Evidence map›Paper›PMID 30296560›Full record

ArticleNeuroImage2019

Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES.

Georg Oeltzschner, Muhammad G Saleh, Daniel Rimbault, Mark Mikkelsen, Kimberly L Chan, Nicolaas A J Puts, Richard A E Edden

Abstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Identifying out-of-voxel echoes in edited MRS with phase cycle inversion.bioRxiv : the preprint server for biology · 2025
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  9. Review
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  20. Application of aImaging neuroscience (Cambridge, Mass.) · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Georg OeltzschnerRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States. Electronic address: goeltzs1@jhmi.edu.
Muhammad G SalehRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
Daniel RimbaultMedical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa.
Mark MikkelsenRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
Kimberly L ChanRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States; Department of Bioengineering, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Nicolaas A J PutsRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
Richard A E EddenRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.

Funding

TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI MORI, SUSUMU · 2012 to 2020
$13.1M
Translational Neuroscience CoreU54HD079123 · NICHD · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI FATEMI, S. ALI, SCHLAGGAR, BRADLEY L · 2014 to 2019
$7.9M
Universal GABA-edited MRS at 3TR01EB016089 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI Richard Anthony Edward Edden · 2013 to 2026
$5.4M
Simultaneous Hadamard Editing of GABA and GlutathioneR01EB023963 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI EDDEN, RICHARD ANTHONY EDWARD · 2017 to 2024
$3.8M
State of the Art 3T Research ScannerS10OD021648 · OD · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2016 to 2016
$2.0M
A Multimodal Investigation of Inhibitory Dysfunction in Autism Spectrum DisorderR00MH107719 · NIMH · JOHNS HOPKINS UNIVERSITY · PI PUTS, NICOLAAS · 2018 to 2019
$492k
A Multimodal Investigation of Inhibitory Dysfunction in Autism Spectrum DisorderK99MH107719 · NIMH · JOHNS HOPKINS UNIVERSITY · PI PUTS, NICOLAAS · 2016 to 2017
$165k
NIBIB NIH HHS P41 EB015909NIBIB NIH HHS R01 EB016089NIBIB NIH HHS R01 EB023963NICHD NIH HHS U54 HD079123NIH HHS S10 OD021648NIMH NIH HHS R00 MH107719
6 · The paper itself

Abstract

purposeTo demonstrate the framework of a novel Hadamard-encoded spectral editing approach for simultaneously detecting multiple low-concentration brain metabolites in vivo at 3T.

methodsHERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) is a four-step Hadamard-encoded editing scheme. 20-ms editing pulses are applied at: (A) 4.58 and 1.9 ppm; (B) 4.18 and 1.9 ppm; (C) 4.58 ppm; and (D) 4.18 ppm. Edited signals from γ-aminobutyric acid (GABA), glutathione (GSH), ascorbate (Asc), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), aspartate (Asp), lactate (Lac), and likely 2-hydroxyglutarate (2-HG) are separated with reduced signal overlap into distinct Hadamard combinations: (A+B+C+D); (A+B-C-D); and (A-B+C-D). HERCULES uses a novel multiplexed linear-combination modeling approach, fitting all three Hadamard combinations at the same time, maximizing the amount of information used for model parameter estimation, in order to quantify the levels of these compounds. Fitting also allows estimation of the levels of total choline (tCho), myo-inositol (Ins), glutamate (Glu), and glutamine (Gln). Quantitative HERCULES results were compared between two grey- and white-matter-rich brain regions (11 min acquisition time each) in 10 healthy volunteers. Coefficients of variation (CV) of quantified measurements from the HERCULES fitting approach were compared against those from a single-spectrum fitting approach, and against estimates from short-TE PRESS data.

resultsHERCULES successfully segregates overlapping resonances into separate Hadamard combinations, allowing for the estimation of levels of seven coupled metabolites that would usually require a single 11-min editing experiment each. Metabolite levels and CVs agree well with published values. CVs of quantified measurements from the multiplexed HERCULES fitting approach outperform single-spectrum fitting and short-TE PRESS for most of the edited metabolites, performing only slightly to moderately worse than the fitting method that gives the lowest CVs for tCho, NAA, NAAG, and Asp.

conclusionHERCULES is a new experimental approach with the potential for simultaneous editing and multiplexed fitting of up to seven coupled low-concentration and six high-concentration metabolites within a single 11-min acquisition at 3T.

Indexed as

BrainHumansMagnetic Resonance SpectroscopyGABAGSHHadamard encodingMagnetic resonance spectroscopyNAAGSpectral editing

Identifiers

PMID30296560
PMCPMC6289748

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.