Accelerated Magnetic Resonance Spectroscopic Imaging (MRSI) using Magnetic Resonance Fingerprinting (MRF)
Rashmi Reddy1, Imam Shaik1, Arush Honnedevasthana1, Pavan Poojar1, and Sairam Geethanath1

1Dayananda Sagar Institutions, Bangalore, India

Synopsis

Magnetic Resonance Spectroscopic Imaging (MRSI) is used as a tool to quantify metabolites in human brain and other organs. It is extensively used in clinical imaging and clinical research applications1. However, the major drawback of this technology is its long acquisition time which is the primary reason for not being used in the clinics. A novel approach of accelerating MRSI using Magnetic Resonance Fingerprinting (MRF) has been proposed in the current work.

Purpose

The proposed approach aims at reducing the acquisition time of Magnetic Resonance Spectroscopic Imaging (MRSI) through application of Magnetic Resonance Fingerprinting (MRF) 2 based on dictionary generation of metabolites.

Methods

A retrospective analysis was performed on the Ethanol (CH3CH2OH) phantom data sets. These datasets were acquired on Siemens 1.5T scanner with dimensions of 16 X 16 X 1024 with 1024 being the time points. A spectra was obtained with TE/TR combination of 30ms/1590ms respectively and Averages=1. 4 bottles having pure distilled water (for reference) in 1 of the bottles and 3 other bottles with different concentrations of ethanol (25%, 50% and 100%) were scanned with total acquisition time of 4 minutes and 30 seconds. The phantom set up is as shown in figure 1. Spectra of ethanol obtained from scanner was noisy due to low TR/TE and less averages.

MRF-Dictionary generation: Free Induction Decay (FID) closely approximating the response of metabolites for the molecular groups of ethanol i.e., CH3, CH2 and OH was generated based on equation as in3 given below,

$$S(k)=\sum_{q=1}^NA_{q}exp(-t_{k}/T_{2}^{q})exp(j(2\pi f_{q}t_{k} + \phi_{q}))$$

Where, S is the simulated FID having ‘q’ number of metabolite peaks each with amplitude Aq having an apparent relaxation time T2q, a frequency fq and a phase φq and tk is the kth time point in the FID. FIDs for above mentioned metabolites were generated for given TE/TR and for different T2 values between the range 50-720ms, 50-750ms and 20-90ms for CH3, CH2 and OH respectively. Spectra obtained by taking Inverse Fast Fourier Transform (IFFT) were added up and stored in dictionary.

Pattern matching: Pattern matching between the original spectra and dictionary was performed using vector dot product. To find the ppm shift of the spectra, cross correlation and circular shift operations were performed on the matched spectra from dictionary. The original and matched spectra were subjected to the following processing steps in jMRUI4: (a) Apodization (b) Phase Correction (c) Frequency Shift.

Results

The spectra obtained from scanner was matched with one of the spectra in dictionary. Signal evolution curves for original spectra obtained from scanner and dictionary matched spectra are shown in figure 2. From figure 2, we can observe that the patterns of scanner spectra and spectra from dictionary were matching. Ratio of the 3 peaks in the spectrum obtained from dictionary was observed to be 0.57, 0.327 and 0.097 for CH3, CH2 and OH respectively as expected.

Conclusion and Discussion

Application of MRF on MRSI has been performed for the first time. This method aids in accelerated MRSI. Future work includes generation of metabolite maps and incorporation of CS for denoising of MRSI data.

Acknowledgements

This work was supported by Department of Science and Technology (DST), Govt. of India under the program Technology Systems Development (TSD) for the project “Novel acquisition and reconstruction strategies to accelerate magnetic resonance imaging using compressed sensing”, No: DST/TSG/NTS/2013/100-G.

References

[1] Posse S, Otazo R, Dager SR, Alger J . MR spectroscopic imaging: principles and recent advances. J Magn Reson Imaging. 2013, 1301-25

[2] Dan Ma, Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L. Sunshine, Jeffrey L.Duerk and Mark A. Griswold. Magnetic Resonance Fingerprinting. Nature. 2013 March 14; 495(7440): 187–192

[3] M. Joliot, B. M. Mazoyer, and R. H. Huesman. Invivo Nmr Spectral Parameter-Estimation - a Comparison between Time and Frequency-Domain Methods. Magnetic Resonance in Medicine, 18(2), 358-370 (1991)

[4] A. Naressi, C. Couturier, I. Castang et al. Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals. Computers in Biology and Medicine, 31(4), 269-286 (2001)

Figures

Fig 1: Phantom setup- a. pure distilled water, b. 25% ethanol, c. 50% ethanol, d. 100% ethanol

Fig 2: Pattern matching of data spectrum and dictionary spectrum



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