Evidence map›Paper›PMID 41400653›Full record

ArticleNeuroradiology2026

Ultra-high contrast MRI: a new technique for recognizing secondary changes to the brain in patients with persistent symptoms following traumatic brain injury.

Daniel Cornfeld, Gil Newburn, Paul Condron, Taylor Emsden, Mark Bydder, Miriam Scadeng, Tracy Melzer, Leigh Potter, Samantha Holdsworth, Eryn Kwon and 2 more

Abstract read
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Article in Neuroradiology, 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.

Daniel CornfeldMatai Medical Research Institute, Gisborne, New Zealand. d.cornfeld@matai.org.nz.
Gil NewburnMatai Medical Research Institute, Gisborne, New Zealand.
Paul CondronMatai Medical Research Institute, Gisborne, New Zealand.
Taylor EmsdenMatai Medical Research Institute, Gisborne, New Zealand.
Mark BydderMatai Medical Research Institute, Gisborne, New Zealand.
Miriam ScadengDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
Tracy MelzerDepartment of Medicine, University of Otago, Christchurch, New Zealand.
Leigh PotterMatai Medical Research Institute, Gisborne, New Zealand.
Samantha HoldsworthMatai Medical Research Institute, Gisborne, New Zealand.
Eryn KwonMatai Medical Research Institute, Gisborne, New Zealand.
Joshua McGeownMatai Medical Research Institute, Gisborne, New Zealand.
Graeme BydderMatai Medical Research Institute, Gisborne, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundManagement of patients with persistent or worsening symptoms following traumatic brain injury (TBI) presents difficulties. MRI is usually negative in mild TBI (mTBI) and usually only shows residual quiescent disease in moderate to severe TBI (msTBI).

objectiveWe hypothesize that patients with persistent symptoms from prior TBI will show findings on a divided Subtracted Inversion Recovery (dSIR) sequence that are sensitive to small changes from normal in white matter T MATERIALS AND

methodsNeurologically healthy controls (n = 37) and patients with persistent symptoms following TBI (n = 29) were examined with T

resultsOvert pathology was seen on the T

conclusionThe whiteout sign was strongly associated with being in the symptomatic group and is a potential biomarker for recognition of secondary changes to the brain in patients with persistent symptoms following TBI.

Indexed as

Brain Injuries, TraumaticMagnetic Resonance ImagingAdultAgedCase-Control StudiesContrast MediaFemaleHumansMaleMiddle AgedContrast MediadSIRMRITraumatic brain injuryUHCWhite out sign

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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.