Evidence mapPaperPMID 41425318Full record

ArticleACS measurement science au2025

Upscaling the Hyperpolarization Sample Volume of an Automated Hydrogenative Parahydrogen-Induced Polarizer.

Yenal Gökpek, Jan-Bernd Hövener, Andrey N Pravdivtsev

Abstract read
In one paragraph

Article in ACS measurement science au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Yenal GökpekSection Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel University, Am Botanischen Garten 14, 24114 Kiel, Germany.ORCID https://orcid.org/0000-0003-2610-4556
Jan-Bernd HövenerSection Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel University, Am Botanischen Garten 14, 24114 Kiel, Germany.ORCID https://orcid.org/0000-0001-7255-7252
Andrey N PravdivtsevSection Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel University, Am Botanischen Garten 14, 24114 Kiel, Germany.ORCID https://orcid.org/0000-0002-8763-617X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) suffer from inherently low sensitivity due to the weak thermal polarization of nuclear spins. Parahydrogen-induced polarization (PHIP) offers a powerful route to enhance NMR signals by several orders of magnitude, enabling real-time metabolic imaging. However, PHIP implementations are often constrained by small sample volumes, limited automation, and complex high-pressure requirements. In this work, we present an upgraded, automated PHIP system capable of hyperpolarizing sample volumes up to 2.2 mL, which is suitable for preclinical MRI applications. We developed several high-pressure reactors and multiport NMR tube caps compatible with standard commercial 5, 10, and 16 mm glass tubes. Reactor designs were simulated and fabricated from chemically resistant polymers, ensuring mechanical safety at more than 30 bar. Using FLASH MRI, nutation, and CPMG sequences, we characterized magnetic field homogeneity and stability, establishing optimal sample dimensions (12.5/16 mm ID/OD glass tube, 20 mm height) with a

Indexed as

automationhyperpolarizationparahydrogenPHIP-SAHvinyl acetate

Identifiers

PMID41425318
PMCPMC12715744

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.