The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFRCT, or high-risk plaque features?
Objectives: The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFRCT algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically significant, with reference to FFRICA.Methods: Pa...
| Publicado en: | European Radiology Vol. 29; no. 7; pp. 3647 - 3658 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2019
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| Acceso en línea: | Ver este registro en EBSCOhost |