The virtual rainbow and real red world of blood flow in cerebral aneurysms: A Neurosurgeon’s perspective

Cerebral aneurysms are potentially lethal lesions and have the propensity to rupture leading to subarachnoid hemorrhage, which can cause instantaneous death. They are managed by either open surgical procedures which include surgical clipping and cerebrovascular bypass procedures or using endovascular techniques such as coiling or flow diverter placement. Generally larger aneurysms are known to rupture and size is a commonly used criterion. However, smaller aneurysms are also known to rupture. Decisions are often intuitive and based on reasonable logic. Patients demand to know if and when an unruptured aneurysm will rupture. Clinicians rely on pooled statistical data, comorbid illnesses, smoking history and ethnicity to predict aneurysm rupture risk. Hemodynamic and structural characteristics of an aneurysm are the key factors that govern aneurysm rupture. However, there is currently no method of evaluating and understanding the in vivo hemodynamic stresses of aneurysms. Computational Fluid Dynamics and Fluid-Structure Interaction studies allow for patient-specific simulations to generate hemodynamic flow parameters and stresses on aneurysms. Despite the significant advancements in imaging as well as computational power, the results obtained from such studies have not been used by Neurosurgeons for the bedside clinical decision-making in patient management. This reluctance is attributed to several reasons including the lack of understanding of engineering methods and concepts, the difficulty in interpretation of results and reliability It is essential to generate data from a large pool of aneurysms to develop a reliable predictive model. As a neurosurgeon who surgically clips and bypasses aneurysms, in my talk, I will attempt to strike a balance between the VIBGYOR of CFD and the RED of blood. 

Funding acknowledgement: This work was supported by grants from Science and Engineering Research Board (SERB), Government of India, under the Scientific and Useful Profound Research Advancement (SUPRA) Scheme (Grant No. SPR/2020/000298) and National 2 Supercomputing Mission (NSM), Government of India (Grant No. DST/NSM/R&D HPC Applications/2021/03.39).