Evidence map›Paper›PMID 42282208›Full record

ArticlemedRxiv : the preprint server for health sciences2026

MRI-Based Pressure Gradient Mapping in Patient-Specific Models of Coarctation of the Aorta.

Priya J Nair, Lorenzo Ferrari, Michael Loecher, Charles McGrath, Carlos A Castillo Passi, Alison L Marsden, Daniel B Ennis

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

7 authors.

Priya J NairDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID 0000-0001-6326-9777
Lorenzo FerrariStanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
Michael LoecherStanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
Charles McGrathStanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
Carlos A Castillo PassiStanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
Alison L MarsdenDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Daniel B EnnisStanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.

Funding

Fast and Accurate Cardiovascular MRI with Hyper 4D-FlowR01HL171515 · NHLBI · STANFORD UNIVERSITY · PI Daniel B Ennis, Shreyas S Vasanawala · 2024 to 2026
$1.9M
Estimating Pressure Gradients in CHD with 4D-Flow MRI and Physics-Informed Bayesian InferenceR01HL183592 · NHLBI · STANFORD UNIVERSITY · PI Daniel B Ennis · 2026 to 2026
$755k
NHLBI NIH HHS R01 HL171515NHLBI NIH HHS R01 HL183592
6 · The paper itself

Abstract

Purpose: Accurate assessment of the pressure gradient ( Methods: Patient-specific compliant aortic phantoms were created from clinical MRI data of two patients with CoA. Additional geometries were synthetically generated by increasing stenosis severity. Phantoms were studied in an MRI-compatible flow loop under physiologically realistic flow and pressure conditions. Pressure gradients were estimated using conventional 4D-Flow MRI, 4D-FlowP, and fluid-structure interaction (FSI) simulations. Results were compared against ground-truth catheter-based measurements across multiple flow rates and stenosis severities. Results: Conventional 4D-Flow consistently underestimated Conclusion: 4D-FlowP enables a more accurate MRI-based pressure gradient mapping in CoA than conventional 4D-Flow, when compared to ground truth catheter measurements. These findings support further

Indexed as

4D-Flow MRIaortic coarctationcomputational fluid dynamicshemodynamics

Identifiers

PMID42282208
PMCPMC13252443

What OpenQuestion holds

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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.