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Arquivos Brasileiros de Cardiologia
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Arquivos Brasileiros de Cardiologia
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Performance Diagnóstica da FFR por Angiotomografia de Coronárias através de Software Baseado em Inteligência Artificial

Authors: Thamara Carvalho Morais; Antonildes Nascimento Assunção-Jr; Roberto Nery Dantas; Carla Franco Grego da Silva; Caroline Bastida de Paula; Roberto Almeida Torres; Tiago Augusto Magalhães; +3 Authors

Performance Diagnóstica da FFR por Angiotomografia de Coronárias através de Software Baseado em Inteligência Artificial

Abstract

FUNDAMENTO: A quantificação não invasiva da reserva fracionada de fluxo miocárdico (FFR (TC) ) através de software baseado em inteligência artificial em versão mais atualizada e tomógrafo de última geração (384 cortes) apresenta elevada performance na detecção de isquemia coronariana. OBJETIVOS: Avaliar o desempenho diagnóstico da FFR (TC) na detecção de doença arterial coronariana (DAC) significativa em relação ao FFRi, em tomógrafos de gerações anteriores (128 e 256 cortes). MÉTODOS: Estudo retrospectivo com pacientes encaminhados à angiotomografia de artérias coronárias (TCC) e cateterismo (FFRi). Foram utilizados os tomógrafos Siemens Somatom Definition Flash (256 cortes) e AS+ (128 cortes). A FFR (TC) e a área luminal mínima (ALM) foram avaliadas em software (cFFR versão 3.0.0, Siemens Healthineers, Forchheim, Alemanha). DAC obstrutiva foi definida como TCC com redução luminal ≥50% e DAC funcionalmente obstrutiva como FFRi ≤0,8. Todos os valores de p reportados são bicaudais; e quando <0,05, foram considerados estatisticamente significativos. RESULTADOS: Noventa e três pacientes consecutivos (152 vasos) foram incluídos. Houve boa concordância entre FFR (TC) e FFRi, com mínima superestimação da FFR (TC) (viés: –0,02; limites de concordância: 0,14 a 0,09). Diferentes tomógrafos não modificaram a relação entre FFR (TC) e FFRi (p para interação = 0,73). A FFR (TC) demonstrou performance significativamente superior à classificação visual de estenose coronariana (AUC 0,93 vs. 0,61, p <0,001) e à ALM (AUC 0,93 vs. 0,75, p <0,001) reduzindo o número de casos falso-positivos. O melhor ponto de corte para a FFR (TC) utilizando um índice de Youden foi de 0,85 (sensiblidade, 87%; especificidade, 86%; VPP, 73%; NPV, 94%), com redução de falso-positivos. CONCLUSÃO: FFR (TC) baseada em inteligência artificial, em tomógrafos de gerações anteriores (128 e 256 cortes), apresenta boa performance diagnóstica na detecção de DAC, podendo ser utilizada para reduzir procedimentos invasivos.

Keywords

Reserva Fracionada de Fluxo Miocárdico, Tomografia Computadorizada, Myocardial Ischemic, Artigo Original, Coronary Artery Disease, Isquemia Miocárdica, Machine Learning, Aprendizado de Máquina, Computed Tomography, RC666-701, Myocardial Fractional Flow Reserve, Diseases of the circulatory (Cardiovascular) system, Doença Arterial Coronariana

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Top 10%
Top 10%
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