Evidence map›Paper›PMID 41721845›Full record

ArticleEuropean radiology2026

Reproducibility of cardiac volumetric parameters derived from fully automatically prescribed image planes: a direct comparison to manual planning at 1.5-T and 3-T MRI.

Karolin K Deyerberg, Felix G Meinel, Lena-Maria Watzke, Ann-Christin Klemenz, Mathias Manzke, Margarita Gorodezky, Gaspar Delso, Antonia Dalmer, Roberto Lorbeer, Danagul Zhexenova and 2 more

Abstract readComparative Study
In one paragraph

Article in European radiology, 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.

Karolin K DeyerbergInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Felix G MeinelInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany. felix.meinel@med.uni-rostock.de.ORCID http://orcid.org/0000-0002-3201-1033
Lena-Maria WatzkeInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Ann-Christin KlemenzInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Mathias ManzkeInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Margarita GorodezkyGE HealthCare, Munich, Germany.
Gaspar DelsoGE HealthCare, Barcelona, Spain.
Antonia DalmerInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Roberto LorbeerDepartment of Radiology, Ludwig-Maximilian University, Munich, Germany.
Danagul ZhexenovaInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.
Marc-André WeberInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.ORCID http://orcid.org/0000-0003-3918-8066
Benjamin BöttcherInstitute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany.ORCID http://orcid.org/0009-0008-7892-8251

Funding

Else Kröner-Fresenius-Stiftung 2024_EKEA.186
6 · The paper itself

Abstract

objectivesThe prescription of cardiac MRI (CMR) image planes is essential for comparable volumetric assessment, but manual planning is time-consuming and error-prone. This prospective single-center study evaluated automated planning and its impact on the reproducibility of volumetric parameters derived from CMR. MATERIALS AND

methodsFifty-two healthy volunteers (26 males, median age 44.5 years) were divided into a 1.5 T sub-cohort (n = 32, both scans at 1.5 T, interval 2-5 weeks) and a 3 T sub-cohort (n = 20, 1st scan 1.5 T, 2nd scan 3 T, interval 1-2 h). All scans were performed using automated and manual planning with identical protocols, acquiring standard cardiac planes. Subjective quality of plane position was rated blinded by two radiologists. Volumetric analysis was performed fully automatically without corrections on SAX, retrieving right ventricular (RV) and left ventricular (LV) parameters. Wilcoxon matched-pairs signed rank test, intraclass correlation coefficient (ICC), and Bland-Altman analysis were used for statistical assessment.

resultsSubjective quality of image planes showed high consistency with good to excellent ratings in both sub-cohorts. Reproducibility of volumetric parameters was good to excellent (all ICC > 0.77) except for LVEF (1.5 T sub-cohort: LVEF manual: 0.323; automated: 0.213; 3 T sub-cohort: LVEF manual: 0.597; automated: 0.742). Overall, reproducibility was better in the 3 T sub-cohort, mainly due to different scan intervals. ICCs were slightly higher compared to manual planning across both sub-cohorts. These trends were also observed in the Bland-Altman analysis.

conclusionFully automated plane positioning for CMR provides high-quality image planes, ensuring high reproducibility of cardiac volumetric parameters across both established field strengths. KEY POINTS: Question The prescription of CMR image planes is essential for a comparable volumetric cardiac analysis, but manual planning is time-consuming and error-prone. Findings Automated plane prescription for CMR provides high-quality image planes, ensuring high reliability and reproducibility of cardiac volumetric parameters across both established field strengths. Clinical relevance Automated plane prescription for CMR reliably provides high-quality image planes, ensuring comparable cardiac volumetric parameters. This technology can simplify the acquisition and promises to reduce variability between follow-up scans, as well as to enhance the availability for patients.

Indexed as

HeartImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMagnetic Resonance Imaging, CineAdultFemaleHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsArtificial intelligenceAutomated workflowCardiacMagnetic resonance imagingReproducibility

Identifiers

PMID41721845
PMCPMC13282237

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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.