Evidence map›Paper›PMID 37243956›Full record

ArticleThe international journal of cardiovascular imaging2023

Agreement of wall shear stress distribution between two core laboratories using three-dimensional quantitative coronary angiography.

Shigetaka Kageyama, Vincenzo Tufaro, Ryo Torii, Grigoris V Karamasis, Roby D Rakhit, Eric K W Poon, Jean-Paul Aben, Andreas Baumbach, Patrick W Serruys, Yoshinobu Onuma and 1 more

Abstract read
In one paragraph

Article in The international journal of cardiovascular imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
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

11 authors.

Shigetaka Kageyama *Department of Cardiology, University of Galway, College of Medicine, Nursing and Health Sciences, Galway, Ireland.
Vincenzo Tufaro *Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK.
Ryo ToriiDepartment of Mechanical Engineering, University College London, London, UK.
Grigoris V KaramasisEssex Cardiothoracic Centre, Basildon, UK.
Roby D RakhitRoyal Free Hospital, London, UK.
Eric K W PoonDepartment of Mechanical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, Australia.
Jean-Paul AbenPie Medical Imaging, Maastricht, The Netherlands.
Andreas BaumbachDepartment of Cardiology, Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK.
Patrick W SerruysDepartment of Cardiology, University of Galway, College of Medicine, Nursing and Health Sciences, Galway, Ireland.
Yoshinobu OnumaDepartment of Cardiology, University of Galway, College of Medicine, Nursing and Health Sciences, Galway, Ireland.
Christos V BourantasDepartment of Cardiology, Barts Heart Centre, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK. cbourantas@gmail.com.

Funding

British Heart Foundation PG/17/18/32883
6 · The paper itself

Abstract

Wall shear stress (WSS) estimated in models reconstructed from intravascular imaging and 3-dimensional-quantitative coronary angiography (3D-QCA) data provides important prognostic information and enables identification of high-risk lesions. However, these analyses are time-consuming and require expertise, limiting WSS adoption in clinical practice. Recently, a novel software has been developed for real-time computation of time-averaged WSS (TAWSS) and multidirectional WSS distribution. This study aims to examine its inter-corelab reproducibility. Sixty lesions (20 coronary bifurcations) with a borderline negative fractional flow reserve were processed using the CAAS Workstation WSS prototype to estimate WSS and multi-directional WSS values. Analysis was performed by two corelabs and their estimations for the WSS in 3 mm segments across each reconstructed vessel was extracted and compared. In total 700 segments (256 located in bifurcated vessels) were included in the analysis. A high intra-class correlation was noted for all the 3D-QCA and TAWSS metrics between the estimations of the two corelabs irrespective of the presence (range: 0.90-0.92) or absence (range: 0.89-0.90) of a coronary bifurcation, while the ICC was good-moderate for the multidirectional WSS (range: 0.72-0.86). Lesion level analysis demonstrated a high agreement of the two corelabls for detecting lesions exposed to an unfavourable haemodynamic environment (WSS > 8.24 Pa, κ = 0.77) that had a high-risk morphology (area stenosis > 61.3%, κ = 0.71) and were prone to progress and cause events. The CAAS Workstation WSS enables reproducible 3D-QCA reconstruction and computation of WSS metrics. Further research is needed to explore its value in detecting high-risk lesions.

Indexed as

Coronary Artery DiseaseFractional Flow Reserve, MyocardialCoronary AngiographyCoronary VesselsHumansImaging, Three-DimensionalLaboratoriesPredictive Value of TestsReproducibility of ResultsStress, MechanicalComputational fluid dynamicsQuantitative coronary angiographyReproducibilityWall shear stress

Identifiers

PMID37243956
PMCPMC10427706

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.