MRI in CFD for chronic type B aortic dissection: Ready for prime time?. (November 2022) - Wang, Qingdi; Guo, Xiaojing; Brooks, Mark; Chuen, Jason; Poon, Eric K.W.; Ooi, Andrew; Lim, Ruth P.
Abstract: Objectives: Better tools are needed for risk assessment of Type B aortic dissection (TBAD) to determine optimal treatment for patients with uncomplicated disease. Magnetic resonance imaging (MRI) has the potential to inform computational fluid dynamics (CFD) simulations for TBAD by providing individualised quantification of haemodynamic parameters, for assessment of complication risks. This systematic review aims to present an overview of MRI applications for CFD studies of TBAD. Methods: Following PRISMA guidelines, a search in Medline, Embase, and the Scopus Library identified 136 potentially relevant articles. Studies were included if they used MRI to inform CFD simulation in TBAD. Results: There were 20 articles meeting the inclusion criteria. 19 studies used phase contrast MRI (PC-MRI) to provide data for CFD flow boundary conditions. In 12 studies, CFD haemodynamic parameter results were validated against PC-MRI. In eight studies, geometric models were developed from MR angiography. In three studies, aortic wall or intimal flap motion data were derived from PC/cine MRI. Conclusions: MRI provides complementary patient-specific information in CFD haemodynamic studies for TBAD that can be used for personalised care. MRI provides structural, dynamic and flow data to inform CFD for pre-treatment planning, potentially advancing its integration into clinical decision-making. The use of MRI to inform CFD in TBAD surgical planning is promising, however further validation and larger cohort studies are required. Highlights: A systematic review of integrating magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) in Type B aortic dissection (TBAD). MRI plays roles in providing flow data for CFD boundary conditions, validating simulation results, and giving wall motion information. Proposal of incorporating multiple MRI modalities to provide patient-specific data and improve the computational modelling of TBAD.