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Feasibility of Free Breathing Quantitative Susceptibility Mapping of the Liver: Comparison with a Breath-Hold Acquisition1Cornell University, Ithaca, NY, United States, 2Weill Cornell Medicine, New York, NY, United States, 3Northern Jiangsu People's Hospital, Yangzhou, China
Synopsis
Quantitative Susceptibility Mapping (QSM) enables accurate non-invasive monitoring of liver iron to guide iron-chelation therapy. Feasibility of a breath-hold sequence has been demonstrated in healthy subjects and in patients. In this work we investigate feasibility of a free-breathing navigator sequence in healthy volunteers to generate QSM maps and compare its correlation with the breath-hold sequence.
INTRODUCTION
Quantitative Susceptibility Mapping (QSM) is an emerging non-invasive MRI method to quantify iron, calcium and other susceptibility sources (1,2). In patients with transfusional iron overload, QSM enables accurate non-invasive monitoring of liver iron to guide iron-chelating therapy. Its feasibility using a breath-hold sequence (~ 30 sec) has been demonstrated in healthy subjects and in patients (3). However, in certain populations, such as pediatric and elderly patients, breath-hold compliance is lower leading to a higher failure rate. In this work, we investigate the use of a free-breathing navigator sequence to overcome the breath-hold requirement. In 6 healthy volunteers, we compared the QSM and R2* obtained using breath-hold and free-breathing data acquisitions.METHODS
Both breath-hold and free-breathing liver QSM acquisitions were performed on a 3 T scanner (Discovery MR750, GE Healthcare, Waukesha, WI) with a 32-channel body coil. In breath-hold (BH) sequence a multi-echo 3D gradient-recalled echo (GRE) sequence was used with the following imaging parameters: number of echoes = 5, unipolar readout gradients, flip angle = 3, TE1 = 2.9 msec, ΔTE = 3.4 msec, TR = 20.1 msec, reconstructed voxel size = 1.56 × 1.56 ×7 mm3, bandwidth (BW) = 390 Hz/pixel, acquisition matrix = 256 × 160 × (28-36), ASSET acceleration factor= 1.25, and acquisition time of 33–38 sec. The free-breathing (FB) sequence employed a pencil-beam diaphragmatic navigator to track respiratory motion (4,5). A 2-bin phase-ordered automatic window selection (PAWS) gating algorithm (4mm effective gating window) was used to tailor data acquisition according to diaphragm position in real-time (6). The remaining acquisition parameters were identical to the breath-hold acquisition with TE1=2.1ms, no acceleration and scan time of ~3 minutes.The T2*-IDEAL problem estimates fat content (F), water content (W), susceptibility induced field (f) and R2* decay by modeling the complex GRE signal shown in Eq. 1. We used out-of-phase echoes (∆TE= 3.4 msec at 3T) to calculate initial guesses (3).
$$(W,F,f,R_2^* )=argmin\sum_{j=1}^n|{S(t_{j})-e^{-R_2^*t_{j}}e^{-i2{\pi}ft_{j}}(W+F)e^{-i2{\pi}\nu_{f}t_{j}}}|^2_2 [1]$$
A QSM map was reconstructed using the MEDI algorithm (3,7),
$$\chi=argmin|{w(e^{-if}-e^{-i(d*\chi)})}|^2_2+{\lambda_1}|{M_{G}\triangledown\chi}|_1+{\lambda_2}|{M_{aorta}(\chi-\overline{\chi_{}}_{aorta})}|^2_2 [2]$$
assuming Gaussian noise (8), w the noise weighting, f the local field, d the dipole kernel, $$$M_G$$$ the binary edge mask, $$$\lambda_{1,2}$$$ regularization parameters, and $$$M_{aorta}$$$ the binary mask of abdominal aorta used for zero-referencing (9).
In all subjects 3 axial slices depicting approximately the same part of the liver were used for ROI analysis. 3 ROIs were drawn on the liver avoiding vasculature. R2*, and susceptibility values in the liver were calculated and compared between the BH and FB acquisitions. Linear regression (slope ,coefficient of determination ) and Bland-Altman analysis (bias and 95% limits of agreement LoA) were performed to compare the two methods.
Results
In all volunteers and both breath-hold and free breathing scans, data acquisition, water/fat separation and QSM reconstruction were performed successfully, with minor motion artifacts observed in one subject.In Figure 1, , and susceptibility maps in a healthy subject with both BH and FB scans show good agreement across the two scans
Figure 2 shows linear regression and Bland-Altman analysis in liver ROIs in R2* and QSM maps comparing breath-hold with free breathing acquisitions. R2* ranged from 35.7 to 76 Hz with good agreement between the two methods. QSM ranged from -0.23 to 0.19 ppm with good agreement among the two methods.
CONCLUSION
Our data indicate that free-breathing data acquisition is a viable option for patients who are unable to hold their breath during the scan.Acknowledgements
No acknowledgement found.References
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