- Stroke is a time sensitive disease.
Time is critical because with every passing minute,
there are millions of neurons that are dying.
And there are also time sensitive therapies,
that today are mostly focused on reperfusion,
opening up the blood vessel, restoring blood flow.
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What bleeding looks like, hemorrhage looks like,
on an MRI is very different
than what ischemic stroke looks like.
Give us information about other features,
which can be important, not just location,
but also size and volume.
It's a magnetic resonance image that you're developing.
It's all powered by a very high field magnet,
and that magnet is what requires the secure bunker location.
What you love to do is feel you're using MRI
to take pictures over and over again.
Or take the MRI and actually apply it
in any setting for a patient's life.
It's a paradigm shift.
You're taking an MRI, to a sick patient,
versus taking a sick patient to the MRI.
So the fundamental gap there was the development
of something called low field, right use high field.
But why is there a way that you can generate
these images using a much lower field?
We started working with a bunch of different folks
and seeing if we can get low field imaging to the bedside.
We basically started working together
on developing this tool.
Over the course of the last year,
we have been imaging just dozens and dozens of patients
that present in our emergency department,
or our neuroscience intensive care unit.
And now you're able to do that.
You can start to think about, well, you know,
what's the limit to that, why can't this MRI machine go
into the back of an ambulance,
why can't it go into an outpatient clinic,
why can't you have 10 clinical rooms
that are all outfitted with MRIs?
This is one of the sort of look under the microscope,
for the first time in moments.
No one has ever taken pictures of a brain hemorrhage
at a low field before.
We're already starting to work on ways
in which we can reconstruct,
use machine learning algorithms to maybe tell us about,
not just what we see in the pictures,
based on visual inspection,
but also to glean information that we may not naturally see.
If you just look that all the people
that theoretically could have a portable MRI,
and all the neural images that could resolve,
your sort of democratizing MRI technology.
And as you do that, and you have this huge datasets,
the amount that you could probably learn,
using all the advances in data science,
I mean, that is just incredible.