Computational modeling of blood flow steal phenomena caused by subclavian stenoses.

The study of steal mechanisms caused by vessel obstructions is of the utmost importance to gain understanding about their pathophysiology, as well as to improve diagnosis and management procedures. The goal of this work is to perform a computational study to gain insight into the hemodynamic forces that drive blood flow steal mechanisms caused by subclavian artery stenosis. Such condition triggers a flow disorder known as subclavian steal. When this occurs in patients with internal thoracic artery anastomosed to the coronary vessels, the phenomenon includes a coronary-subclavian steal. True steal can exist in cases of increased arm blood flow, potentially resulting in neurological complications and, in the case of coronary-subclavian steal, graft function failure. In this context, the anatomically detailed arterial network (ADAN) model is employed to simulate subclavian steal and coronary-subclavian steal phenomena. Model results are verified by comparison with published data. It is concluded that this kind of model allows us to effectively address complex hemomdynamic phenomena occurring in clinical practice. More specifically, in the studied conditions it is observed that a regional brain steal occurs, primarily affecting the posterior circulation, not fully compensated by the anterior circulation. In the case of patients with coronary revascularization, it is concluded that there is a large variability in graft hemodynamic environments, which physically explain both the success of the procedure in cases of severe occlusive disease, and the reason for graft dysfunction in mildly stenosed left anterior descending coronary artery, due to alternating graft flow waveform signatures.