Does ML-based CT-FFR improve the diagnostic performance of cCTA for ruling out significant CAD in elderly patients before TAVR?
Adding ML-based CT-FFR to cCTA during pre-TAVR planning may improve diagnostic accuracy and reduce unnecessary invasive coronary angiographies.
ML-based CT-FFR may further improve the diagnostic performance of cCTA by correctly reclassifying a considerable proportion of patients with morphological signs of obstructive CAD on cCTA during pre-TAVR evaluation. Thereby, CT-FFR has the potential to further reduce the need for ICA in this challenging elderly group of patients before TAVR.
Gohmann et al. (Wed,) studied this question.
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