Mathematical model examines factors influencing risk of cerebral aneurysm rupture

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Aneurysm expanding and rupturing (Credit: Sajan Abdul Salam, Subash M Nair, B Jayanand Sudhir)

Researchers from India have developed a patient-specific mathematical model to examine and elucidate the parameters—including shape and size—that influence aneurysm rupture risks prior to surgical intervention.

Predicting the rupture of cerebral aneurysms is crucial for medical prevention and treatment, as the vessel rupture and resultant blood leakage within the brain can lead to severe stroke, or death.

With this in mind, a team of researchers from the Sree Chitra Tirunal Institute for Medical Sciences and Technology in Trivandrum, India, and the Indian Institute of Technology Madras in Chennai, India, developed a patient-specific mathematical model to examine what aneurysm parameters influence rupture risk prior to surgery.

Their findings have been published in Physics of Fluids under the title ‘Influence of morphological parameters on hemodynamics in internal carotid artery bifurcation aneurysms’.

“Since clinicians encounter these aneurysms at various growth stages, it motivated us to analyse internal carotid artery aneurysms in a systematic manner,” said B Jayanand Sudhir (Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, India). “The current study is a sincere and systematic attempt to address the dynamics of blood flow at various stages to understand the initiation, progression, and rupture risk.”

The team examined the aspect ratio and size ratio of aneurysms, which describe the shape and size characteristics of the ‘bulge’ in a holistic manner. As these parameters increase and the aneurysm expands, the stress applied against the aneurysm walls and the time blood spends within the aneurysm increase. This leads the probability of rupture to rise.

Patient-specific computed tomography (CT) scans are fed into the model, which reconstructs the geometry and blood flow of the aneurysm. It then uses mathematical equations to describe the fluid flow, generating information about the blood vessel walls and blood flow patterns.

“This was feasible due to the access we had to the national supercomputing cluster for performing the computational fluid dynamics-based simulations,” said B S V Patnaik (Indian Institute of Technology Madras, Chennai, India).

“The novelty of this work lies in close collaboration and amalgamation of expertise from clinical and engineering backgrounds,” added Sudhir. “The aneurysm models were of different shapes, which helped us build and understand the complexity of flow structures in multilobed cerebral aneurysms.”

The research team found that multilobed aneurysms, which include more than one balloon-like pocket of expanding blood, contained more complex blood flow structures than their single-lobed counterparts.

The authors hope to transform these rupture risk predictions into a user-friendly software to help clinicians and neurosurgeons prioritise and manage high-risk patients. In addition, they plan to use the model to assess the effectiveness of different treatment options for aneurysms moving forward.


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