Evidence map›Paper›PMID 42128943›Full record

ArticleClinical neuroradiology2026

Detection of Hemorrhagic Transformation of Cerebral Infarcts with Ultra-low Field MRI.

Dimah Hasan, Julian Sauer, Clara Heller, Annika Rieder, Konstantin Ueffing, Frederic de Beukelaer, Jörg Schulz, Johannes Schiefer, Manuel Dafotakis, Arno Reich and 3 more

Abstract read
In one paragraph

Article in Clinical 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. Review
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

13 authors.

Dimah HasanDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Julian SauerDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Clara HellerDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Annika RiederDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Konstantin UeffingDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Frederic de BeukelaerDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Jörg SchulzDepartment of Neurology, Universitätsklinikum Aachen, Aachen, Germany.
Johannes SchieferDepartment of Neurology, Universitätsklinikum Aachen, Aachen, Germany.
Manuel DafotakisDepartment of Neurology, Universitätsklinikum Aachen, Aachen, Germany.
Arno ReichDepartment of Neurology, Universitätsklinikum Aachen, Aachen, Germany.
Martin WiesmannDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany.
Florian HoltberndDepartment of Neurology, Universitätsklinikum Aachen, Aachen, Germany.
Charlotte WeylandDepartment of Neuroradiology, Universitätsklinikum Aachen, Aachen, Germany. cweyland@ukaachen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHemorrhagic transformation (HT) within ischemic infarcts is a critical post-stroke complication that significantly influences secondary prevention strategies, particularly the timing and safety of anticoagulation. Ultra-low field (ULF) MRI (0.064 T, Swoop, Hyperfine) offers bedside neuroimaging, but its ability to detect hemorrhagic transformation compared to standard MRI (1.5 T or 3 T) and CT remains uncertain. This study aimed to evaluate the diagnostic accuracy of ULF-pMRI for detecting hemorrhagic transformation in ischemic stroke patients.

methodsWe retrospectively analyzed 97 patients with ischemic infarcts who underwent both ULF-pMRI and standard neuroimaging (standard MRI or CT). The presence of hemorrhagic transformation was assessed by two independent readers (trained neuroradiologists) and by consensus reading in univariate analysis using the Heidelberg Bleeding Classification (HBC). Diagnostic accuracy metrics sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated with the standard method (standard MRI or CT within two days of ULF-pMRI) as the reference. Agreement was quantified using Cohen's Kappa.

resultsOf 97 stroke patients, n = 21 (21.6%) showed hemorrhagic transformation on standard imaging. Most findings corresponded to scattered small petechia and subarachnoid hemorrhage. Reader 1 detected hemorrhagic transformation in ULF-pMRI with a sensitivity of 5/21 (23.8%), specificity 100%, positive predictive value (PPV) 100%, and negative predictive value (NPV) 82% and Reader 2 showed a sensitivity of 3/21 (14.3%), specificity 100%, PPV 100%, and NPV 81%, while consensus reading showed sensitivity of 3/21 (14.3%), specificity 100%, PPV 100%, NPV 81%. ULF-pMRI failed to detect petechial hemorrhages (0/13 HBC1a; 0/3 HBC1b), while detection improved for more extensive hemorrhagic transformations (HBC 1c and 3). After exclusion of petechial hemorrhages (HBC1a and HBC1b), ULF-pMRI detected 5 of 9 remaining hemorrhagic transformation subtypes (55.6%).

conclusionUltra-low-field MRI demonstrated low sensitivity for detecting hemorrhagic transformation in ischemic stroke, particularly for petechial hemorrhages (HBC class 1a and 1b). Detection was higher for non-petechial hemorrhagic transformations (HBC class 1c and 3), but overall performance remains insufficient for reliable therapy-guiding decisions.

Indexed as

Cerebral HemorrhageCerebral InfarctionMagnetic Resonance ImagingAgedAged, 80 and overFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityTomography, X-Ray ComputedDiagnostic accuracyHemorrhagic transformationIschemic strokeSensitivityULF-pMRI

Identifiers

PMID42128943
PMCPMC13521962

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.