CT derived fractional flow reserve: Part 1 - Comprehensive review of methodologies

Area of Science:

• Cardiovascular Imaging
• Medical Diagnostics
• Computational Physiology

Background:

• Cardiac computed tomography angiography (CCTA) traditionally provides anatomical information.
• Recent advancements allow CCTA to yield crucial physiological data.
• Assessing coronary physiology non-invasively is a significant clinical need.

Purpose of the Study:

• To review methodologies for deriving fractional flow reserve (FFR) from CCTA.
• To focus on computational fluid dynamics-based FFR (CT-FFR) and AI-driven plaque analysis.
• To explore the expansion of CCTA beyond anatomical assessment for non-invasive coronary physiology evaluation.

Main Methods:

• Overview of computational fluid dynamics (CFD) principles applied to CT-FFR.
• Description of artificial intelligence (AI) and quantitative plaque metrics for ischemia assessment.
• Analysis of workflows and limitations for each non-invasive technique.

Main Results:

• CCTA can now provide functional information, complementing anatomical data.
• CT-FFR and AI-based plaque analysis are key emerging non-invasive methods.
• These techniques reduce the need for invasive diagnostic procedures.

Conclusions:

• Non-invasive assessment of coronary physiology using CCTA is rapidly evolving.
• CT-FFR and AI-driven plaque analysis represent significant advancements.
• Future directions point towards integrated anatomical and physiological assessment via CCTA.