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dc.contributor.author
Kajita, Alexandre  
dc.contributor.author
Bezerra, Cristiano Guedes  
dc.contributor.author
Ozaki, Yuichi  
dc.contributor.author
Dan, Kazuhiro  
dc.contributor.author
Melaku, Gebremedhin D.  
dc.contributor.author
Pinton, Fabio A.  
dc.contributor.author
Falcão, Breno A. A.  
dc.contributor.author
Mariani, José  
dc.contributor.author
Bulant, Carlos Alberto  
dc.contributor.author
Maso Talou, Gonzalo Daniel  
dc.contributor.author
Esteves, Antonio  
dc.contributor.author
Blanco, Pablo Javier  
dc.contributor.author
Waksman, Ron  
dc.contributor.author
Garcia Garcia, Hector M.  
dc.contributor.author
Lemons, Pedro Alves  
dc.date.available
2021-02-09T04:49:13Z  
dc.date.issued
2019-02-25  
dc.identifier.citation
Kajita, Alexandre; Bezerra, Cristiano Guedes; Ozaki, Yuichi; Dan, Kazuhiro; Melaku, Gebremedhin D.; et al.; 500.05 Comparison Between Fractional Flow Reserve (FFR) vs. Computational Fractional Flow Reserve Derived from Three-dimensional Intravascular Ultrasound (IVUSFR) and Quantitative Flow Ratio (QFR); Elsevier; Jacc: Cardiovascular Interventions; 12; 4; 25-2-2019; 1-1  
dc.identifier.issn
1936-8798  
dc.identifier.uri
http://hdl.handle.net/11336/125166  
dc.description.abstract
BACKGROUND The determination of the ischemic status of a coronary artery by wireless physiologic assessment derived from angiography has been validated and approved in the US. However, the use ofplain angiography quantitative variables does not add much to thephysiology data since it has low correlation with fractional flowreserve (FFR) and predicts clinical outcomes poorly. Recently, a grayscale intravascular ultrasound (IVUS) derived physiology method(IVUSFR) was developed and showed a good correlation with invasiveFFR by combining the geometric advantages of IVUS with physiology.The aim of this study is to assess the coefficient of correlation (R) ofinvasive FFR compared to IVUSFR and quantitative flow ratio (QFR).METHODS Stable coronary artery disease (CAD) patients with intermediate lesions (i.e. 40?80% of diameter stenosis) were assessed by angiography and IVUS. QFR was derived from the angiography images, andIVUSFR was derived from quantitative IVUS data using computationalfluid dynamics. Coefficient of correlation (R) was used in this report.RESULTS Twenty-four patients with 34 lesions were included in theanalysis. The IVUSFR, invasive FFR, Vessel QFR fixed flow (vQFRf),and Vessel QFR contrast flow (vQFRc) values varied from 0.52 to 1.00,0.71 to 0.99, 0.55 to 1.00, and 0.34 to 1.00, respectively. The coefficient of correlation (R) of FFR vs. IVUSFR was 0.79; FFR vs. vQFRf was0.72; FFR vs. vQFRc was 0.65 (Figure).CONCLUSION Compared to invasive FFR, IVUSFR and vQFRf showed asimilar coefficient of correlation and were better than vQFR contrast flow  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
FFR  
dc.subject
IVUS  
dc.subject
QFR  
dc.subject.classification
Radiología, Medicina Nuclear y Diagnóstico por Imágenes  
dc.subject.classification
Medicina Clínica  
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CIENCIAS MÉDICAS Y DE LA SALUD  
dc.subject.classification
Otras Ingeniería Médica  
dc.subject.classification
Ingeniería Médica  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
500.05 Comparison Between Fractional Flow Reserve (FFR) vs. Computational Fractional Flow Reserve Derived from Three-dimensional Intravascular Ultrasound (IVUSFR) and Quantitative Flow Ratio (QFR)  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2020-11-18T21:21:33Z  
dc.journal.volume
12  
dc.journal.number
4  
dc.journal.pagination
1-1  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Kajita, Alexandre. Medstart; Estados Unidos  
dc.description.fil
Fil: Bezerra, Cristiano Guedes. Universidade Federal da Bahia; Brasil  
dc.description.fil
Fil: Ozaki, Yuichi. Medstart; Estados Unidos  
dc.description.fil
Fil: Dan, Kazuhiro. Medstart; Estados Unidos  
dc.description.fil
Fil: Melaku, Gebremedhin D.. Medstart; Estados Unidos  
dc.description.fil
Fil: Pinton, Fabio A.. Universidade de Sao Paulo; Brasil  
dc.description.fil
Fil: Falcão, Breno A. A.. Hospital of Messejana; Brasil  
dc.description.fil
Fil: Mariani, José. Universidade de Sao Paulo; Brasil  
dc.description.fil
Fil: Bulant, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. National Laboratory For Scientific Computing; Brasil  
dc.description.fil
Fil: Maso Talou, Gonzalo Daniel. National Laboratory For Scientific Computing; Brasil  
dc.description.fil
Fil: Esteves, Antonio. Universidade de Sao Paulo; Brasil  
dc.description.fil
Fil: Blanco, Pablo Javier. National Laboratory For Scientific Computing; Brasil  
dc.description.fil
Fil: Waksman, Ron. Medstart; Estados Unidos  
dc.description.fil
Fil: Garcia Garcia, Hector M.. Medstart; Estados Unidos  
dc.description.fil
Fil: Lemons, Pedro Alves. Universidade de Sao Paulo; Brasil  
dc.journal.title
Jacc: Cardiovascular Interventions  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S1936879819302006  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.jcin.2019.01.146