Evidence map›Paper›PMID 35130153›Full record

ArticleIEEE transactions on medical imaging2022

Modeling Bias Error in 4D Flow MRI Velocity Measurements.

Sean M Rothenberger, Jiacheng Zhang, Melissa C Brindise, Susanne Schnell, Michael Markl, Pavlos P Vlachos, Vitaliy L Rayz

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
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

11 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 4D flow MRI velocity uncertainty quantification.Magnetic resonance in medicine · 2025
    Article
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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

7 authors at 2 institutions in 1 country.

Sean M Rothenberger
Jiacheng Zhang
Melissa C Brindise
Susanne Schnell
Michael Markl
Pavlos P Vlachos
Vitaliy L Rayz
Purdue University West Lafayette · USNorthwestern University · US

Funding

Risk Assessment of Cerebral Aneurysm Growth with 4D flow MRIR01HL115267 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANSARI, SAMEER A, LAWTON, MICHAEL T · 2013 to 2023
$4.2M
Multi-modality 4D Flow MRI data enhancement for quantification of cerebral aneurysms hemodynamicsR21NS106696 · NINDS · PURDUE UNIVERSITY · PI RAYZ, VITALIY L, SCHNELL, SUSANNE · 2018 to 2019
$419k
NHLBI NIH HHS R01 HL115267NINDS NIH HHS R21 NS106696
6 · The paper itself

Abstract

We present a model to estimate the bias error of 4D flow magnetic resonance imaging (MRI) velocity measurements. The local instantaneous bias error is defined as the difference between the expectation of the voxel's measured velocity and actual velocity at the voxel center. The model accounts for bias error introduced by the intra-voxel velocity distribution and partial volume (PV) effects. We assess the intra-voxel velocity distribution using a 3D Taylor Series expansion. PV effects and numerical errors are considered using a Richardson extrapolation. The model is applied to synthetic Womersley flow and in vitro and in vivo 4D flow MRI measurements in a cerebral aneurysm. The bias error model is valid for measurements with at least 3.75 voxels across the vessel diameter and signal-to-noise ratio greater than 5. All test cases exceeded this diameter to voxel size ratio with diameters, isotropic voxel sizes, and velocity ranging from 3-15mm, 0.5-1mm, and 0-60cm/s, respectively. The model accurately estimates the bias error in voxels not affected by PV effects. In PV voxels, the bias error is an order of magnitude higher, and the accuracy of the bias error estimation in PV voxels ranges from 67.3% to 108% relative to the actual bias error. The bias error estimated for in vivo measurements increased two-fold at systole compared to diastole in partial volume and non-partial volume voxels, suggesting the bias error varies over the cardiac cycle. This bias error model quantifies 4D flow MRI measurement accuracy and can help plan 4D flow MRI scans.

Indexed as

Intracranial AneurysmMagnetic Resonance ImagingBlood Flow VelocityHumansImaging, Three-DimensionalReproducibility of ResultsSignal-To-Noise Ratio

Identifiers

PMID35130153
PMCPMC9247036
OpenAlexW4210872849

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.