Evidence map›Paper›PMID 41207863›Full record

ArticleMagnetic resonance in medicine2026

Data Stitching for Dynamic Field Monitoring With NMR Probes.

Jinyuan Zhang, Zihao Zhang, Zhentao Zuo, Rong Xue, Yan Zhuo, Cameron Cushing, Alexander Bratch, Edward Auerbach, Andrea Grant, Jing An and 2 more

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2026. 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

12 authors.

Jinyuan ZhangState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-5072-4934
Zihao ZhangState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0001-9286-8189
Zhentao ZuoState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Rong XueState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0001-7055-4939
Yan ZhuoState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Cameron CushingSkope MRT, Zurich, Switzerland.
Alexander BratchCenter for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA.
Edward AuerbachCenter for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0003-4553-1545
Andrea GrantCenter for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA.
Jing AnDigital Department, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China.
Kamil UgurbilCenter for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0002-8475-9334
Xiaoping WuCenter for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0001-6021-9088

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger, KAMIL UGURBIL · 2019 to 2026
$11.7M
Elementary Neuronal Ensembles to Whole Brain Networks: Ultrahigh Resolution Imaging of Function and Connectivity in Humans - SUPPLEMENTU01EB025144 · NIBIB · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2017 to 2022
$9.7M
CONSOLE FOR 10.5 TESLA WHOLE BODY MRI SYSTEMS10RR029672 · NCRR · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2010 to 2010
$7.8M
Ultrahigh-resolution Functional MRI of the Human Brain at 10.5 TeslaR01NS136490 · NINDS · UNIVERSITY OF MINNESOTA · PI Luca Vizioli, Xiaoping Wu · 2024 to 2026
$1.7M
China National Science and Technology Innovation 2030 Major Program 2022ZD0211901National Natural Science Foundation of China 82271985NCRR NIH HHS S10 RR029672NIBIB NIH HHS P41 EB027061NIBIB NIH HHS U01 EB025144NIH HHS P41 EB027061NIH HHS R01 NS136490NIH HHS S10 RR029672NIH HHS U01 EB025144NINDS NIH HHS R01 NS136490Strategic Priority Research Program of the CAS XDB0930000Youth Innovation Promotion Association of the Chinese Academy of Sciences 2022093
6 · The paper itself

Abstract

purposeTo propose a new method for characterizing sequences with higher resolution or readout length than allowed by standard field monitoring approaches.

methodsOur proposed method was devised to characterize entire readout gradients by stitching multiple segment-specific dynamic field measurements obtained across a matched number of consecutive TRs corresponding to a certain segmentation of the readout gradient. The utility of our proposed stitching method for high-order dynamic field measurements was illustrated using 2D spiral sequences. It was first demonstrated at 10.5 T and then at 7 T using both simulated and experimental MRI data. At 10.5 T, two extreme spiral readout scenarios were considered where standard field monitoring did not work. Our method was then validated in humans at 7 T, where spiral sequences were employed for brain imaging. At 7 T, our method was further compared against gradient impulse response function (GIRF)-based trajectory prediction.

resultsAt 10.5 T, our stitching method outperformed the standard approach, producing plausible dynamic field measurements throughout entire readouts. At 7 T, it produced nearly identical measurements for one readout where standard field monitoring also worked; for another readout when standard field monitoring did not work, it still produced sensible field measurements, improving image reconstruction for both simulated and experimental MRI data.

conclusionOur proposed stitching method provides an effective means to characterize challenging imaging gradients using commercially available hardware and without assuming a linear gradient system, thereby having utility for many applications especially those aiming for ultrahigh-resolution MRI at ultrahigh field.

Indexed as

BrainImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsComputer SimulationHumansPhantoms, ImagingReproducibility of Results2D spiraldynamic field monitoringhigh‐order image reconstructionhigh‐order MR simulationspiral imaging

Identifiers

PMID41207863
PMCPMC12643177

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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.