Dr. Robert Hamilton, co-founder and Chief Scientific Officer at NovaSignal, on VatorNews podcast

Steven Loeb · May 13, 2022 · Short URL: https://vator.tv/n/5439

NovaSignal uses AI and robotics to identify blood clots and other neurological abnormalities

Steven Loeb speaks with Dr. Robert Hamilton, co-founder and Chief Scientific Officer at NovaSignal, a medical device startup that leverages AI and robotics to measure cerebral blood flow and identify blood clots and other neurological abnormalities.

Our overall goal is to understand how technology is radically changing healthcare: the way we screentreat and measure progress and outcomes. How we’re empowering the consumer. Whether we’re creating productivity that drives economic costs down? And how tech advancements change the role of the doctor. 

Highlights from the interview:

  • The founding of Novus Sigma came from two fundamental mistakes: Hamilton switched two cables which led to two different signals coming into the algorithm that he had been working on; at the same time, a mistake in the computer code mislabeled that information, so it took a non-invasive signal and put it into a big program that they had been working on for years. That led to an "aha" moment that the use of ultrasound, and looking at small variations in ultrasound, can actually tell you much more about what's going on in blood flow in the brain than previously thought.
  • There's EEG that looks at electrical activity in the brain on the surface of the brain but we don't have access to real-time, hemodynamic information about blood flow. That's critical because the brain is very sensitive organ to how much blood flow it's getting. What NovaSignal is trying to do is democratize access and provide them this information for the first time in a very simple, easy to use way.
  • NovaSignal’s technology is based on transcranial Doppler, which looks at blood flow velocity and large arteries of the brain. It's a blind ultrasound, requiring somebody to hold a probe to the side of your head and look into your brain to see if they can find the vessels. This takes an ultra-specialized technician who need additional credentials to be a neurovascular technologist, meaning only around 8% of hospitals in the US have access to this expertise.
  • Ultrasound reflects bone most of it, so you have to use a very specific type of ultrasound for the brain, and put it on the temple, since it is thin enough to allows that ultrasound to go through. NovaSignal uses a very low frequency ultrasound to bounce off the red blood cells as they're moving through blood vessels, so it can tell how fast those blood cells are moving, giving information about how much blood there is and the condition of that patient. It's very different from a tpyical ultrasound, it's actually probably closer to looking at an electrocardiogram.
  • NovaSignal focuses on stroke, but it has done a lot of work in severe traumatic brain injury, as well as Alzheimer's disease. Most people are familiar with Alzheimer's as a plaque or an amyloid deposits in the brain but there are also blood flow changes in patients. Oftentimes, once Alzheimer's symptoms occur, the patient has probably had the disease for five to 10 years. There are exams that you get at certain ages as you get older, but we don't look at the brain today, so the idea would be to do a quick, non-invasive test to look at how your blood vessels are doing and whether or not you're getting increased resistance, similar to a yearly mammogram. 
  • The company has demonstrated that anyone can use its technology, so the next steps are miniaturization and expansion. NovaSignal works with the DOD and they have supported the development of more miniaturized devices as well to not only get outside of the hospital and into the home, but really thinking about other areas like the ambulance or the battlefield.
  • NovaSignal is able to train a robot in understanding what blood flow should look like and how to find it. As you get more and more patients into the database, you can really address some of the inequities within healthcare by customizing real personalized medicine for this, developing models based on age, gender, and race. Once the robot has collected the information, the company uses machine learning to interpret it for the healthcare professional, to make their jobs more streamlined, more accurate, and just overall easier, allowing for quicker, more accurate diagnosis.

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