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Using Data to Predict Which Aneurysms May Burst

In This Video

  • Aman B. Patel, MD, is the director of Cerebrovascular and Endovascular Neurosurgery and co-director of the Neuroendovascular Program
  • His research focuses on trying to identify new factors that lead to aneurysm rupture or changes in its size
  • Here, he discusses using computational flow dynamics to identify high pressure points on an aneurysm that lead to a higher rupture risk

Aman B. Patel, MD, is the director of Cerebrovascular and Endovascular Neurosurgery and co-director of the Neuroendovascular Program. His research focuses on trying to identify new factors that lead to aneurysm rupture or changes in its size. In this video, he discusses using computational flow dynamics to identify high pressure points on an aneurysm that lead to a higher rupture risk.

Transcript

My research is essentially focused on trying to identify the factors which lead to rupture or changes in size of the aneurysm. We have two different methods of investigation. One is we're using computational flow dynamics which is a computer algorithm analyzing the flow in the blood vessels, evaluating where there are pressure points and trying to identify which type of pressure points will lead to a higher risk of rupture.

And we correlate that with an animal model of aneurysms. So in the laboratory we develop aneurysms in mice. Some of these mice will rupture and some won't and we're looking at many different inflammatory factors and other biological markers which would predispose the aneurysm to grow or rupture.

We've had several publications and national presentations, especially on the computational flow dynamics in which we've identified pressure points where we've compared unruptured aneurysms.

We do the computational flow dynamics using computer models and identify high-pressure points in the aneurysm based on imaging studies that are done prior to surgery and then we correlate those high-pressure areas to what we see when we're operating on these patients. And what we found is that high-pressure areas that are identified on the computer models are areas that are thinner on the aneurysm when we actually take pictures of the aneurysm where we see little blobs in thinner areas. And what we found is that in ruptured aneurysms, those high-pressure areas tend to be the sites where the aneurysm actually burst from.

So what we're hoping to do is use this data to identify which aneurysms require treatment. After we identify the factors which would lead to aneurysm growth or rupture when we see patients with unruptured aneurysms will be able to characterize which aneurysms are more dangerous and require treatment prior to rupture and which aneurysms can be monitored for future changes rather than jumping in and operating on every aneurysm that we see on the cat scan.

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