Evidence map›Paper›PMID 42658455›Full record

ReviewMagma (New York, N.Y.)2026

Recent advances in arterial spin labeling MRI for imaging brain tumors.

Gabriel Hoffmann, Matthias J P van Osch

Abstract readReview
PubMed Publisher
In one paragraph

Review in Magma (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Gabriel HoffmannSchool of Medicine and Health, Department of Neuroradiology, Technical University of Munich, Munich, Germany. gabriel.hoffmann@tum.de.ORCID http://orcid.org/0000-0002-5233-7532
Matthias J P van OschDepartment of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands.

Funding

Alzheimer Nederland WE.30-2022-04Deutsche Forschungsgemeinschaft 547163214Evangelisches Studienwerk Villigst Personal GrantFondation Leducq 23CVD03MODEM 10510032120006Stichting voor de Technische Wetenschappen 22131Stichting voor de Technische Wetenschappen https://doi.org/10.61686/ZQBJN99976
6 · The paper itself

Abstract

Perfusion MRI plays an important role in brain tumor assessment, especially for tumor grading and differentiation of tumor progression from pseudoprogression. Arterial spin labeling (ASL) MRI is a non-invasive method for measuring cerebral blood flow (CBF) using blood water as an endogenous tracer, which has great clinical potential for brain tumor imaging and might help to lower the use of gadolinium-based contrast agents. In this review, we discuss recent advances of the ASL method with a special focus on brain tumors, including multi-time point ASL which not only allows more accurate CBF quantification, but also yields arterial transit time (ATT) maps. Another method to reduce dependency on ATT is velocity-selective ASL, for which labeling is directly performed in the imaging volume. By performing a physiological challenge, like a hypercapnia breathing challenge, the reactivity of the tumor's neovasculature can be determined. More recent advances in ASL allow probing the blood-brain barrier (BBB) integrity by measuring the rate of water transport across the BBB (BBB-ASL). By labeling only a single artery, selective ASL sequences can help to identify what part of the tumor is fed by which artery. In conclusion, we see the future potential of ASL MRI not only in replacing contrast agents for perfusion assessment but also in providing additional information to the MRI exam, such as BBB integrity or the architecture of the vascular feeders.

Indexed as

Arterial spin labelingBlood–brain barrierBrain tumorsReview

Identifiers

PMID42658455

What OpenQuestion holds

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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.