Evidence map›Paper›PMID 41134326›Full record

ArticleEuropean radiology2026

Serial T

Mihaela Rata, Nina Tunariu, Yun Jiang, Julie Hughes, Georgina Hopkinson, Erica Scurr, Jessica M Winfield, Vikas Gulani, Dow-Mu Koh, Matthew R Orton

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology, 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

5 · Who and what money

Authors and funding

10 authors.

Mihaela RataDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK. Mihaela.Rata@rmh.nhs.uk.ORCID http://orcid.org/0000-0003-4999-8038
Nina TunariuDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Yun JiangDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
Julie HughesDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Georgina HopkinsonDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Erica ScurrDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Jessica M WinfieldDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Vikas GulaniDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA.
Dow-Mu KohDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.
Matthew R OrtonDepartment of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.

Funding

3D High Resolution Magnetic Resonance Fingerprinting for Prostate CancerR37CA263583 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yun Jiang · 2021 to 2026
$3.8M
Quantitative MRI to automatically delineate intraprostatic tumor for radiation therapyR01CA284172 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GUO, JIA, JIANG, YUN · 2024 to 2025
$1.4M
NCI NIH HHS R01 CA284172NCI NIH HHS R37 CA263583
6 · The paper itself

Abstract

objectivesThis study evaluated serial magnetic resonance fingerprinting (MRF)-derived T MATERIALS AND

methodsThis prospective study (July 2020 to July 2022) included MRF and conventional MRI acquisitions (T

resultsThirty-four patients with metastatic prostate cancer (mean age, 68 years ± 7 [standard deviation]) were evaluated pre-treatment; 19 participants were further scanned post-treatment. MRF-derived mean T

conclusionA good correlation of MRF-derived T KEY POINTS: Question MR fingerprinting (MRF)-derived T

Indexed as

Bone NeoplasmsMagnetic Resonance ImagingProstatic NeoplasmsAgedHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsBoneMetastasisMR fingerprintingProstate cancer

Identifiers

PMID41134326
PMCPMC12961610

What OpenQuestion 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 OpenQuestion graph.