Assessment of factors associated with measurability of fractional flow reserve derived from coronary computed tomography angiography in type 2 diabetic ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10-19

AUTHORS

Tsuyoshi Nozue, Takeshi Takamura, Kazuki Fukui, Kiyoshi Hibi, Satoru Kishi, Ichiro Michishita

ABSTRACT

Recently, fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFRCT) has been developed. However, FFRCT cannot be calculated for all patients from CCTA datasets. The purpose of the present study, therefore, was to evaluate the predictors that results in cases being inappropriate for FFRCT processing. This study was a sub-analysis of the TRACT trial, from which 50 patients were divided into 2 groups according to FFRCT measurability (measurable [group M] or not measurable [group N]) using CCTA examination at baseline. Thirty-nine (78%) patients comprised group M and 11 (22%) comprised group N. Heart rate at CCTA examination (72 beats/min vs. 63 beats/min; p = 0.007) and Agatston score (665 vs. 33; p = 0.002) in group N were significantly higher than those in group M. Multivariate logistic regression analyses revealed that heart rate at CCTA examination (OR 1.348 [95% CI 1.167–1.556]; p < 0.001) and Agatston score (OR 1.002 [95% CI 1.000–1.003]; p = 0.004) were significant, independent factors associated with non-measurability of FFRCT. The frequency of poor image quality was highest in patients with heart rate > 65 beats/min and Agatston score > 400 (p < 0.0001). In conclusions, high heart rate at the time of CCTA examination and higher Agatston score were associated with poor image quality that resulted in cases being inappropriate for FFRCT processing. Heart rate control at CCTA examination is necessary to acquire good-quality images required for computing FFRCT. More... »

PAGES

359-365

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10554-018-1476-0

DOI

http://dx.doi.org/10.1007/s10554-018-1476-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107729067

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30341670


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