Neurosurgeons at the Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), in collaboration with the Department of Applied Mechanics at IIT Madras, Chennai, have now developed a patient-specific mathematical model that can predict the rupture of an aneurysm by studying its features as well the blood flow patterns.
Cerebral aneurysms (an aneurysm is a balloon-like dilation that can appear due to a weakening in the wall of a blood vessel) appear in 5% to 8% of the population. For a certain proportion of patients, these aneurysms can rupture when the vessel wall elasticity reaches a certain threshold. The abnormal intra-cranial bleeding that results can be fatal in most cases.
Even though recent advancements in medical imaging techniques have enabled the identification of unruptured intracranial aneurysms, for neuro surgeons, the challenge has been in determining which of these aneurysms can burst. For this, it is vital to understand the initiation, progression, and rupture mechanisms of aneurysms.
The study, funded by the Science and Engineering Research Board of the Department of Science and Technology, appears as a featured article in the latest issue of the prestigious journal, Physics of Fluids.
“Once we have identified a patient with an aneurysm, we do not have much time to do extensive clinical investigations or follow up the case to the point of rupture because that would be endangering the patient. This collaboration with the engineers of IIT Madras, led by Prof Prasad Patnaik, was thus a simulation study and a no-risk experiment to understand the haemodynamic features of an aneurysm that can lead to its rupture,” said B. Jayanand Sudhir, SCTIMST.
Angiogram images were processed using the computational software provided by IIT Madras to develop geometric models of aneurysms. These were subjected to a series of simulation studies on how blood flows inside the aneurysms.
The inputs were very patient-specific. Apart from angiogram images, blood pressure data of patients and blood flow parameters extracted using ultrasound doppler techniques were also put in.
“We studied the turbulence of blood inside the aneurysm, the pressure characteristics, the pressure developing against the wall of the vessel and how these features determine the aneurysm’s potential to rupture. In doing this, we shifted the focus from the risk factors common to patients (smoking, blood pressure etc.) to the specifics of aneurysm that can lead to its rupture,” Dr. Sudhir said.
The mathematical model of the haemodynamic profile of aneurysms has been built on the huge volume of data from SCTIMST’s own cases of ruptured and unruptured aneurysms.
“Since we cannot study one aneurysm to various points of growth till its rupture, we picked up one particular type of aneurysm and developed three different patient models wherein the aneurysm’s size and shape progressively increases. We found that when the size of the aneurysm increases, the blood flow pattern changes and these haemodynamic characteristics are known to lead to ruptures. We are thus on the right track to make accurate predictions on an aneurysm’s potential to burst,” Dr. Sudhir said. Investigations would have to be done with a larger data volume to see if this modelling was valid for a larger population.
“The benefit of this study is that it helps neurosurgeons decide if and when they should act on an unruptured aneurysm that may be identified by a screening angiogram using MR/CT techniques. Arterial models of patients can be made and the haemodynamics pattern mapped to determine if a rupture is imminent,“ Mahesh S. Nagargoje, SCTIMST, said.
