Evidence map›Paper›PMID 34608218›Full record

ArticleScientific reports2021

The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography.

Roshni Solanki, Rebecca Gosling, Vignesh Rammohan, Giulia Pederzani, Pankaj Garg, James Heppenstall, D Rodney Hose, Patricia V Lawford, Andrew J Narracott, John Fenner and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  4. Patient-specificFrontiers in cardiovascular medicine · 2024
    Review
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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

12 authors at 3 institutions in 1 country.

Roshni SolankiDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Rebecca GoslingDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Vignesh RammohanDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Giulia PederzaniDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Pankaj GargInsigneo Institute for In Silico Medicine, University of Sheffield, Sheffield, UK.
James HeppenstallDepartment of Radiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
D Rodney HoseDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Patricia V LawfordDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Andrew J NarracottDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
John FennerDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Julian P GunnDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK.
Paul D MorrisDepartment of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK. paul.morris@sheffield.ac.uk.
Insigneo · GBUniversity of Sheffield · GBSheffield Teaching Hospitals NHS Foundation Trust · GB

Funding

British Heart Foundation FS/12/85/29869British Heart Foundation FS/16/48/32306British Heart Foundation TG/19/1/34451Medical Research Council MC_PC_13076Wellcome Trust 214567
6 · The paper itself

Abstract

Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute 'virtual' fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet the methods required remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR. Clinically realistic coronary phantom models were created comprosing seven standard stenoses in aluminium and 15 patient-based 3D-printed, imaged with CA, three times, according to standard clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the real phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n = 45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (± 0.03 mm) which was < 1% (95% CI 0.13-1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ± 0.06 (Bland Altman 95% limits of agreement). Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but contribute to clinically relevant errors when used to compute vFFR.

Indexed as

Fractional Flow Reserve, MyocardialImaging, Three-DimensionalCoronary AngiographyCoronary Artery DiseaseCoronary VesselsHumansImage Processing, Computer-AssistedPhantoms, ImagingReproducibility of Results

Identifiers

PMID34608218
PMCPMC8490364
OpenAlexW3202103453

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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.