Michael G Crabb1, Karl P Kunze1,2, Carlos Castillo-Passi1,3, Camila Munoz1, Carlos Velasco1, Radhouene Neji1,2, Claudia Prieto1,3, and Rene M Botnar1,3,4
1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom, 3Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile, 4School of Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
Synopsis
Keywords: Myocardium, Low-Field MRI
Native T1 and T1ρ mapping has shown promising
results for the detection of focal and diffuse myocardial fibrosis without
requiring contrast agents. However, conventional myocardial maps are acquired
sequentially in 2D at 1.5T/3T fields. 3D joint T1/T1ρ mapping has recently been
proposed at 1.5T, but not demonstrated at lower field, which could potentially
make cardiac MRI more accessible and affordable. Furthermore, lower T1
relaxation times, reduced SAR and fewer B0/B1 inhomogeneities make low-field
MRI an attractive alternative for joint T1/T1ρ mapping. Here, we investigate
the feasibility of novel 3D whole-heart joint T1/T1ρ mapping on the latest
0.55T MR scanner generation.
Introduction
Native T1 and T1ρ mapping has shown promising results for the
detection of focal and diffuse myocardial fibrosis without the need of contrast
agents1,2. However, conventional myocardial maps are acquired
sequentially in 2D breath-hold scans with limited heart coverage at 1.5T or 3T
fields. A 3D whole-heart joint T1/T1ρ mapping sequence with
Dixon encoding has recently been proposed at 1.5T3. However, this approach
has not been demonstrated at lower fields, which may provide more affordable
access to cardiac MRI in the future4. Furthermore, lower T1
relaxation times (improved T1 sensitivity), reduced SAR (higher spin-locking
frequencies) and fewer B0/B1 inhomogeneities (fat-water separation) make
low-field MRI an attractive alternative for joint T1/T1ρ mapping5.
Here, we investigate the feasibility of a novel free-breathing, 3D whole-heart
joint T1/T1ρ mapping sequence with Dixon encoding to provide native 3D T1 and T1ρ
maps with isotropic resolution and co-registered water and fat volumes for
myocardial tissue characterisation on the latest 0.55T MR scanner generation.Methods
The ECG-triggered 3D joint
T1/T1ρ
research sequence (Fig. 1) consists of a repeating
set of preparation modules over 4 heartbeats (HBs): IR preparation (TI=245ms),
no preparation, no preparation and T1ρ
preparation (spin-lock duration(TSL)/amplitude(fSL)=40ms/175Hz).
A 2-point Dixon GRE read-out (TE1/TE2/TR=2.6/6.5/9.7ms,
flip angle=8o, bandwidth=451 Hz/pixel, spatial resolution 2 mm isotropic) is
used every HB to acquire pseudo in-phase (IP) and opposed-phase (OP) echoes. A 4x
undersampled variable-density Cartesian trajectory with spiral profile order and
golden angle step6 is used to acquire the 3D data. 2D image
navigators (iNAVs)7 acquired prior to each spiral are used to
perform beat-to-beat translational respiratory motion estimation and correction,
as well as to bin the 3D data into 4 equally populated respiratory bins for
estimation of bin-to-bin 3D non-rigid motion8. The 8 3D image
contrasts (pseudo IP and OP echoes for each HB) are reconstructed using
non-rigid motion correction with patch-based multi-dimensional low-rank
regularisation (HD-PROST)9. Water and fat images are estimated from
the reconstructed IP/OP HB images10. An EPG simulation11 was
used to generate a dictionary with Np~6.7k T1/T1ρ parameter combinations, and
mapping was performed voxel-by-voxel by maximising the inner-product of the
dictionary and water HB images. Research 2D MOLLI12 and 2D T1ρ13 maps
were acquired during a breath-hold at 0.55T and used as a reference to compare
with proposed 3D joint T1/T1ρ values. For 2D T1ρ reference, the sequence13
was adapted from a bSSFP readout with Fat-Sat at 1.5T to a 2-echo Dixon GRE
readout (TE1/TE2/TR=2.6/6.2/9.5ms,
flip angle=20o) at 0.55T. Four
T1ρ-contrasts were acquired (TSL=5,15,30,40 ms) in a total of 12 HB
breath-hold sequence. Mono-exponential fitting of reconstructed water contrast
images was used to estimate a 2D T1ρ map. For 3D joint T1/T1ρ and 2D T1ρ, TSL was limited to 40ms (with
fSL=175 Hz) due to the maximum power of the RF amplifier available
in the scanner.
Data was acquired on a 0.55T MR
scanner (MAGNETOM Free.MAX, Siemens Healthcare, Erlangen, Germany) on phantoms
with varying simulated heart rate (HR) and on 4 healthy
subjects.Results
Phantom experiments show good agreement
with 2D MOLLI and 2D T1ρ with good precision for both proposed T1 and T1ρ values for high HRs (Fig. 2). In-vivo experiments on 4 healthy subjects (HR = 58±4
bpm), with an acquisition window of ~150
ms at mid-diastole resulted in a total scan-time of ~12.3±1.6 mins. 3D water, fat, T1 and T1ρ maps estimated with the
proposed approach for a representative subject are shown in Fig. 3 in both
mid-coronal as well as in short-axis (SAx) views through the 3D reconstruction.
Mid-ventricular SAx views of the proposed 3D T1/T1ρ maps, 2D MOLLI and 2D T1ρ
for 2 subjects are shown in Fig. 4, showing good
qualitative agreement with the references. Fig. 5 illustrates a comparison
across all 4 healthy subjects. For T1, values (818±61 ms) with the
proposed sequence are higher than 2D MOLLI (740±35 ms), and for T1ρ values (52.4±6.7 ms) with the
proposed sequence are smaller than 2D T1ρ (69.5±12.2
ms).Conclusions
Preliminary 3D whole-heart
joint T1/T1ρ
mapping results demonstrate good agreement with 2D MOLLI and 2D T1ρ reference values in phantoms,
and promising results in-vivo at 0.55T. Further work will include validation
in phantoms using 2D spin-echo reference measurements, and acquisition of a
larger cohort of healthy subjects and patients with suspected cardiovascular
disease.Acknowledgements
This work was supported by the following grants: (1) EPSRC P/V044087/1;
(2) BHF programme grant RG/20/1/34802, (3) Wellcome/EPSRC Centre for Medical
Engineering (WT 203148/Z/16/Z), (4) Millennium Institute for Intelligent
Healthcare Engineering ICN2021_004, (5) FONDECYT 1210637 and 1210638, (6)
IMPACT, Center of Interventional Medicine for Precision and Advanced Cellular
Therapy, ANID FB210024.References
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