One-dimensional computational flow modelling using patient specific geometry to assess fractional flow reserve (FFR) - KEVIN MOHEE (2022)
Fractional flow reserve (FFR) improves the assessment of the physiological significance of coronary lesions compared with conventional angiography. However, it requires additional interventional techniques and equipment to perform. Multiple proposed virtual functional indices are derived from coronary imaging alone but require complex computational fluid dynamics modelling which is time-consuming and hence cannot influence immediate clinical management. The Zienkiewicz Centre for Computational Engineering at Swansea University has developed a reduced order one-dimensional model that generates a “virtual” value of FFR in considerably less time but its accuracy is unknown and has not been validated against invasive FFR. This MSc by research project aims to refine this 1D model with patient specific data and use it to predict the severity of blood flow reduction caused by individual plaques. Clinical data obtained from coronary angiography will be used and patient-specific data will be generated and then validated by already measured invasive derived FFR data. The study will cover blood flow modelling in different arterial network and assess fractional flow reserve (a physiological index determined from the ratio of the pressure distal to a stenosis relative to that before the stenosis).