CT derived fractional flow reserve: Part 2 – Critical appraisal of the literature
Patricia Rodriguez-Lozano, Anam Waheed, Sotirios Evangelou, Márton Kolossváry, Kashif Shaikh, Saira Siddiqui, Lauren Stipp, Suvasini Lakshmanan, En-Haw Wu, Nick S. Nurmohamed, Ady Orbach, Vinit Baliyan, João Matos, S. Trivedi, Nidhi Madan, Todd C. Villines, Abdul Rahman Ihdayhid
Abstract
The integration of computed tomography-derived fractional flow reserve (CT-FFR), utilizing computational fluid dynamics and artificial intelligence (AI) in routine coronary computed tomographic angiography (CCTA), presents a promising approach to enhance evaluations of functional lesion severity. Extensive evidence underscores the diagnostic accuracy, prognostic significance, and clinical relevance of CT-FFR, prompting recent clinical guidelines to recommend its combined use with CCTA for selected individuals with with intermediate stenosis on CCTA and stable or acute chest pain. This manuscript critically examines the existing clinical evidence, evaluates the diagnostic performance, and outlines future perspectives for integrating noninvasive assessments of coronary anatomy and physiology. Furthermore, it serves as a practical guide for medical imaging professionals by addressing common pitfalls and challenges associated with CT-FFR while proposing potential solutions to facilitate its successful implementation in clinical practice.