Evidence map›Paper›PMID 40985755›Full record

ArticleCardiovascular research2025

Invasive validation of novel 1D models for computation of coronary fractional flow reserve.

Daniel J Taylor, Harry Saxton, Xu Xu, Eron Yones, Louise Aubiniere-Robb, Thilanka Adikari, Tom Newman, Marcel van 't Veer, Daniëlle C J Keulards, Pim Tonino and 7 more

Abstract readValidation StudyComparative Study
In one paragraph

Article in Cardiovascular research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Daniel J TaylorDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.ORCID 0000-0003-1068-1236
Harry SaxtonInsigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
Xu XuInsigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, UK.
Eron YonesDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Louise Aubiniere-RobbDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Thilanka AdikariKingston and Richmond NHS Foundation Trust, London, UK.
Tom NewmanDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Marcel van 't VeerDepartment of Cardiology, Catharina Hospital, Eindhoven, Netherlands.
Daniëlle C J KeulardsDepartment of Cardiology, Catharina Hospital, Eindhoven, Netherlands.
Pim ToninoDepartment of Cardiology, Catharina Hospital, Eindhoven, Netherlands.
Rebecca GoslingDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.ORCID 0000-0001-7465-3563
Krzysztof CzechowiczDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.ORCID 0000-0002-0605-8591
Andrew NarracottDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
David R HoseDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Julian P GunnDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Ian HallidayDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.
Paul D MorrisDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK.ORCID 0000-0002-3965-121X

Funding

NIHR Sheffield Biomedical Research Centre
6 · The paper itself

Abstract

aimsComputed virtual fractional flow reserve (vFFR), derived from invasive angiography, non-invasively quantifies coronary epicardial lesion physiology. Developments of 1-dimensional (1D) vFFR models have introduced methods of side-branch flow representation and reduced simulation time by several orders of magnitude vs. 3-dimensional (3D) alternatives. This study aimed to quantify agreement and diagnostic accuracy of 1D and 3D vFFR models, in a matched cohort, and compare results with established FFR alternatives. METHODS AND

resultsWe used five 1D models, which differed in their side-branch flow representation, to compute vFFR in 104 arteries. The simplest model ignored side-branch flow, the second and third models used vessel anatomy to homogenously distribute side-branch flow and regionalize this to bifurcations, respectively. The final two 1D models additionally used simulated pressure in the main vessel to modulate side-branch flow magnitude. To aid interpretability, diagnostic accuracy was also reported for 3D vFFR, visual assessment and resting invasive pressure assessment (Pd/Pa). Median FFR was 0.81 [0.73-0.88] and 46 (44%) lesions were haemodynamically significant. Optimal FFR agreement was achieved with the 1D model that regionalized side-branch flow to bifurcations (mean bias at diagnostic threshold -0.03, 95% agreement limits -0.23 to 0.20). Diagnostic accuracy did not differ significantly between the five 1D models, with area under the curve (AUC) values ranging 0.68 to 0.74. Diagnostic accuracy for 1D vFFR was superior to visual assessment, comparable to 3D vFFR and poorer than invasive resting pressure assessment.

conclusion1D models of vFFR facilitate rapid in-silico assessment of epicardial lesion severity. Inclusion of anatomical side branch flow mildly improved agreement, but the additional inclusion of simulated pressure was not beneficial. Agreement of 1D models was comparable to 3D simulations. However, current 1D models are not sufficiently accurate to suggest they may entirely replace wire-based assessment.

Indexed as

Cardiac CatheterizationCoronary AngiographyCoronary Artery DiseaseCoronary StenosisCoronary VesselsFractional Flow Reserve, MyocardialModels, CardiovascularAgedComputer SimulationFemaleHumansMaleMiddle AgedPredictive Value of TestsReproducibility of Results1D modellingComputational fluid dynamicsCoronary artery diseasePercutaneous coronary interventionVirtual fractional flow reserve

Identifiers

PMID40985755
PMCPMC12638729

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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.