ArticleMagnetic resonance in medicine2019
Caval to pulmonary 3D flow distribution in patients with Fontan circulation and impact of potential 4D flow MRI error sources.
Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Impact of Contour Boundary Offsets on 4D Flow CMR-Derived Intracardiac Haemodynamic Parameters.Journal of cardiovascular development and disease · 2026Article
- Following the flow: in vivo imaging of fetal foramen ovale physiology using four-dimensional flow magnetic resonance imaging with doppler ultrasound gating.Radiology case reports · 2026Article
- Robust and fast stochastic 4D flow vector-field signature technique for quantifying composite flow dynamics from 4D flow MRI: Application to left atrial flow in atrial fibrillation.Medical image analysis · 2024Article
- Impact of pulmonary artery flow distribution on Fontan hemodynamics and flow energetics.Pediatric radiology · 2023Article
- Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications.Applied sciences (Basel, Switzerland) · 2022Article
- Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data.Scientific reports · 2021Article
- Reduced scan time and superior image quality with 3D flow MRI compared to 4D flow MRI for hemodynamic evaluation of the Fontan pathway.Scientific reports · 2021Article
- 4D flow MRI applications in congenital heart disease.European radiology · 2021Review
- Respiration Dependency of Caval Blood Flow in Patients with Fontan Circulation: Quantification Using 5D Flow MRI.Radiology. Cardiothoracic imaging · 2019Article
- Multipoint 5D flow cardiovascular magnetic resonance - accelerated cardiac- and respiratory-motion resolved mapping of mean and turbulent velocities.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
purposeUneven flow distribution in patients with Fontan circulation is suspected to lead to complications. 4D flow MRI offers evaluation using time-resolved pathlines; however, the potential error is not well understood. The aim of this study was to systematically assess variability in flow distribution caused by well-known sources of error.
methods4D flow MRI was acquired in 14 patients with Fontan circulation. Flow distribution was quantified by the % of caval venous flow pathlines reaching the left and right pulmonary arteries. Impact of data acquisition and data processing uncertainties were investigated by (1) probabilistic 4D blood flow tracking at varying noise levels, (2) down-sampling to mimic acquisition at different spatial resolutions, (3) pathline calculation with and without eddy current correction, and (4) varied segmentation of the Fontan geometry to mimic analysis errors.
resultsAveraged among the cohort, uncertainties accounted for flow distribution errors from noise ≤3.2%, low spatial resolution ≤2.3% to 3.8%, eddy currents ≤6.4%, and inaccurate segmentation ≤3.9% to 9.1% (dilation and erosion, respectively). In a worst-case scenario (maximum additive errors for all 4 sources), flow distribution errors were as high as 22.5%.
conclusionInaccuracies related to postprocessing (segmentation, eddy currents) resulted in the largest potential error (≤15.5% combined) whereas errors related to data acquisition (noise, low spatial resolution) had a lower impact (≤5.5%-7.0% combined). Whereas it is unlikely that these errors will be additive or affect the identification of severe asymmetry, these results illustrate the importance of eddy current correction and accurate segmentation to minimize Fontan flow distribution errors.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.