Highly accelerated chemical exchange saturation transfer (CEST) measurements with linear algebraic modeling

Research output: Contribution to journalArticle

Abstract

Purpose: In clinical studies, compartmental average chemical exchange saturation transfer (CEST) measurements rather than voxel-by-voxel CEST images may suffice for evaluating its diagnostic value. A recently developed method—spectroscopy with linear algebraic modeling, or SLAM—could directly provide compartmental measures with dramatically reduced scan time and optimal signal-to-noise ratios. Here, we test whether SLAM can be adapted to significantly accelerate CEST acquisitions. Theory and Methods: Conventional anatomical images and raw CEST image k-space data were acquired from seven brain tumor patients. SLAM was applied to the CEST data using acceleration factors of R = 1–45, after segmenting compartments from co-registered images. SLAM-CEST measures were compared with average values from the identical compartments obtained by conventional Fourier transform (FT) CEST. Results: SLAM generated compartmental average CEST z-spectra that were indistinguishable from conventional FT-CEST for R ≤ 45. SLAM-CEST z-spectra at ±3.5 ppm were highly correlated with FT-CEST measures (r2 ≥ 0.98 for R ≤ 9; r ≥ 0.995 for R ≤ 45). The average error of SLAM-CEST versus FT-CEST measures was ≤10% for R ≤ 45, in acquisitions requiring as few as a single k-space phase-encoding step. Conclusion: Applied to patients with brain tumors, SLAM-CEST can yield results that are quantitatively equivalent to conventional CEST up to 45 times faster, which could prove enabling in clinical settings where scan time is limiting. Magn Reson Med 76:136–144, 2016.

Original languageEnglish (US)
Pages (from-to)136-144
Number of pages9
JournalMagnetic Resonance in Medicine
Volume76
Issue number1
DOIs
StatePublished - Jul 1 2016

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Fourier Analysis
Brain Neoplasms
R Factors
Signal-To-Noise Ratio

Keywords

  • amide proton transfer (APT)
  • brain tumor
  • chemical exchange saturation transfer (CEST)
  • spectroscopy by linear algebraic modeling (SLAM)

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

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title = "Highly accelerated chemical exchange saturation transfer (CEST) measurements with linear algebraic modeling",
abstract = "Purpose: In clinical studies, compartmental average chemical exchange saturation transfer (CEST) measurements rather than voxel-by-voxel CEST images may suffice for evaluating its diagnostic value. A recently developed method—spectroscopy with linear algebraic modeling, or SLAM—could directly provide compartmental measures with dramatically reduced scan time and optimal signal-to-noise ratios. Here, we test whether SLAM can be adapted to significantly accelerate CEST acquisitions. Theory and Methods: Conventional anatomical images and raw CEST image k-space data were acquired from seven brain tumor patients. SLAM was applied to the CEST data using acceleration factors of R = 1–45, after segmenting compartments from co-registered images. SLAM-CEST measures were compared with average values from the identical compartments obtained by conventional Fourier transform (FT) CEST. Results: SLAM generated compartmental average CEST z-spectra that were indistinguishable from conventional FT-CEST for R ≤ 45. SLAM-CEST z-spectra at ±3.5 ppm were highly correlated with FT-CEST measures (r2 ≥ 0.98 for R ≤ 9; r ≥ 0.995 for R ≤ 45). The average error of SLAM-CEST versus FT-CEST measures was ≤10{\%} for R ≤ 45, in acquisitions requiring as few as a single k-space phase-encoding step. Conclusion: Applied to patients with brain tumors, SLAM-CEST can yield results that are quantitatively equivalent to conventional CEST up to 45 times faster, which could prove enabling in clinical settings where scan time is limiting. Magn Reson Med 76:136–144, 2016.",
keywords = "amide proton transfer (APT), brain tumor, chemical exchange saturation transfer (CEST), spectroscopy by linear algebraic modeling (SLAM)",
author = "Yi Zhang and Heo, {Hye Young} and Shanshan Jiang and Lee, {Dong Hoon} and Bottomley, {Paul A} and Jinyuan Zhou",
year = "2016",
month = "7",
day = "1",
doi = "10.1002/mrm.25873",
language = "English (US)",
volume = "76",
pages = "136--144",
journal = "Magnetic Resonance in Medicine",
issn = "0740-3194",
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T1 - Highly accelerated chemical exchange saturation transfer (CEST) measurements with linear algebraic modeling

AU - Zhang, Yi

AU - Heo, Hye Young

AU - Jiang, Shanshan

AU - Lee, Dong Hoon

AU - Bottomley, Paul A

AU - Zhou, Jinyuan

PY - 2016/7/1

Y1 - 2016/7/1

N2 - Purpose: In clinical studies, compartmental average chemical exchange saturation transfer (CEST) measurements rather than voxel-by-voxel CEST images may suffice for evaluating its diagnostic value. A recently developed method—spectroscopy with linear algebraic modeling, or SLAM—could directly provide compartmental measures with dramatically reduced scan time and optimal signal-to-noise ratios. Here, we test whether SLAM can be adapted to significantly accelerate CEST acquisitions. Theory and Methods: Conventional anatomical images and raw CEST image k-space data were acquired from seven brain tumor patients. SLAM was applied to the CEST data using acceleration factors of R = 1–45, after segmenting compartments from co-registered images. SLAM-CEST measures were compared with average values from the identical compartments obtained by conventional Fourier transform (FT) CEST. Results: SLAM generated compartmental average CEST z-spectra that were indistinguishable from conventional FT-CEST for R ≤ 45. SLAM-CEST z-spectra at ±3.5 ppm were highly correlated with FT-CEST measures (r2 ≥ 0.98 for R ≤ 9; r ≥ 0.995 for R ≤ 45). The average error of SLAM-CEST versus FT-CEST measures was ≤10% for R ≤ 45, in acquisitions requiring as few as a single k-space phase-encoding step. Conclusion: Applied to patients with brain tumors, SLAM-CEST can yield results that are quantitatively equivalent to conventional CEST up to 45 times faster, which could prove enabling in clinical settings where scan time is limiting. Magn Reson Med 76:136–144, 2016.

AB - Purpose: In clinical studies, compartmental average chemical exchange saturation transfer (CEST) measurements rather than voxel-by-voxel CEST images may suffice for evaluating its diagnostic value. A recently developed method—spectroscopy with linear algebraic modeling, or SLAM—could directly provide compartmental measures with dramatically reduced scan time and optimal signal-to-noise ratios. Here, we test whether SLAM can be adapted to significantly accelerate CEST acquisitions. Theory and Methods: Conventional anatomical images and raw CEST image k-space data were acquired from seven brain tumor patients. SLAM was applied to the CEST data using acceleration factors of R = 1–45, after segmenting compartments from co-registered images. SLAM-CEST measures were compared with average values from the identical compartments obtained by conventional Fourier transform (FT) CEST. Results: SLAM generated compartmental average CEST z-spectra that were indistinguishable from conventional FT-CEST for R ≤ 45. SLAM-CEST z-spectra at ±3.5 ppm were highly correlated with FT-CEST measures (r2 ≥ 0.98 for R ≤ 9; r ≥ 0.995 for R ≤ 45). The average error of SLAM-CEST versus FT-CEST measures was ≤10% for R ≤ 45, in acquisitions requiring as few as a single k-space phase-encoding step. Conclusion: Applied to patients with brain tumors, SLAM-CEST can yield results that are quantitatively equivalent to conventional CEST up to 45 times faster, which could prove enabling in clinical settings where scan time is limiting. Magn Reson Med 76:136–144, 2016.

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