Evidence map›Paper›PMID 27539731›Full record

ArticleThe international journal of cardiovascular imaging2016

Optimisation of coronary vascular territorial 3D echocardiographic strain imaging using computed tomography: a feasibility study using image fusion.

Martina Chantal de Knegt, A Fuchs, P Weeke, R Møgelvang, C Hassager, K F Kofoed

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in The international journal of cardiovascular imaging, 2016. 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
1.7field-weighted citation impact, top 16% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Hybrid anatomo-functional imaging of coronary artery disease: Beneficial irrespective of its core components.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2019
    Review
  6. Cardiovascular imaging 2016 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2017
    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

6 authors at 2 institutions in 1 country.

Martina Chantal de KnegtDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark. martinadeknegt@gmail.com.
A FuchsDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
P WeekeDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
R MøgelvangDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
C HassagerDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
K F KofoedDepartment of Cardiology 2014, Faculty of Health Sciences, The Heart Center, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, 2100, Copenhagen, Denmark.
Rigshospitalet · DKUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current echocardiographic assessments of coronary vascular territories use the 17-segment model and are based on general assumptions of coronary vascular distribution. Fusion of 3D echocardiography (3DE) with multidetector computed tomography (MDCT) derived coronary anatomy may provide a more accurate assessment of left ventricular (LV) territorial function. We aimed to test the feasibility of MDCT and 3DE fusion and to compare territorial longitudinal strain (LS) using the 17-segment model and a MDCT-guided vascular model. 28 patients underwent 320-slice MDCT and transthoracic 3DE on the same day followed by invasive coronary angiography. MDCT (Aquilion ONE, ViSION Edition, Toshiba Medical Systems) and 3DE apical full-volume images (Artida, Toshiba Medical Systems) were fused offline using a dedicated workstation (prototype fusion software, Toshiba Medical Systems). 3DE/MDCT image alignment was assessed by 3 readers using a 4-point scale. Territorial LS was assessed using the 17-segment model and the MDCT-guided vascular model in territories supplied by significantly stenotic and non-significantly stenotic vessels. Successful 3DE/MDCT image alignment was obtained in 86 and 93 % of cases for reader one, and reader two and three, respectively. Fair agreement on the quality of automatic image alignment (intra-class correlation = 0.40) and the success of manual image alignment (Fleiss' Kappa = 0.40) among the readers was found. In territories supplied by non-significantly stenotic left circumflex arteries, LS was significantly higher in the MDCT-guided vascular model compared to the 17-segment model: -15.00 ± 7.17 (mean ± standard deviation) versus -11.87 ± 4.09 (p < 0.05). Fusion of MDCT and 3DE is feasible and provides physiologically meaningful displays of myocardial function.

Indexed as

Computed Tomography AngiographyEchocardiography, Three-DimensionalMultidetector Computed TomographyRadiographic Image Interpretation, Computer-AssistedVentricular Function, LeftAgedCoronary AngiographyCoronary StenosisCoronary VesselsFeasibility StudiesFemaleHumansMaleMiddle AgedModels, CardiovascularMultimodal ImagingLongitudinal strainMultidetector computed tomographyMultimodality imagingThree-dimensional echocardiography

Identifiers

PMID27539731
OpenAlexW2513538242

What OpenQuestion holds

Textmetadata
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.