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Improving the diagnostic yield of magnetic resonance spectroscopy for pediatric brain tumors through mathematical optimization

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Abstract

Brain tumors are the leading cause of cancer-related deaths among children. Increasing attention in pediatric neuro-oncology has been given to magnetic resonance spectroscopy (MRS). Notwithstanding the important achievements, the potential of MRS for pediatric neuro-oncology is yet to be realized. This is largely due to reliance upon inadequate signal processing methods based upon the fast Fourier transform (FFT) plus fitting. Herein, we applied an advanced signal processor, the fast Padé transform (FPT) to MRS time signals encoded in vivo from a glioma in a pediatric patient, using a 1.5T scanner. Three echo times (TE) were used: 22, 136 and 272 ms. Compared to those from the FFT, the total shape spectra from the FPT were better resolved. The most striking advantages of the FPT lie in its parametric capabilities from which component spectra were generated. At the shortest TE, for which spectral density is greatest, the FPT resolved the numerous overlapping resonances, delineating myoinositol and other short-lived metabolites. The FPT resolved components of diagnostically-important peaks centered at chemical shifts near 2.0, 3.0 and 3.2 parts per million. The latter includes not only free choline, but also the cancer biomarker, phosphocholine. An information-preserving procedure for suppression of residual water is introduced and validated, via windowing using a step function. This investigation demonstrates that mathematical optimization through the FPT can be successfully applied to MRS time signals encoded in vivo from pediatric brain tumors using standard clinical scanners at 1.5T. Improved diagnostic yield within pediatric neuro-oncology is anticipated thereby.

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Notes

  1. Note that Glx is often used as a joint acronym for both Glu and Gln.

  2. In Refs. [51, 52], K = 25 is used only as an example for the total number of resonances in the simulated FIDs. In reality, however, there is no upper bound on the total number K of resonances that can, in principle, be reconstructed by the FPT.

Abbreviations

Ace:

Acetate

Ala:

Alanine

Asp:

Aspartate

ARMA:

Autoregressive moving average

bl:

Band limited

BW :

Bandwidth

Cho:

Choline

Cr:

Creatine

DFT:

Discrete Fourier transform

DWI:

Diffusion weighted imaging

FFT:

Fast Fourier transform

FID:

Free induction decay

fMRI:

Functional MRI

FPT:

Fast Padé transform

FWHM:

Full width at half maximum

GABA:

Gamma amino butyric acid

GE:

General Electric

Gln:

Glutamine

Glu:

Glutamate

Glx:

Glutamine plus glutamate

HLSVD:

Hankel–Lanczos singular value decomposition

IDFT:

Inverse discrete Fourier transform

IFFT:

Inverse fast Fourier transform

Lac:

Lactate

Leu:

Leucine

Lip:

Lipids

m-Ins:

Myoinositol

MR :

Magnetic resonance

MRI:

Magnetic resonance imaging

MRS:

Magnetic resonance spectroscopy

MRSI:

Magnetic resonance spectroscopic imaging

ms :

Milliseconds

NAA:

N-acetyl aspartate

NAAG:

N-acetyl aspartyl glutamic acid

PC:

Phosphocholine

PCM:

Personalized cancer medicine

PCr:

Phosphocreatine

PRESS:

Point-resolved spectroscopy sequence

ppm:

Parts per million

rad:

Radian

s-Ins:

Scylloinositol

SNR:

Signal-noise ratio

SNS:

Signal-noise separation

SRI:

Spectral range of interest

SVD:

Singular value decomposition

Tau:

Taurine

TE:

Echo time

TR:

Repetition time

Val:

Valine

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Acknowledgments

This work was supported by the King Gustav the 5th Jubilee Fund and FoUU through Stockholm County Council to which the authors are grateful.

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Authors and Affiliations

  1. Department of Oncology/Pathology, Karolinska Institute, P.O. Box 260, 171776, Stockholm, Sweden

    Dževad Belkić & Karen Belkić

  2. School of Community and Global Health, Claremont Graduate University, Claremont, CA, USA

    Karen Belkić

  3. Institute for Health Promotion and Disease Prevention Research, University of Southern California School of Medicine, Los Angeles, CA, USA

    Karen Belkić

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Belkić, D., Belkić, K. Improving the diagnostic yield of magnetic resonance spectroscopy for pediatric brain tumors through mathematical optimization. J Math Chem 54, 1461–1513 (2016). https://doi.org/10.1007/s10910-016-0632-9

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