In silico modelling of changes in spinal cord blood flow after endovascular aortic aneurysm repair

To develop an in-silico model of the aorta and its spinal cord-supplying branches, using it to characterise haemodynamic changes following aortic aneurysm (AA) repair. The work is motivated by the risk of spinal cord ischaemia (SCI) and paraplegia, serious complications that can arise from disruption of spinal cord perfusion during AA surgery. An objective, patient-specific tool capable of predicting changes in spinal cord blood flow pre-intervention would address a critical unmet clinical need.

SimVascular was used to retrospectively model a 76-year-old female patient's aorta pre- and post-uncomplicated endovascular thoraco-abdominal AA repair. The full extent of the aorta and its branches, including spinal cord-supplying vessels, was segmented. Pulsatile flow simulations were conducted under the assumption of rigid walls, with patient-specific inlet and three-element Windkessel models for the outlet boundary conditions on the SimVascular Gateway Cluster. Haemodynamic changes following (staged) stent graft implantation were evaluated, alongside key surface-based metrics: time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT) and endothelial cell activation potential (ECAP) were assessed primarily focussing on spinal cord-supplying vessels.

Postoperatively, segmental artery flow to the spinal cord decreased by 51.86% following exclusion of lumbar and posterior intercostal arteries by the stent. Spinal cord-supplying arteries showed increased TAWSS (+5.2%) and reduced RRT and ECAP, with minimal change in OSI. Modest flow increases were observed in non-spinal vascular beds, including the legs (+6.09%), reno-visceral vessels (+5.89%), and supra-aortic branches (+5.97%). Across vascular territories, visceral arteries had the highest TAWSS and lowest RRT/ECAP, while leg arteries had the lowest TAWSS and highest RRT/ECAP; supra-aortic vessels exhibited the highest OSI. Simulating a hypothetical first-stage thoracic stent deployment demonstrated an 18.2% reduction in spinal cord-directed flow, compared with the 51.9% reduction after complete repair, illustrating the pipeline's capacity to compare surgical strategies.

This study lays a foundation for computational prediction of SCI risk. It leverages in-silico modelling, using open-source software and routine medical imaging, to assess spinal cord blood flow alterations after aortic surgery. Scaling to more patients and enriching physiological detail of models may forge a path towards a clinical decision-making tool.