Evidence map›Paper›PMID 26507326›Full record

Observational studyThe international journal of cardiovascular imaging2016

The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography.

Lili Liu, Wenjie Yang, Yasuomi Nagahara, Yingguang Li, Saeb R Lamooki, Takashi Muramatsu, Pieter Kitslaar, Masayoshi Sarai, Yukio Ozaki, Peter Barlis and 3 more

Abstract readComparative StudyObservational Study
PubMed Publisher
In one paragraph

Observational study 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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Robotics, imaging, and artificial intelligence in the catheterisation laboratory.EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology · 2021
    Review
  4. Article
  5. Observational
  6. Article
  7. Cardiovascular imaging 2016 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2017
    Article
  8. Cardiovascular imaging 2015 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2016
    Review
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

13 authors.

Lili LiuBiomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Wenjie YangDepartment of Radiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yasuomi NagaharaDepartment of Cardiology, Fujita Health University Hospital, Toyoake, Japan.
Yingguang LiDivision of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Saeb R LamookiBiomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Takashi MuramatsuDepartment of Cardiology, Fujita Health University Hospital, Toyoake, Japan.
Pieter KitslaarDivision of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Masayoshi SaraiDepartment of Cardiology, Fujita Health University Hospital, Toyoake, Japan.
Yukio OzakiDepartment of Cardiology, Fujita Health University Hospital, Toyoake, Japan.
Peter BarlisDepartment of Medicine, Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.
Fuhua YanDepartment of Radiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Johan H C ReiberDivision of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Shengxian TuBiomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. sxtu@sjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calculation of fractional flow reserve (FFR) based on computational fluid dynamics (CFD) requires reconstruction of patient-specific coronary geometry and estimation of hyperemic flow rate. Coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) are two dominating imaging modalities used for the geometrical reconstruction. Our aim was to investigate the impact of image resolution as inherently associated with these two imaging modalities on geometrical reconstruction and subsequent FFR calculation. Patients with mild or intermediate coronary stenoses who underwent both CCTA and ICA were included. CCTA images were acquired either by 320-row area detector CT or by 128-slice dual-source CT. Two geometrical models were reconstructed separately from CCTA and ICA, from which FFRCTA and FFRQCA were subsequently calculated using CFD simulations, applying the same hyperemic flow rate derived from the ICA images at the inlet boundaries. A total of 57 vessels in 41 patients were analyzed. Average diameter stenosis was 43.4 ± 10.8 % by 3D QCA. Reasonably good correlation between FFRCTA and FFRQCA was observed (r = 0.71, p < 0.001). The difference between FFRCTA and FFRQCA was correlated with the deviation between minimal lumen areas by CCTA and by ICA (ρ = 0.34, p = 0.01), but not with plaque volume (ρ = -0.09, p = 0.51) or calcified plaque volume (ρ = 0.01, p = 0.95). Applying the cutoff value of ≤0.8 to both FFRCTA and FFRQCA, the agreement between FFRCTA and FFRQCA in discriminating functional significant stenoses was moderate (kappa 0.47, p < 0.001). Disagreement was found in 10 (17.5 %) vessels. Acceptable correlation between FFRCTA and FFRQCA was observed, while their agreement in distinguishing functional significant stenosis was moderate. Our results suggest that image resolution has a significant impact on FFR computation.

Indexed as

Fractional Flow Reserve, MyocardialImaging, Three-DimensionalMultidetector Computed TomographyAgedAlgorithmsCoronary AngiographyCoronary Artery DiseaseCoronary StenosisCoronary VesselsFemaleHumansHyperemiaImage Interpretation, Computer-AssistedMaleMiddle AgedModels, CardiovascularComputational fluid dynamicsCoronary computed tomography angiographyFractional flow reserveQuantitative coronary angiography

Identifiers

PMID26507326

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.