2D MR Spectroscopic Imaging of the Pediatric Brain using Compressed Sensing
Rohini Vidya Shankar1, Houchun Harry Hu2, John C Chang3, and Vikram D Kodibagkar1

1Biomedical Engineering, Arizona State University, Tempe, AZ, United States, 2Radiology, Phoenix Children's Hospital, Phoenix, AZ, United States, 3Banner MD Anderson Cancer Center, Gilbert, AZ, United States

Synopsis

The spatial variations in brain metabolite concentrations can be mapped using magnetic resonance spectroscopic imaging (MRSI). The long scan times in MRSI do not permit its inclusion in pediatric imaging protocols. MRSI accelerated by compressed sensing was used to image the pediatric brain for various acceleration factors 2X-5X. The retrospectively undersampled reconstructions showed high data fidelity for up to 80% undersampling when compared with the fully sampled reference dataset. Studies are underway to prospectively acquire and validate CS accelerated MRSI data in pediatric patients.

Introduction

Magnetic resonance spectroscopic imaging (MRSI) is a useful technique for assessing the in vivo spatial profiles of various key metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help distinguish between healthy and diseased tissues, thus, providing diagnostic and prognostic information to the clinician, potentially leading to improved treatment strategies. However, MRSI scans are not accommodated in the current clinical acquisition window due to the lengthy scan time involved – a 16x16 spatial grid would require 256 phase encoding gradients to be played out. This results in a scan time of ~9-12 min depending on the TR, with a further increase in time for larger volumes. Such long scan times are particularly not desirable when imaging pediatric cases, particularly those under anesthesia. Acceleration techniques like compressed sensing (CS)1-2 allow a faithful reconstruction of the data even when the kspace is undersampled well below the established Nyquist limit, and CS has been adopted in MRSI reconstructions to reduce the scan time3. The objective of this study was to evaluate the fidelity of the CS reconstructions when applied to the MR spectroscopic imaging of pediatric patients.

Materials and Methods

All MRSI data was acquired on a Philips 3T Ingenia MRI scanner. Fully sampled MRSI data was collected on patients in the age range of 1 - 10 years, with the following acquisition parameters – 16x16x2048 grid, TE/TR = 46/1500 ms, 1 average, 10 mm slice thickness, total scan time for the fully sampled reference 1X dataset = 9 min. The kspace was pseudo-randomly undersampled to generate datasets that represented 50% (2X), 33% (3X), 25% (4X), and 20% (5X) acceleration. Retrospectively undersampled MRSI datasets were reconstructed in Matlab by employing the conjugate gradient algorithm to solve the convex optimization problem: argmin∥Fum−y∥2L1∥Wm∥1TVTV(m). The undersampled reconstructions were quantitatively compared with the 1X dataset in terms of the SNR and peak amplitudes of various brain metabolites. The error in reconstruction was quantified using the normalized root mean square error (nRMSE) metric. Minimal post processing was applied to the reconstructed datasets in jMRUI4 namely, apodization, phase correction, and removal of residual water, and the corresponding metabolite maps were generated.

Results and Discussion

Figure 1 shows the metabolite maps for NAA, creatine, and choline for various acceleration factors 1X-5X in a 9 year old female patient with no abnormalities detected. Figure 2 depicts the metabolite maps following quantification in a 10 year male with a brain tumor. In both cases, the CS reconstructions for various acceleration factors demonstrate good fidelity with the fully-sampled reference dataset, with negligible reconstruction errors. The error in reconstruction, as quantified by the normalized RMSE, is illustrated for both cases in Figure 3 and is below 2% for reconstructions up to 5X. All twelve patient datasets retrospectively tested using the CS-MRSI reconstruction algorithm showed very low reconstruction errors till 5X, indicating the robustness of the reconstruction.

Conclusion

The feasibility of CS-MRSI in pediatric patients has been demonstrated, with the accelerated reconstructions showing negligible errors. Further studies currently underway focus on prospective CS acquisitions on the scanner and on improvements in the reconstruction algorithm.

Acknowledgements

No acknowledgement found.

References

[1] Donoho, Information Theory, IEEE Transactions on, 2006; 52(4): 1289-1306. [2] Lustig et al, MRM, 2007; 58 (6): 1182-1195. [3] Geethanath et al, Radiology, 2012; 262 (3): 985-994. [4] Naressi et al, Computers in Biology and Medicine, 2001; 31(4): 269-286.

Figures

Figure1 Metabolite maps of NAA, creatine, and choline in a 9 year old female patient for various acceleration factors 1X-5X.

Figure2 Metabolite maps of NAA, creatine, and choline in a 10 year old male patient for various acceleration factors 1X-5X. Very low concentrations of the brain metabolites were seen in the tumor region.

Figure3 The normalized RMSEs from the two datasets depicted earlier (a) Normal pediatric brain, and (b) Pediatric brain tumor. In both cases, the errors are less than 2% for reconstructions up to 5X.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
3951