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Melanie Cole, MS (Host): Welcome to UF Health MedEd Cast
with UF Health Shands Hospital. I'm Melanie Cole. And joining me today is Dr.
Abbas Babajani. He's an Associate Professor in the Department of Neurology in
the Division of Epilepsy at the University of Florida College of Medicine, and
he's the Director of the MEG Laboratory at UF Health Shands Hospital. He's here
to talk to us today about magnetoencephalography or MEG, a window into brain
function and dysfunction.

Melanie Cole, MS: Dr. Babajani, it's such a pleasure to
have you join us today. I'd like you to start by helping us to understand the
basic concepts of MEG technology and its underlying principles.

Dr Abbas Babajani-Feremi: Hello, I'm thrilled to be
here. Thank you so much for the time that you're providing to me and talking
about the magnetoencephalography, MEG. I'm going to say MEG for the rest of
this talk. So yeah, MEG is a noninvasive and neuroimaging technique used to
measure the magnetic field generated by the electrical activity of the brain
neurons. So, it provides a direct measure of the neural activity with a very
high temporal resolution, we are talking about 200 microseconds, and a very
high spatial resolution in order of millimeters. But MEG detects the very tiny
magnetic fields from the brain. When I'm talking to you, a part of my brain
named Broca's area is active and generating magnetic fields. But this magnetic
field is very tiny. Very tiny. It's in the order of like hundred million times
smaller than the magnetic field of the earth. The magnetic field of the earth
is very tiny. So still, this is very, very small brain magnetic field generated
by neurons. So to detect such a small and tiny magnetic field generated by the
neurons in the brain, we use a very specific equipment and sensor named SQUID,
superconducting quantum interference device. This very specific sensor helps us
to detect this tiny magnetic field of the brain. By having this magnetic field
of the brain, we can find the location of the brain doing what type of
activities and then, with a good spatial and temporal resolution that's needed
to study the brain.

Melanie Cole, MS: Isn't that fascinating what we're
talking about here today, Dr. Babajani? So, how does it provide insights into
brain function and dysfunction compared to other neuroimaging techniques? Tell
us a little bit about some of the advantages compared to other neuroimaging
that you might use.

Dr Abbas Babajani-Feremi: So, I think MEG has several
advantages over other neuroimaging techniques. Firstly, it has an exceptional
temporal resolution. As I talk to you, it has a temporal resolution in order of
200 microseconds. So, it is very, very accurate time-wise. And by doing that,
it led us to study the dynamic of the brain function. So, the brain has, you
probably heard about that, different waves, a slow wave, very fast waves. So,
those waves are the basic of the brain function. And using this super high
resolution technique, we can investigate different functions of the brain
comparing to other modalities, for example, functional MRI, which is also
another really good and nice technology, but it does not have a good temporal
resolution. Temporal resolution is in the order of one second compared to 200
microseconds of MEG. So based on that, for example, if MRI cannot be used for
studying the fast dynamic of the brain.

Second advantage of MEG is an exceptional and excellent spatial
resolution. We are talking about a few millimeters. By having such a great
spatial resolution, we can pinpoint any location in the brain to see what's
going on at that part of the brain. Also, I think another important aspect of
the MEG is that this technology is noninvasive. Actually, MEG is maybe the most
noninvasive technology that you can imagine because the sensor of the MEG even
does not touch the head. So comparing to other imaging like PET that you need,
you know, ionization or radiation, MEG does not have any of them. Completely
non-invasive modality that is very safe to use for any kind of disease that's
appropriate for studying MEG.

And also, another importance of the MEG is that this
technology, we can directly access the brain and neuron activity compared to
other modalities, again, like functional MRI, which provides an indirect
measure of the neural activity. The technique like MEG provided direct measure
of the brain activity. So, this is another unique aspect of this technology.

So altogether, I think MEG provides a lot of advantages
compared to other modalities. But I should say that other modalities, like a
functional MRI, they also have some advantages. And usually in our work, we
combine different modalities to benefit from their complementary aspects.

Melanie Cole, MS: Well, thank you for explaining that.
So, what are some of the most promising clinical applications of MEG? What are
you using it for, doctor?

Dr Abbas Babajani-Feremi: Sure. So, MEG has FDA approval
for epilepsy and brain tumor. So. We use MEG for a patient with epilepsy and
brain tumor. And actually, MEG is the only technology which provides a one-stop
shop for patients with epilepsy. So, about 30 to 40% of the patients with
epilepsy are drug-resistant. For those patients, after they fail multiple drug
medications, so they need to do at the end of their treatment an epilepsy
surgery. They need to resect some part of their brain. So MEG, actually, the
technology will help us to exactly find which location of the brain generated
the abnormal brain activity of the epilepsy. So, that's one aspect of MEG.

Another aspect that MEG is doing, it is also providing the
eloquent cortex of the brain, meaning that it will map the language part of the
brain, the speech part of the brain, listening part of the brain or visual part
of the brain. So, I think the idea here is in our patients with epilepsy after
epilepsy surgery, we want to be a cure after resecting their brain, but we
don't want that they cannot talk and walk. So, MEG provides a comprehensive
function of the brain in addition to location of the brain that has epilepsy,
provides this information for the neurosurgeon and neurologist to do the
treatment for patient with epilepsy. So, that's the clinical application, which
has FDA approval for MEG.

But MEG has an endless application in research in many
neurological diseases. For example, in Parkinson's disease, MEG can be used to
find the coherence between the deepest structure like the thalamus and how that
malfunctions in the connection between the thalamus the motor cortex of the
brain, MEG can be used for that. For patients with Alzheimer's disease, we can
use MEG to find some biomarker from the brain that can predict the early stage
of Alzheimer's disease. Or, for example, in patients with traumatic brain
injury, we can use MEG based on the brain network and derive from that to
distinguish mild TBI, mild traumatic brain injury study from the ICU control.
So from the research point of view, MEG has a lot of exciting applications and
have been used in all these applications with a lot of promise to some of these
research applications, getting clinical approval in the future.

Melanie Cole, MS: Well, Dr. Babajani, and this is really
exciting technology, how are you integrating the findings into a patient's
overall diagnostic workup? And for other providers, what are some of the
challenges or limitations that should be considered when interpreting MEG data?

Dr Abbas Babajani-Feremi: So, integrating MEG findings
into a patient's diagnostic workup involves a multidisciplinary approach, MEG
data along with other neuroimaging data like EEG and MRI. In addition to all
clinical data and information, we will incorporate all of them in a careful
analysis of the MEG data that we collected to find and to provide the final
interpretation, result and report for the result of the MEG that we provide for
neurologists who referred MEG to us.

So, a couple of challenges I would like to mention for MEG.
First, one challenge would be MEG, compared to EEG, MEG is kind of more complex
and complicated technology compared to very simple technology like
electroencephalography, EEG. Because of that, you need specific trained
expertise for analysing, for collecting data and interpreting the result.

Another aspect of the imaging that needs to be carefully
considered is that MEG is affected by various factors such as the head movement
and environment noise, the artifact generated by heart or eye movement. So,
these are the factors that essentially have a lot of effect on MEG data. And
the person using MEG needs to be very careful about the cleaning of the data,
about interpretation and result of data, considering all these factor that
affect very tiny, small brain signal, magnetic brain signal generated by neural
activity. Another aspect of imaging that needs to be considered that there
needs to be a collaboration between MEG experts and clinicians when we do the
clinical data toward finalizing the result in the way that the result ultimately
has a clinical relevance at the end of the data collection and analysis.

Melanie Cole, MS: Are there any ethical or practical
considerations involved in using this in clinical practice? How are you
addressing these issues to ensure patients safety, privacy? Speak a little bit
about that.

Dr Abbas Babajani-Feremi: First of all, I should say
that MEG is a non-invasive technology. It is actually one of the most
non-invasive technology that you would consider. So, safety of the patient is
not a concern, like MRI or other modalities. Even MRI is a non-invasive
modality, but MEG is much more safer than any other technology that we would
consider. So from the point of view of safety, MEG is completely safe.

But from the privacy and ethical, I think we consider that, for
any research that we'll be doing, definitely providing informed consent from
the patient and also protecting patient privacy and data security is an
important part of our MEG practice. And also, the patient always will be
provided with adequate information in advance. What is the purpose of the
study? What is the potential risk and discomfort? So that we will provide them
to respecting the patient privacy and ethical things. Altogether, ensuring the
wellbeing and safety of the patient during MEG measure is crucial for us. And
this involves proper training and supervision patient during the procedure and
maintaining a safe and comfortable environment with the MEG facility.

Melanie Cole, MS: This is so interesting and you've made
such great points. That was very good information. Dr. Babajani, as we get
ready to wrap up, highlight some of the potential future directions for MEG
research, clinical applications, including its use in non-invasive brain
computer interfaces.

Dr Abbas Babajani-Feremi: I think the future of the MEG
and the clinical application is very exciting and holds great promise. So, MEG
is advancing in both direction toward the hardware and toward the analysis.
From the hardware point of view, we have a new technology that just recently
got developed, optically pumped magnetometer or OPM-MEG, which is compared to
the Squid EEG. That's a wearable EEG you can have on your head like a helmet
and patient can move around and that provides a lot of flexibility regarding
the movement of the patient, and also provides more signal to noise issue
because the sensor of OPM is closer to to the brain. So, that's from the
hardware point of view. There's a lot of exciting avenue s and enhancement from
the analysis data, as you said, the VCR brain computer interface. That's also
very exciting.

And I mean, actually I am involved in a project in patients
with ALS. So for those patients who their brain is normal, but they cannot talk
because of some neural issue that they have in their motor neuron disease. So
for them a non-invasive technology like MEG and EEG integrating with artificial
intelligence can be used, for example, to decode their speech. For example, the
patient talking about the word. And the idea here is, okay, you think about the
word and without saying that, the MEG combined with an artificial intelligence
and machine learning can predict what's in your mind and to say that for the
communication of the patient with others.

So yeah, altogether it's very exciting, both the ward and all the
hardware and also the analysis integrating with the machine learning and AI.
There's a lot of exciting advancement in the field of MEG. I'm very excited to
see it in the near future.

Melanie Cole, MS: That's so cool, Dr. Babajani. Those
future directions and potential applications are absolutely amazing. And thank
you so much for joining us today and sharing your expertise for other
providers. To learn more and to listen to more podcasts from our experts,
please visit innovation.ufhealth.org or you can visit ufhealth.org/medmatters.
That concludes today's episode of UF Health MedEd Cast with UF Health Shands
Hospital. I'm Melanie Cole. Thanks so much for joining us today.