Noninvasive CT-based hemodynamic assessment of coronary lesions derived from fast computational analysis: a comparison against fractional flow reserve View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Panagiotis K. Siogkas, Constantinos D. Anagnostopoulos, Riccardo Liga, Themis P. Exarchos, Antonis I. Sakellarios, George Rigas, Arthur J. H. A. Scholte, M. I. Papafaklis, Dimitra Loggitsi, Gualtiero Pelosi, Oberdan Parodi, Teemu Maaniitty, Lampros K. Michalis, Juhani Knuuti, Danilo Neglia, Dimitrios I. Fotiadis

ABSTRACT

OBJECTIVES: Application of computational fluid dynamics (CFD) to three-dimensional CTCA datasets has been shown to provide accurate assessment of the hemodynamic significance of a coronary lesion. We aim to test the feasibility of calculating a novel CTCA-based virtual functional assessment index (vFAI) of coronary stenoses > 30% and ≤ 90% by using an automated in-house-developed software and to evaluate its efficacy as compared to the invasively measured fractional flow reserve (FFR). METHODS AND RESULTS: In 63 patients with chest pain symptoms and intermediate (20-90%) pre-test likelihood of coronary artery disease undergoing CTCA and invasive coronary angiography with FFR measurement, vFAI calculations were performed after 3D reconstruction of the coronary vessels and flow simulations using the finite element method. A total of 74 vessels were analyzed. Mean CTCA processing time was 25(± 10) min. There was a strong correlation between vFAI and FFR, (R = 0.93, p < 0.001) and a very good agreement between the two parameters by the Bland-Altman method of analysis. The mean difference of measurements from the two methods was 0.03 (SD = 0.033), indicating a small systematic overestimation of the FFR by vFAI. Using a receiver-operating characteristic curve analysis, the optimal vFAI cutoff value for identifying an FFR threshold of ≤ 0.8 was ≤ 0.82 (95% CI 0.81 to 0.88). CONCLUSIONS: vFAI can be effectively derived from the application of computational fluid dynamics to three-dimensional CTCA datasets. In patients with coronary stenosis severity > 30% and ≤ 90%, vFAI performs well against FFR and may efficiently distinguish between hemodynamically significant from non-significant lesions. KEY POINTS: Virtual functional assessment index (vFAI) can be effectively derived from 3D CTCA datasets. In patients with coronary stenoses severity > 30% and ≤ 90%, vFAI performs well against FFR. vFAI may efficiently distinguish between functionally significant from non-significant lesions. More... »

PAGES

2117-2126

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-018-5781-8

DOI

http://dx.doi.org/10.1007/s00330-018-5781-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107640276

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30324382


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    "description": "OBJECTIVES: Application of computational fluid dynamics (CFD) to three-dimensional CTCA datasets has been shown to provide accurate assessment of the hemodynamic significance of a coronary lesion. We aim to test the feasibility of calculating a novel CTCA-based virtual functional assessment index (vFAI) of coronary stenoses >\u200930% and \u2264\u200990% by using an automated in-house-developed software and to evaluate its efficacy as compared to the invasively measured fractional flow reserve (FFR).\nMETHODS AND RESULTS: In 63 patients with chest pain symptoms and intermediate (20-90%) pre-test likelihood of coronary artery disease undergoing CTCA and invasive coronary angiography with FFR measurement, vFAI calculations were performed after 3D reconstruction of the coronary vessels and flow simulations using the finite element method. A total of 74 vessels were analyzed. Mean CTCA processing time was 25(\u00b1\u200910)\u00a0min. There was a strong correlation between vFAI and FFR, (R\u2009=\u20090.93, p\u2009<\u20090.001) and a very good agreement between the two parameters by the Bland-Altman method of analysis. The mean difference of measurements from the two methods was 0.03 (SD\u2009=\u20090.033), indicating a small systematic overestimation of the FFR by vFAI. Using a receiver-operating characteristic curve analysis, the optimal vFAI cutoff value for identifying an FFR threshold of \u2264\u20090.8 was \u2264\u20090.82 (95% CI 0.81 to 0.88).\nCONCLUSIONS: vFAI can be effectively derived from the application of computational fluid dynamics to three-dimensional CTCA datasets. In patients with coronary stenosis severity >\u200930% and \u2264\u200990%, vFAI performs well against FFR and may efficiently distinguish between hemodynamically significant from non-significant lesions.\nKEY POINTS: Virtual functional assessment index (vFAI) can be effectively derived from 3D CTCA datasets. In patients with coronary stenoses severity >\u200930% and \u2264\u200990%, vFAI performs well against FFR. vFAI may efficiently distinguish between functionally significant from non-significant lesions.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5781-8'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5781-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5781-8'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5781-8'


 

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