Evidence map›Paper›PMID 41961412›Full record

ArticleThe international journal of cardiovascular imaging2026

Feasibility of quantitative pulmonary function imaging in real-world cardiovascular magnetic resonance.

Jan Gröschel, Josephine Hausmann, Leonhard Grassow, Richard Hickstein, Philine Reisdorf, Edyta Blaszczyk, Phillip van Dijck, Jasmin Zernikow, Robert Grimm, Andreas Voskrebenzev and 2 more

Abstract read
In one paragraph

Article in The international journal of cardiovascular imaging, 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

12 authors.

Jan GröschelCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Josephine HausmannCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Leonhard GrassowCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Richard HicksteinCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Philine ReisdorfCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Edyta BlaszczykCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Phillip van DijckCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Jasmin ZernikowCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Robert GrimmResearch & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany.
Andreas VoskrebenzevCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Jens Vogel-ClaussenCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Jeanette Schulz-MengerCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. jeanette.schulz-menger@charite.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Providing insights into the feasibility of pulmonary function assessment in real-world cardiovascular magnetic resonance (CMR) practice by applying Phase-REsolved FUnctional Lung imaging (PREFUL). We retrospectively analyzed consecutive patients who underwent PREFUL imaging in addition to routine 1.5T CMR between September 2023 and January 2024. PREFUL was acquired in three coronal slices, with a prototype tool used to derive quantitative perfusion and ventilation defect percentages (QDP and VDP, respectively). Cardiac function was assessed from short-axis cine images. Subgroup analyses included patients with primary pulmonary disease and reduced left ventricular ejection fraction (LVEF). Statistical analyses comprised linear regression, correlation analysis, and Kruskal-Wallis test. The final cohort included N = 172 patients (74 females), median age 60 years (IQR 46-71). PREFUL was feasible in all cases (mean scan time 60 s/slice). Multivariable regression with bootstrap-based backward selection showed associations of QDP with LVEF, pulmonary disease, age, and BMI (all p ≤ 0.005), while VDP was associated with pulmonary disease, age, and male sex (all p < 0.001). QDP correlated negatively with LV stroke volume (ρ (Spearman's rho) - 0.336, p < 0.001) and cardiac output (ρ - 0.360; p < 0.001) and was higher in patients with LVEF < 50% (p < 0.001). Patients with primary pulmonary disease had higher QDP (p = 0.005) and VDP (p = 0.036). No correlations between cardiac function and VDP were detected (all p > 0.05). Application of PREFUL is feasible and fast in CMR routine. While QDP and VDP are affected by pulmonary disease, QDP is additionally associated with markers of cardiac function and was higher in patients with reduced LVEF.

Indexed as

LungLung DiseasesMagnetic Resonance Imaging, CineAgedFeasibility StudiesFemaleHumansMaleMiddle AgedPerfusion Magnetic Resonance ImagingPredictive Value of TestsReproducibility of ResultsRetrospective StudiesStroke VolumeVentricular Function, LeftCardiovascular magnetic resonanceFeasibilityPREFULPulmonary assessment

Identifiers

PMID41961412
PMCPMC13433384

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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.