Dr. Farhad R. Nezami currently serves as the Lead Investigator at the Division of Cardiac Surgery at Brigham and Women’s Hospital, holds the position of Assistant Professor at Harvard Medical School, and is an affiliate Faculty member at the Institute for Medical Engineering and Science at MIT. With a PhD in Mechanical Engineering from ETH Zurich, Dr. Nezami’s diverse research portfolio spans human pathophysiology, translating preclinical experiments to clinical practices, optimizing medical device design, and pioneering engineering platforms that seamlessly bridge the gap from laboratory bench and computational toolkit to the patient’s bedside. His work involves developing predictive and prognostic tools by integrating clinical data, computational tools, and machine-learning algorithms.

I am from Iran. I have got my Bsc and MSc in Aerospace Engineering from Tehran Polytechnic and Sharif University of Technology, respectively. I have got my PhD from ETH Zurich and have been affiliated with the MIT Institute for Medical Engineering and Science (IMES) from 2014. I direct a lab in the Division of Cardiac Surgery at Mass General Brigham and hold the position of Assistant Professor at Harvard Medical School.

What led you to become involved with brain aneurysm research?

I have amassed a solid background in computational modeling and AI and their translation in medicine and medical device development. With the devastating rate of morbidity and mortality for brain aneurysm, I was always looking for leveraging my background to contribute to the research in this critical dilemma.

In the simplest terms, what is the purpose of your project?

Over the past decade, flow diversion (FD) technology has greatly improved the treatment of brain aneurysms. However, even with advancements in platelet testing, device technology, and better deployment techniques, some aneurysms, especially larger and more complex ones, are not fully treated. To improve patient outcomes, it is crucial to understand how blood flow changes in and around the aneurysm after FD treatment. Our project aims to predict treatment success and clotting risk by developing computer and machine learning models. These models will use detailed 3D images of blood vessels, simulations of blood flow, and clinical data from patients in the U.S. 

In the simplest terms, what do you hope will change through your research findings?

We hope to provide personalized care and guide treatment decisions by weighing the benefits and risks of interventional devices for each patient. We aim to leverage metrics of blood flow for therapy planning, quickly calculated by machine learning suites, in combination with anatomical measures.

Why is the funding you are receiving through the Brain Aneurysm Foundation so important?

I lead an early-career research lab filled with enthusiastic and skilled team members. However, to advance our research on brain aneurysms, we urgently need financial support. Securing BAF funding is crucial for supporting my team and establishing a long-term investment in our aneurysm research efforts. This funding will provide the essential resources we need to make significant strides in this critical area of study.