Optimization and application of bipolar gradient for flow-suppressed hyperpolarized 13C CSI in mouse liver at 9.4T
Hansol Lee1, Joonsung Lee2, Eunhae Joe1, Seungwook Yang1, Jae Eun Song1, Young-suk Choi3, Eunkyung Wang3, Ho-Taek Song3, and Dong-Hyun Kim1

1Department of Electrical & Electronic Engineering, Yonsei university, Seoul, Korea, Republic of, 2Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, Korea, Republic of, 3Department of Radiology, Yonsei University College of Medicine, Seoul, Korea, Republic of

Synopsis

In hyperpolarized 13C MRI, high signal intensity of vasculature can cause errors in quantification of metabolites or conversion rate constants. The bipolar gradient was used to suppress vascular signal for accurate quantification. However, the velocity of vessel can vary depending on anesthetic level and pulsation. Furthermore, additional T2* relaxation signal loss can be induced by delayed data acquisition in ultra-high field (9.4T) due to short T2*. In this study, the bipolar gradient was optimized to minimize additional signal loss and mitigate variable velocity, then the optimized bipolar gradient was implemented for hyperpolarized 13C CSI and applied to mouse liver experiment.

Purpose

In hyperpolarized 13C MRI, quantification of metabolites or conversion rate constants is used as a marker for assessing metabolic activities in vivo1,2. In these quantitative applications, high vasculature signal can interfere with surrounding tissues, leading to quantification error. To reduce the contamination coming from vessels, previous research used bipolar gradient to suppress the vasculature signal3,4. However, the velocity of vessel can vary depending on the anesthetic level as well as pulsation. In addition, the delayed data acquisition by the insertion of bipolar gradient could cause severe signal loss in ultra-high field (9.4T) due to short 13C T2* relaxation time (~20ms). In this study, simulations were performed to optimize the bipolar gradient with respect to velocity and T2*, then the velocity-optimized bipolar gradient was implemented in conventional chemical shift imaging (CSI) for application in hyperpolarized 13C mouse liver experiment.

Method

Simulation

Signal suppression of flowing spins by bipolar gradient was modeled by $$$\phi_{v}=\gamma m_{1} v(x)$$$ and $$$S_{flow}=S_{0}(1-\int_{voxel}^{}exp(-t/T_2^*)\times exp(-i\phi_{v})dv)$$$, where $$$\phi_{v}$$$ is a velocity-dependent phase accrual, $$$m_{1}$$$ is the 1st gradient moment, $$$v(x)$$$ is velocity at position $$$x$$$ in voxel, and $$$S_{0}$$$ is the signal in the absence of bipolar gradient.3 The velocity within the voxel was assumed to follow a laminar distribution. Also, T2* related signal loss of static spins was simulated by $$$S_{T_2^*}=S_{0}exp(-t/T_2^*)$$$. 13C T2* of 21.2ms was used, which was obtained from separate scans of 13C CSI (data not shown). Since there is a trade-off between flow suppression and T2* relaxation, an efficiency term for flow suppression was defined as $$$E_{fs}=(S_{flow}/S_{0})\times (S_{T_2^*}/S_{0})$$$. The simulation was performed with varying bipolar gradient pulse width (0.01~4.5ms) and velocity (0.01~4.5cm/s) (Fig.1b). In this simulation, fixed gradient amplitude of 352mT/m, corresponding to 80% of maximum gradient strength, was used to minimize bipolar gradient duration.

In vivo Experiments

All experiments were performed on a 9.4T small animal imaging system (Bruker BioSpin MRI GmbH, Germany) equipped with 1H-13C dual-tuned mouse volume transmit/receive coil. [1-13C] pyruvic acid doped with 15mM Trityl radical and 1.5M Dotarem was polarized for 1h using HyperSense polarizer (Oxford Instruments, Oxford, UK). Samples were dissoluted with Tris/EDTA-NaOH solution, and approximately 350ul of pyruvate was injected into Balb/c mouse through tail vein catheter over duration of 5s. The bipolar gradient was inserted in alternate TRs in the direction of slice-selection after slice-selective excitation as shown in Fig.1a. Prior to flow suppression experiments, velocities of vessels flowing through the selected slice were measured to optimize the bipolar gradient using phase-contrast MRI (PC-MRI). For validation of flow suppression, 1H fast low-angle shot (FLASH) with interleaved acquisition was performed (TR=250ms, TE1/TE2=5.3/13.3ms, FA=30, Gamp=88mT/m, δ=3.9ms). For hyperpolarized 13C experiments, flow-suppressed CSI in the presence (TR1/TE1=89/8.1ms) and absence (TR2/TE2=81/1.1ms) of bipolar gradient was performed on mouse liver. The slowest velocity of vessels was measured as 2.2cm/s. The optimal pulse width (δ) of bipolar gradient for the slowest velocity was determined to be 3.3ms (Fig.1c). Other scan parameters were set as follows: FoV=28×28mm2, matrix size=16×16, FA=10°, spectral bandwidth=6510Hz, sampling point=512, NEX=2, Gamp=352mT/m. The scan was started at 30s after injection of hyperpolarized [1-13C] pyruvate.

Results

Flow suppression using bipolar gradient was validated in 1H imaging as shown in Fig.2. High signal intensity in the vasculature was observed in the absence of bipolar gradient (Fig.2a). With the implemented bipolar gradient, the signal from flowing spins was suppressed (Fig.2b). Peak SNR (PSNR) maps of each metabolite were obtained from the flow-suppressed CSI data (Fig.3). The signal of pyruvate and lactate in the vasculature was suppressed by 88%. In liver tissue, pyruvate and lactate PSNR was reduced by 34.7% and 29.4%, respectively, resulting in PSNR of 23.4±4.4 for pyruvate, and 14.8±3.7 for lactate. While the signal reduction of lactate signal was comparable to the simulation result as expected from the T2* relaxation (27% reduction), increased reduction of pyruvate signal was observed. The large reduction of pyruvate was attributed to decreased contamination by flow suppression.

Discussion and Conclusion

Signal contamination from vasculature was reduced using bipolar gradient implemented for hyperpolarized 13C CSI in mouse liver. To minimize signal loss arising from T2* and mitigate the variability in each experiments, the bipolar gradient was optimized with respect to velocity and T2*. Although additional signal loss is introduced in stationary tissues by both T2* relaxation and diffusion sensitization, diffusion related signal loss was ignored in this study because the b-value used for flow suppression was relatively low compared to diffusion weighted imaging (DWI)3. As a future work, this technique can also be applied to other organs which require accurate quantification of metabolism in hyperpolarized 13C studies.

Acknowledgements

No acknowledgement found.

References

1. Golman K, et al. Metabolic Imaging by Hyperpolarized 13C Magnetic Resonance Imaging for In vivo Tumor Diagnosis. Cancer Res. 2006;66:10855-10860.

2. Day SE, et al. Detecting tumor response to treatment using hyperpolarized 13C magnetic resonance imaging and spectroscopy. Nat Med. 2007;13:1382-1387.

3. Gordon JW, et al. Application of flow sensitive gradients for improved measures of metabolism using hyperpolarized 13C MRI. Magn Reson Med. 2015;early view.

4. Lau AZ, et al. Cardiac perfusion imaging using hyperpolarized 13C urea using flow sensitizing gradients. Magn Reson Med. 2015;early view.

5. Bernstein, et al. Handbook of MRI Pulse Sequences. 2004

Figures

(a) The scheme of flow suppression by insertion of bipolar gradient in the direction of slice-selection. (b) An efficiency of flow suppression is illustrated as a function of velocity and bipolar gradient pulse width (δ). The efficiency for v=2.2cm/s is plotted in (c), resulting in δ of 3.3ms.

1H FLASH images in the absence (a) and presence (b) of bipolar gradient. High signal intensity of vasculature signal (thoracic aorta (TA), caudal vena cava (CVC), portal vein (PV)) was suppressed by the bipolar gradients. The velocities of vessels were measured using PC-MRI as shown in (a).

Peak SNR (PSNR) maps of each metabolite without (a,b) and with (c,d) flow suppression. The vasculature signal was suppressed by bipolar gradient. In liver tissue, PSNR was reduced by 34.7% and 29.4% for pyruvate and lactate, respectively (PSNR = 23.4±4.4 for pyruvate and 14.8±3.7 for lactate with flow suppression).



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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