Evidence map›Paper›PMID 29566702›Full record

ArticleBiomedical engineering online2018

A new CFD based non-invasive method for functional diagnosis of coronary stenosis.

Xinzhou Xie, Minwen Zheng, Didi Wen, Yabing Li, Songyun Xie

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.6field-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

11 citing papers in PubMed, 29 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Xinzhou XieDepartment of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China. xinzhxie@hotmail.com.
Minwen ZhengDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, 15 West Changle Road, Xi'an, Shaanxi, People's Republic of China.
Didi WenDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, 15 West Changle Road, Xi'an, Shaanxi, People's Republic of China.
Yabing LiDepartment of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China.
Songyun XieDepartment of Electronic Science and Technology, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shaanxi, People's Republic of China.
Northwestern Polytechnical University · CNAir Force Medical University · CN

Funding

Fundamental Research Funds for the Central Universities 3102017jc11002National Natural Science Foundation of China 61601368National Natural Science Foundation of China 81471663Natural Science Basic Research Plan in Shaanxi Province of China 2017JQ6012
6 · The paper itself

Abstract

backgroundAccurate functional diagnosis of coronary stenosis is vital for decision making in coronary revascularization. With recent advances in computational fluid dynamics (CFD), fractional flow reserve (FFR) can be derived non-invasively from coronary computed tomography angiography images (FFR

methodsInstead of modeling maximal hyperemia condition, a series of boundary conditions are specified and those simulated results are combined to provide a pressure-flow curve for a stenosis. Then, functional diagnosis of stenosis is assessed based on parameters derived from the obtained pressure-flow curve.

resultsThe proposed method is applied to both idealized and patient-specific models, and validated with invasive FFR in six patients. Results show that additional hemodynamic information about the flow resistances of a stenosis is provided, which cannot be directly obtained from anatomy information. Parameters derived from the simulated pressure-flow curve show a linear and significant correlations with invasive FFR (r > 0.95, P < 0.05).

conclusionThe proposed method can assess flow resistances by the pressure-flow curve derived parameters without modeling of maximal hyperemia condition, which is a new promising approach for non-invasive functional assessment of coronary stenosis.

Indexed as

Computer SimulationHydrodynamicsCoronary StenosisHumansPatient-Specific ModelingPressureCFDFunctional coronary stenosisNon-invasive assessmentPressure-flow curve

Identifiers

PMID29566702
PMCPMC5863834
OpenAlexW2801752769

What OpenQuestion holds

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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.