 2) A deep image prior (DIP) reconstruction was employed that
used a u-net to generate denoised maps without a dictionary (10).
Self-supervised training was performed by enforcing consistency with acquired
k-space data, with no need for additional training data, using 20,000
iterations with a batch size of 5 TRs and 10% dropout, implemented in
Tensorflow/Keras on a GPU.
Experiments: Twelve healthy subjects were
scanned at 1.5T (Sola, MAGNETOM Siemens) using an 18-channel cardiac array coil
and 16-channels from the spine array. Lower- and higher-resolution MRF scans
were collected at a mid-ventricular slice. MOLLI and T2-prepared
bSSFP maps were collected at the lower resolution, similar to routine clinical
protocols (11,12).
ROIs were manually drawn in the LV septum and RV wall, carefully avoiding blood
pixels. Mean T1 and T2 were compared between LV/RV and among
different imaging methods using Kruskal-Wallis tests with Bonferroni post-hoc
corrections. Intersubject standard deviation (SD) was quantified as the SD of
the mean T1 and T2 over all subjects. Intrasubject SD was
quantified by measuring the SD within each ROI and computing the mean over subjects.Results
Figure 2 shows maps from one subject using lower- and
higher-resolution MRF with SLLR and DIP reconstructions, as well as
conventional maps. The DIP reconstruction yielded improved suppression of noise
and undersampling artifacts, with substantial improvement in image quality
compared to SLLR at the higher resolution. Figure 3 shows high-resolution
MRF maps in five additional subjects.
Figure 4 summarizes the mean and intersubject SD for
LV and RV T1 and T2 over all subjects. With MOLLI, T1
values were higher in the RV (1049+/-34ms) than LV (1016+/-23ms), while T2
values using T2-prep bSSFP were comparable in the LV (48.3+/-2.2ms) and RV (49.4+/-2.8ms). With lower-resolution
MRF, T1 values were similar in both ventricles (LV 1044+/-32, RV 1035+/-31ms). The same trend was observed
with higher-resolution MRF (LV 1061+/-22, RV 1062+/-29ms), and the intersubject SD was
slightly smaller compared to lower-resolution MRF. For T2, lower-resolution
MRF measurements were slightly higher in the RV (44.0+/-3.9ms) compared to the LV (41.1+/-3.5ms). With higher-resolution
MRF, T2 values in both ventricles were comparable (LV 42.2+/-3.4, RV 42.7+/-2.5ms) and had a slightly lower
intersubject SD compared to the lower-resolution scan.
For all methods, intrasubject T1
and T2 SD were higher in the RV than LV (Figure 5). Higher-resolution
MRF had slightly larger intrasubject SD (LV T1 49.9ms, T2
3.4ms; RV T1 87.5ms, T2 5.6ms) than lower-resolution MRF (LV
T1 30.2ms, T2 2.1ms; RV T1 72.5ms, T2
5.3ms); this difference was significant only for LV T1.Discussion and Conclusions
This study demonstrated initial feasibility of high-resolution
(1.2x1.2x5 mm3) MRF T1, T2, and M0 mapping
in both the LV and RV in healthy subjects. The DIP reconstruction was critical
for suppressing and residual aliasing, considering the 2.8x lower SNR and 1.4x fewer
total TRs compared to some previous (lower-resolution) cardiac MRF studies. While RV
T1 mapping has been demonstrated using Look-Locker techniques with
respiratory navigation (13),
the proposed method provides T1, T2, and M0 maps
in one breathhold. This technique has clinical implications for assessing conditions
with RV involvement, such as arrhythmogenic right ventricular cardiomyopathy and
pulmonary hypertension (14–16).
Reduced partial volume artifacts at higher resolution may facilitate easier segmentation,
which could improve precision of myocardial T1-T2
measurements. Future work will include spiral off-resonance correction and image
quality rating comparisons.Acknowledgements
This work was supported by the Michigan Institute for Clinical &
Health Research (MICHR) Grant UL1TR002240, Siemens Healthineers, and National
Institutes of Health / National Heart, Lung, and Blood Institute (NIH/NHLBI)
R01HL163030 and R01HL153034.References
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