Evidence map›Paper›PMID 40146474›Full record

ArticleMagma (New York, N.Y.)2025

The Pulseq-CEST Library: definition of preparations and simulations, example data, and example evaluations.

Alexander Liebeskind, Jan Rüdiger Schüre, Moritz Simon Fabian, Simon Weinmüller, Patrick Schünke, Vladimir Golkov, Daniel Cremers, Moritz Zaiss

Abstract read
In one paragraph

Article in Magma (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Effective Modeling of Continuous WaveMagnetic resonance in medicine · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Reproducibility and quality assurance in MRI.Magma (New York, N.Y.) · 2025
    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

8 authors.

Alexander LiebeskindComputer Vision Group, Technical University of Munich (TUM), Boltzmannstraße 3, 85748, Garching bei München, Germany. alexanderliebeskind@yahoo.com.ORCID http://orcid.org/0000-0002-2457-8662
Jan Rüdiger SchüreInstitute of Neuroradiology, University Hospital Erlangen, Erlangen Schwabachanlage 6, 91054, Erlangen, Germany.
Moritz Simon FabianInstitute of Neuroradiology, University Hospital Erlangen, Erlangen Schwabachanlage 6, 91054, Erlangen, Germany.
Simon WeinmüllerInstitute of Neuroradiology, University Hospital Erlangen, Erlangen Schwabachanlage 6, 91054, Erlangen, Germany.
Patrick SchünkePhysikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Bundesallee 100, 38116, Brunswick, Germany.
Vladimir GolkovComputer Vision Group, Technical University of Munich (TUM), Boltzmannstraße 3, 85748, Garching bei München, Germany.
Daniel CremersComputer Vision Group, Technical University of Munich (TUM), Boltzmannstraße 3, 85748, Garching bei München, Germany.
Moritz ZaissInstitute of Neuroradiology, University Hospital Erlangen, Erlangen Schwabachanlage 6, 91054, Erlangen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDespite prevalent use of chemical exchange saturation transfer (CEST) MRI, standardization remains elusive. Imaging depends heavily on parameters dictating radiofrequency (RF) events, gradients, and apparent diffusion coefficient (ADC). We present the Pulseq-CEST Library, a repository of CEST preparation and simulation definitions, including example data and evaluations, that provides a common basis for reproducible research, rapid prototyping, and in silico deep learning training data generation. MATERIALS AND

methodsA Pulseq-CEST experiment requires (i) a CEST preparation sequence, (ii) a Bloch-McConnell parameter set, (iii) a Bloch-McConnell simulation, and (iv) an evaluation script. Pulseq-CEST utilizes the Bloch-McConnell equations to model in vitro and in vivo conditions. Using this model, a candidate sequence or environment can be held constant while varying other inputs, enabling robust testing.

resultsData were compared for amide proton transfer weighted (APTw) and water shift and B1 (WASABI) protocols using a five-tube phantom and simulated environments. Real and simulated data matched anticipated spectral shapes and local peak characteristics. The Pulseq-CEST Library supports similar experiments with common sequences and environments to assess new protocols and sample data. DISCUSSION: The Pulseq-CEST Library provides a flexible mechanism for standardizing and prototyping CEST sequences, facilitating collaborative development. With the capability for expansion, including open-source incorporation of new sequences and environments, the library accelerates the invention and spread of novel CEST and other saturation transfer approaches, such as relayed NOEs (rNOEs) and semisolid magnetization transfer contrast (MTC) methods.

Indexed as

Magnetic Resonance ImagingAlgorithmsBrainComputer SimulationDeep LearningHumansImage Processing, Computer-AssistedPhantoms, ImagingProtonsRadio WavesReproducibility of ResultsProtonsComputer assistedComputer simulationImage processingImagingMagnetic resonance imagingPhantomsSoftware

Identifiers

PMID40146474
PMCPMC12255581

What OpenQuestion holds

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LicenceCC BY
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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.