Evidence map›Paper›PMID 40266551›Full record

ArticleThe international journal of cardiovascular imaging2025

Effects of parametric feature maps on the reproducibility of radiomics from different fields of view in cardiac magnetic resonance cine images- a clinical and experimental study setting.

Laura Jacqueline Jensen, Damon Kim, Thomas Elgeti, Ingo Günter Steffen, Lars-Arne Schaafs, Anja Cretnik, Bernd Hamm, Sebastian Niko Nagel

Abstract readComparative Study
In one paragraph

Article in The international journal of cardiovascular imaging, 2025. 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

8 authors.

Laura Jacqueline JensenDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany. laura-jacqueline.jensen@charite.de.ORCID https://orcid.org/0000-0002-6436-5733
Damon KimDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0003-3145-7559
Thomas ElgetiDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0002-7155-6044
Ingo Günter SteffenDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0003-2059-4275
Lars-Arne SchaafsDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0002-2250-5419
Anja CretnikDepartment of Cardiology, Angiology and Intensive Care Medicine, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0002-9994-7805
Bernd HammDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0002-9141-027X
Sebastian Niko NagelDepartment of Radiology, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.ORCID https://orcid.org/0000-0002-9489-2913

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In cardiac MRI, the field of view (FOV) is adapted to the individual patient's size, influencing spatial resolution and myocardial radiomics. This study aimed to investigate the effects of parametric feature maps on radiomics derived from cine images acquired with different FOV sizes on individuals without myocardial pathologies. In the clinical setting, cardiac MRI scans from clinical care were screened retrospectively for patients without pathological findings, neither in the MRI nor the medical history or follow-up, resulting in 61 included patients. In the experimental setting, 12 healthy volunteers were prospectively examined on a 1.5 Tesla MRI scanner with cine images acquired with three different FOVs (256 × 329 mm, 279 × 359 mm, 302 × 390 mm). One midventricular end-diastolic short-axis slice of the non-enhanced cine images was extracted for healthy volunteers and patients. The left ventricular myocardium was encompassed with regions of interest (ROIs). Ninety-three features were extracted using PyRadiomics. Images were converted to parametric radiomic feature maps using pretested software. ROIs were copied to the maps to retrieve the feature quantity. The variability of features across the different FOVs from the original images and feature maps was assessed with coefficients of variation (COVs) and rated stable at up to 10%. When derived from the original images, out of the 93 extracted features, only 24 (patients) and 29 (volunteers) revealed COVs < 10%. When extracted from the parametric maps, the number of stable features increased by 63% and 66%, with 39 (patients) and 48 (volunteers) features showing COVs < 10%, respectively. Software-computed parametric feature maps improve the reproducibility of radiomics across different FOVs in cardiac cine images of individuals without myocardial pathologies. Prospective investigations with different FOVs of a patient collective with myocardial pathologies could enhance the generalizability of the findings.

Indexed as

Heart DiseasesImage Interpretation, Computer-AssistedMagnetic Resonance Imaging, CineAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsProspective StudiesRadiomicsReproducibility of ResultsRetrospective StudiesVentricular Function, LeftCardiac magnetic resonance imagingCine MRIFeature mapRadiomicsReproducibility

Identifiers

PMID40266551
PMCPMC12162737

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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.