Giorgia Milotta1, Gastao Cruz2, Radhouene Neji2, Claudia Prieto2, and Rene Botnar2
1University College London, London, United Kingdom, 2King's College London, London, United Kingdom
Synopsis
Quantitative T1 and T2
mapping has shown promising results in the quantification of liver fibrosis and
inflammation, whereas proton density fat fraction mapping has been used to
quantify the hepatic lipid content in fatty liver diseases. Conventionally multiple
sequential 2D breath-held scans are performed to acquire sequential 2D T1, T2
and fat fraction maps. However, this approach suffers from limited spatial
resolution and coverage and potential misregistration errors. In this work, we
sought to develop a free-breathing non-rigid motion corrected 3D sequence for
simultaneous and co-registered acquisition of joint liver T1, T2 and fat
fraction maps for quantitative tissue characterization
Introduction
Quantitative T1 and T2 mapping has shown promising results in the identification and quantification of liver fibrosis and inflammation1, whereas proton density fat fraction mapping has been used to quantify the hepatic lipid content in fatty liver diseases2. Conventionally multiple sequential 2D breath-held scans are performed to acquire 2D T1, T2 and fat fraction maps separately. However, this approach suffers from limited spatial resolution and coverage and potential misregistration errors. In this work, we sought to develop a free-breathing non-rigid motion corrected 3D sequence for simultaneous and co-registered acquisition of joint liver T1, T2 and fat fraction maps for quantitative tissue characterization. Methods
The proposed framework
is shown in Figure 1. Four interleaved volumes are acquired with variable density
Cartesian trajectory3,4,
three-point Dixon GRE readout and 1) IR-preparation, 2 and 3) no-preparation,
4) T2-preparation respectively. 2D low-resolution image based navigators
(iNAVs)5 are
acquired prior to imaging to estimate and correct for shot-to-shot translational
respiratory motion, enabling 100% scan efficiency. A 3D bin-to-bin non-rigid motion
corrected multi-contrast patch-based low-rank reconstruction (non-rigid
HD-PROST)6 is
performed to jointly reconstruct the acquired echoes. A water-fat separation
algorithm7 is used
to generate water and fat images for each dataset, and the four water images
are used to obtain the signal evolution across the four acquired volumes. Extended
phase graph (EPG) simulations8, matching
the acquisition parameters, are carried out to generate a simulated dictionary
and quantitative water T1 and T2 maps are generated by
matching each voxel measured signal evolution to the closest dictionary entry9.
Fat fraction and M0 maps are obtained from the water-fat separation
algorithm. Five healthy subjects were scanned on a 1.5T scanner (Siemens
Magnetom Aera) to validate the proposed free-breathing sequence. Sequence
parameters included: coronal orientation, Dixon encoded GRE readout, FA = 8
degrees, 14 echoes for iNAV acquisition, isotropic resolution of 2mm3 and
~6min scan time. Three subjects were acquired with in-out-phase dual echo Dixon
encoding (TE1/TE2 = 2.38/4.76ms) to test T1
and T2 encoding of the acquisition scheme and the non-rigid motion
corrected reconstruction. Two additional subjects were acquired with a 3-point Dixon
encoding (TE/ΔTE=2.0/1.36ms) allowing to reconstruct 3D fat fraction and M0
maps in addition to 3D T1 and T2 maps. Results
Water T1 and T2 maps and fat volume obtained with and
without non-rigid motion correction are shown for one healthy subject in coronal,
sagittal and transversal views in Figure 2. Depiction of small vessels and
increased sharpness is obtained with non-rigid motion correction in every
reformatted view. Good agreement in T1 and T2 values was obtained within a ROI
in the liver with and without motion correction (T1MOCO = 601±15ms,
T2MOCO = 62±2ms and T1NO_MOCO = 669±32ms, T2NO_MOCO
= 56±4ms), although a reduced spatial variability was observed with non-rigid
motion correction.
T1, T2, fat fraction and M0 maps for one healthy
subject acquired with 3-point Dixon are shown in Figure 3 in coronal, sagittal
and transversal orientation. T1 = 704±30ms and T2 = 58±3ms
were measured within a ROI in the liver and are in good agreement with
literature values10. Fat
fraction of 3.3±1.7% and 88±3% were measured in the liver and subcutaneous fat
respectively. Conclusion
Preliminary results of the proposed non-rigid motion
corrected joint T1/T2 and fat fraction mapping sequence
showed the feasibility of obtaining free-breathing 3D T1, T2, fat fraction and
M0 maps in a clinically feasible scan time of less than 6 minutes. Non-rigid
motion correction increased image sharpness and reduced T1 and T2 variability,
allowing the acquisition of T1 and T2 maps in agreement with literature values.
Future work will include the acquisition of a larger cohort of subjects with 3
point Dixon encoding and comparison with biopsy and standard T1, T2
and fat fraction mapping techniques for clinical validation of the proposed
technique.Acknowledgements
This work was supported by the following grants:
(1) EPSRC EP/P032311/1, EP/P001009/1 and EP/P007619/1, (2) BHF programme grant
RG/20/1/34802, (3) King’s BHF Centre for Research Excellence RE/18/2/34213 (4)
Wellcome EPSRC Centre for Medical Engineering (NS/A000049/1). References
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