Evidence map›Paper›PMID 38558490›Full record

ArticleJournal of magnetic resonance imaging : JMRI2025

Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping.

Thomas In de Braekt, Jean-Paul Aben, Marc Maussen, Harrie C M van den Bosch, Patrick Houthuizen, Arno A W Roest, Pieter J van den Boogaard, Hildo J Lamb, Jos J M Westenberg

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

9 authors.

Thomas In de BraektDepartment of Radiology, Catharina Hospital, Eindhoven, the Netherlands.ORCID https://orcid.org/0000-0001-7945-3421
Jean-Paul AbenPie Medical Imaging BV, Maastricht, the Netherlands.
Marc MaussenPie Medical Imaging BV, Maastricht, the Netherlands.
Harrie C M van den BoschDepartment of Radiology, Catharina Hospital, Eindhoven, the Netherlands.
Patrick HouthuizenDepartment of Cardiology, Catharina Hospital, Eindhoven, the Netherlands.
Arno A W RoestDepartment of Pediatric Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
Pieter J van den BoogaardDepartment of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
Hildo J LambDepartment of Radiology, Leiden University Medical Center, Leiden, the Netherlands.ORCID https://orcid.org/0000-0002-6969-2418
Jos J M WestenbergDepartment of Radiology, Leiden University Medical Center, Leiden, the Netherlands.ORCID https://orcid.org/0000-0003-1946-1715

Funding

Radiological Society of the Netherlands (NVvR) 1261584
6 · The paper itself

Abstract

backgroundAutomated 4D flow MRI valvular flow quantification without time-consuming manual segmentation might improve workflow. PURPOSE: Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c-AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF). STUDY TYPE: Retrospective. POPULATION: 27 c-AVSD patients (median, 23 years; interquartile range, 16-31 years) and 24 healthy volunteers (25 years; 12.5-36.5 years). FIELD STRENGTH/SEQUENCE: Whole-heart 4D flow MRI and cine steady-state free precession at 3T. ASSESSMENT: After automatic valve tracking, valve annuli were segmented on time-resolved reformatted trans-valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency. STATISTICAL TESTS: Comparisons between methods were assessed by Wilcoxon signed-rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.

resultsAMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from -0.7-1.0 mL, -0.5-2.8 mL, -1.1-3.6 mL, and - 3.1--2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%-7.5% and 3.8%-4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong-to-excellent for NFV and RF (ICC ≥0.88). DATA

conclusionMS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Indexed as

Heart ValvesAdolescentAdultBlood Flow VelocityChildFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMagnetic Resonance Imaging, CineMaleReproducibility of ResultsRetrospective StudiesYoung Adult4D flow MRIautomated valve segmentationnet flow volumepostprocessing analysis timeregurgitation fraction

Identifiers

PMID38558490
PMCPMC11645491

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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.