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Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T

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Abstract

The purpose of this study was to apply compressed sensing method for accelerated phosphorus MR spectroscopic imaging (31P-MRSI) of human brain in vivo at 3T. Fast 31P-MRSI data of five volunteers were acquired on a 3T clinical MR scanner using pulse-acquire sequence with a pseudorandom undersampling pattern for a data reduction factor of 5.33 and were reconstructed using compressed sensing. Additionally, simulated 31P-MRSI human brain tumor datasets were created to analyze the effects of k-space sampling pattern, data matrix size, regularization parameters of the reconstruction, and noise on the compressed sensing accelerated 31P-MRSI data. The 31P metabolite peak ratios of the full and compressed sensing accelerated datasets of healthy volunteers in vivo were similar according to the results of a Bland–Altman test. The estimated effective spatial resolution increased with reduction factor and sampling more at the k-space center. A lower regularization parameter for both total variation and L1-norm penalties resulted in a better compressed sensing reconstruction of 31P-MRSI. Although the root-mean-square error increased with noise levels, the compressed sensing reconstruction was robust for up to a reduction factor of 10 for the simulated data that had sharply defined tumor borders. As a result, compressed sensing was successfully applied to accelerate 31P-MRSI of human brain in vivo at 3T.

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References

  1. Ahmed OA (2005) New denoising scheme for magnetic resonance spectroscopy signals. IEEE Trans Med Imaging 24:809–816. doi:10.1109/TMI.2004.828350

    Article  PubMed  Google Scholar 

  2. Askin NC, Atis B, Ozturk-Isik E (2012) Accelerated phosphorus magnetic resonance spectroscopic imaging using compressed sensing. Conf Proc IEEE Eng Med Biol Soc 2012:1106–1109. doi:10.1109/EMBC.2012.6346128

    PubMed  Google Scholar 

  3. Banerjee S, Ozturk-Isik E, Nelson SJ, Majumdar S (2009) Elliptical magnetic resonance spectroscopic imaging with GRAPPA for imaging brain tumors at 3T. Magn Reson Imaging 27:1319–1325. doi:10.1016/j.mri.2009.05.031

    Article  PubMed  Google Scholar 

  4. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  CAS  PubMed  Google Scholar 

  5. Candes EJ, Romberg J, Tao T (2006) Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inf Theory 52:489–509

    Article  Google Scholar 

  6. Cao P, Wu EX (2015) Accelerating phase-encoded proton MR spectroscopic imaging by compressed sensing. J Magn Reson Imaging 41:487–495. doi:10.1002/jmri.24553

    Article  PubMed  Google Scholar 

  7. Citak Er F, Hatay G, Okeer E, Yildirim M, Hakyemez B, Ozturk-Isik E (2014) Classification of phosphorus magnetic resonance spectroscopic imaging of brain tumors using support vector machine and logistic regression at 3T. Conf Proc IEEE Eng Med Biol Soc 2014:2392–2395

    Google Scholar 

  8. Donoho D (2006) Compressed sensing. IEEE Trans Inf Theory 52:1289–1306

    Article  Google Scholar 

  9. Geethanath S, Baek HM, Ganji SK, Ding Y, Maher EA, Sims RD, Choi C, Lewis MA, Kodibagkar VD (2012) Compressive sensing could accelerate 1H MR metabolic imaging in the clinic. Radiology 262:985–994. doi:10.1148/radiol.11111098

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hardy CJ, Bottomley PA, Roemer PB, Redington RW (1988) Rapid 31P spectroscopy on a 4-T whole-body system. Magn Reson Med 8:104–109

    Article  CAS  PubMed  Google Scholar 

  11. Hatay G, Okeer E, Hakyemez B, Ozturk-Isik E (2014) Comparison of 2D iterative frame based and 3D direct compressed sensing reconstruction for accelerated phosphorus MR spectroscopic imaging of human brain. In: Proceedings of the 22nd annual meeting of ISMRM, Milan, Italy, p 6839

  12. Hu S, Lustig M, Chen AP, Crane J, Kerr A, Kelley DA, Hurd R, Kurhanewicz J, Nelson SJ, Pauly JM, Vigneron DB (2008) Compressed sensing for resolution enhancement of hyperpolarized 13C flyback 3D-MRSI. J Magn Reson 192:258–264. doi:10.1016/j.jmr.2008.03.003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hu S, Lustig M, Balakrishnan A, Larson PE, Bok R, Kurhanewicz J, Nelson SJ, Goga A, Pauly JM, Vigneron DB (2010) 3D compressed sensing for highly accelerated hyperpolarized (13)C MRSI with in vivo applications to transgenic mouse models of cancer. Magn Reson Med 63:312–321. doi:10.1002/mrm.22233

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hubesch B, Sappey-Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW (1990) P-31 MR spectroscopy of normal human brain and brain tumors. Radiology 174:401–409

    Article  CAS  PubMed  Google Scholar 

  15. Larson PE, Hu S, Lustig M, Kerr AB, Nelson SJ, Kurhanewicz J, Pauly JM, Vigneron DB (2011) Fast dynamic 3D MR spectroscopic imaging with compressed sensing and multiband excitation pulses for hyperpolarized 13C studies. Magn Reson Med 65:610–619. doi:10.1002/mrm.22650

    Article  CAS  PubMed  Google Scholar 

  16. Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58:1182–1195. doi:10.1002/mrm.21391

    Article  PubMed  Google Scholar 

  17. Maguire ML, Geethanath S, Lygate CA, Kodibagkar VD, Schneider JE (2015) Compressed sensing to accelerate magnetic resonance spectroscopic imaging: evaluation and application to 23Na-imaging of mouse hearts. J Cardiovasc Magn Reson 17:45. doi:10.1186/s12968-015-0149-6

    Article  PubMed  PubMed Central  Google Scholar 

  18. Maintz D, Heindel W, Kugel H, Jaeger R, Lackner KJ (2002) Phosphorus-31 MR spectroscopy of normal adult human brain and brain tumours. NMR Biomed 15:18–27. doi:10.1002/nbm.735

    Article  CAS  PubMed  Google Scholar 

  19. Maudsley AA, Matson GB, Hugg JW, Weiner MW (1994) Reduced phase encoding in spectroscopic imaging. Magn Reson Med 31:645–651

    Article  CAS  PubMed  Google Scholar 

  20. Nowak RD (1999) Wavelet-based Rician noise removal for magnetic resonance imaging. IEEE Trans Image Process Publ IEEE Signal Process Soc 8:1408–1419. doi:10.1109/83.791966

    Article  CAS  Google Scholar 

  21. Obruchkov S (2011) Echo Planar Spectroscopic Imaging and 31P In Vivo Spectroscopy. Open Access Distertations and Theses. Paper 4121. McMaster University, Hamilton, Ontario, Canada

  22. Ozturk-Isik E, Chen AP, Crane JC, Bian W, Xu D, Han ET, Chang SM, Vigneron DB, Nelson SJ (2009) 3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T. Magn Reson Imaging 27:1249–1257. doi:10.1016/j.mri.2009.05.028

    Article  PubMed  PubMed Central  Google Scholar 

  23. Parasoglou P, Feng L, Xia D, Otazo R, Regatte RR (2012) Rapid 3D-imaging of phosphocreatine recovery kinetics in the human lower leg muscles with compressed sensing. Magn Reson Med 68:1738–1746. doi:10.1002/mrm.24484

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Srinivasa-Raghavan R, Panda A, Valette J, James JR, Heberlein K, Boettcher U, Henry PG, Bansal N, Dydak U (2009) 31P Spectroscopic imaging with GRAPPA. In: Proceedings of the 17th annual meeting of ISMRM, Honolulu, USA, p 4317

  25. Ulrich M, Wokrina T, Ende G, Lang M, Bachert P (2007) 31P-{1H} echo-planar spectroscopic imaging of the human brain in vivo. Magn Reson Med 57:784–790. doi:10.1002/mrm.21192

    Article  CAS  PubMed  Google Scholar 

  26. Vanhamme L, van den Boogaart A, Van Huffel S (1997) Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 129:35–43

    Article  CAS  PubMed  Google Scholar 

  27. Wang SX, Caines GH, Schleich T (1993) 31P-{1H} nuclear overhauser effects of phosphorus-containing metabolites in chemical exchange between free and macromolecular bound states. J Magn Reson Ser B 102:47–53. doi:10.1006/jmrb.1993.1060

    Article  CAS  Google Scholar 

  28. Xu Y, Weaver JB, Healy DM, Lu J (1994) Wavelet transform domain filters: a spatially selective noise filtration technique. IEEE Trans Image Process Publ IEEE Signal Process Soc 3:747–758. doi:10.1109/83.336245

    CAS  Google Scholar 

  29. Young K, Soher BJ, Maudsley AA (1998) Automated spectral analysis II: application of wavelet shrinkage for characterization of non-parameterized signals. Magn Reson Med 40:816–821

    Article  CAS  PubMed  Google Scholar 

  30. Zaroubi S, Goelman G (2000) Complex denoising of MR data via wavelet analysis: application for functional MRI. Magn Reson Imaging 18:59–68

    Article  CAS  PubMed  Google Scholar 

  31. Zierhut ML, Ozturk-Isik E, Chen AP, Park I, Vigneron DB, Nelson SJ (2009) (1)H spectroscopic imaging of human brain at 3 Tesla: comparison of fast three-dimensional magnetic resonance spectroscopic imaging techniques. J Magn Reson Imaging 30:473–480. doi:10.1002/jmri.21834

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This research was supported by TUBITAK Career Development Grant 112E036 and EU Marie Curie IRG Grant FP7-PEOPLE-RG-2009 256528.

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Authors and Affiliations

  1. Biomedical Engineering Institute, Bogazici University, Rasathane Cad, Kandilli Campus, Kandilli Mah., 34684, Istanbul, Turkey

    Gokce Hale Hatay, Muhammed Yildirim & Esin Ozturk-Isik

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  1. Gokce Hale Hatay
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  2. Muhammed Yildirim
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  3. Esin Ozturk-Isik
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Correspondence to Esin Ozturk-Isik.

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Conflict of interest

Gokce Hale Hatay and Esin Ozturk-Isik: no relevant conflicts of interest to disclose. Muhammed Yildirim: financial activities related to the present article: none to disclose. Financial activities not related to the present article: is an employee of Philips Healthcare. Other relationships: none to disclose.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Hatay, G.H., Yildirim, M. & Ozturk-Isik, E. Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T. Med Biol Eng Comput 55, 1303–1315 (2017). https://doi.org/10.1007/s11517-016-1591-9

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  • DOI: https://doi.org/10.1007/s11517-016-1591-9

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