PATIENT-SPECIFIC PREDICTION OF FALSE LUMEN THROMBOSIS IN TYPE B AORTIC DISSECTION
Claudia Menichini1, Zhuo Cheng1, Richard G.J. Gibbs1,3, Xiao Yun Xu1
1Imperial College London, UK;
2St. Mary’s Hospital, UK;
3Imperial College NHS Trust, UK
Type B dissection is caused by the formation of a tear in the inner layer of the aortic wall. The thrust of diverted blood causes splitting of the wall layers and leads to the formation of a “false lumen” (FL). Partial FL thrombosis was identified as a significant predictor for late complications, due to increased FL pressure and hence an elevated risk for aortic dilatation and rupture. On the other hand, improved outcomes are associated with complete FL thrombosis, which can be achieved through endovascular repair (TEVAR).
This study presents the application of a novel computational model to predict FL thrombosis in medically treated and TEVAR patients under physiological conditions. Thrombus formation and growth are predicted through the evaluation of hemodynamic parameters and flow patterns. The model has been applied to several patient-specific geometries reconstructed from CT images and representing (i) medically treated patients with no thrombus; (ii) medically treated patients with partial thrombosis; (iii) TEVAR patients with partial thrombosis; (iv) TEVAR patients with complete thrombosis. All patients were kept under surveillance, and predictions of thrombus growth were compared with follow-up CT scans. Good agreement between predicted thrombosis and in vivo data was found in all cases. The model was able to predict how variations in morphology and flow led to different thrombus growth patterns, demonstrating its applicability to patient-specific prediction of FL thrombosis. The long term objective of this work is to identify key risk factors for maintenance of FL patency and predictors of FL thrombosis, in order to optimize treatment strategies.