- Hi, I'm Sanjiv.
We are in the Laser Lab in Willis Annexe.
This is Olivia.
Do you wanna give a quick introduction of yourself
and what you do?
- I'm Olivia.
I'm doing research in Arteriovenous Fistula failure.
So I'm working with surgeons in the Prince of Wales hospital
which we try to see how we can help patient's life
by predicting when this Arteriovenous Fistula the AVF
will fail, yeah.
- Okay.
So that's why do you look into failure is because of that
trying to figure out when it fails or?
- Yes, trying to see when and what factors that might affect
Arteriovenous Fistula, AVF failure.
- Yeah.
- So that's basically the goal of my research.
- Cool. - Yeah.
- So how are you trying to see when and why,
Arteriovenous Fistula fails?
What's your procedure?
- So, because I work closely with the surgeons there,
so I will be able to have patients geometry.
So, basically what I do is, I do ultrasound scan on patient.
And with the ultrasound images, I am able to get the STL,
the 3D geometry, that I'm able to use it for CFD,
computational fluid dynamic analysis,
on which where I look at different parameters
that might cause a big failure in the hemodynamic sense.
- So STL was like a virtual kind of model of the fistula.
- Yeah.
So it looks like a 3D model of fistula.
- Okay, how do you, what does a scan look?
What does ultrasound scan look like?
How does an ultrasound scan turn into a virtual model?
What's the process?
- Yeah, so we start by getting 2D images
from the ultrasound machine.
So, with the 2D images, that looks something like that,
I segment it based on the, Wayne and Ashy.
- Okay, so segmenting means like picking certain points
- Yeah, picking certain points on the ultrasound images
and with that I...
So the way I pick different points is by looking
at the gray scale of the image and with that
I convert to a 3D geometry.
So, this is one of the geometry that I have,
one of the AVF example.
Yeah. - Okay, cool.
And then you're on CFD on this, is it?
- Yeah.
So then I do CFD analysis on that.
CFD as an analysis is essentially trying to see
how the fluid dynamic of, in the vessel will affect
or basically looking at different reasons, different flow,
different flow patterns of the flow in the vessel.
- Okay, okay.
So all in this, so now you've taken the real life
into the virtual.
- Yeah.
- What does it look like though?
What does it look?
How do you visualize it?
- Yeah.
So this is one of the examples of the geometry.
So the CFD streamlined velocity stream that I have.
So if you can look at this image,
there's some inlets, two inlets
and that's the boundary conditions.
And you can see that flow is flowing up from the vein.
So essentially CFD is that we putting different inlets,
different boundary conditions and the boundary conditions
is the same as the patient's.
So basically, the velocity of the blood
is the same as the patient
when we took the scan. - Yeah.
- So it's trying to make it more patient specific,
because it's quite important for AVF
to be patient specific, the sense.
- Okay.
So this looks like a chain of blood.
So is that all you look at the velocities in the blood,
or is there other aspects?
So this is the velocity.
We also look
at the washer stress. - Okay.
- So this is one of the example
of how we look at different washer stress.
So, we look at OSI, time average, washer stress,
trans washer stress and image.
So trying to see how washer stress will affect AVF,
or you know, causing different diseases
in the area. - Okay.
- Yeah.
- And you seem to be checking, there's a graph as well,
what does a graph show?
- So, the graph gives us information of what is the,
so for example, this trans washer stress,
we have information of how the trans washer stress
varies across the center line from the anastomosis.
So, the anastomosis is a connection of the artery
and the vein. - Okay.
So, essentially along the vessel, is a?
- Yeah, along the vessel, yes.
- Okay, cool.
What is all this equipment?
What does it do what you use it for?
- Yes.
So this is the system that we bring up to the hospital
every week, to get patients' scan.
And this is the ultrasound machine.
That's the camera.
And the camera captures the rigid body at the probe
and the probe is the one that we use for ultrasound scans.
And that's all connected to a computer.
So, yeah. - Cool.
So how do you get, so this is actually the system
that's used to get those scans
that you showed us previously. - Yes.
Yeah, that's right. - Okay.
So how do you get it?
How do you get the whole arm or a vessel of a patient?
- Yeah, so essentially,
yeah, maybe I can try on you.
So what we do is, we do ultrasound scan
on the forearm of the patient. - Yeah.
- Which where, the AVF is at.
And with that ultrasound scan, we will have 2D images.
Slices of 2D images.
And, so that's how we get the geometry right?
And then, to get the velocity,
because remember we have to have a patient specific
and it needs to sync with what the blood flow is
at the patient at the point of time.
So, we do Doppler.
We get captured
the Doppler off the patient. - Okay.
- And that's basically the velocity of the blood flow
of the patient at that point. - Okay.
- So this is one of the example that we have, yeah.
- That's the purple stuff is it?
That show the velocity.
- Yeah this purple stuff is the velocity
of the flow of the blood.
- Okay, with the heartbeat
of something. - Yes.
So if you look at the green one,
the heartbeat of the patient, in which we capture with ECG.
So that's important, because then we want to sync it
with the Doppler information that we have
and putting it at different boundaries
of the computational model.
- Okay, because there are so many inlets,
you want to sync everything. - That's right, yeah.
So we have to sync everything together.
- Okay. - Yeah.
You showed me this.
You said something
about rigid body model.
What is it?
What does that do?
- Yeah, so this rigid body, so if you look at the,
the camera actually tracks the rigid body.
That's where, how we locate the vessel of the patient.
So that's basically the idea of connecting,
getting the camera to locate the rigid body.
And that's how we look at the patient
because we scan the AVF
and that's, you know, we can look at the,
can know the location.
- So that means when you're moving,
this camera knows where this probe is, is it?
- Yeah.
So the camera will be able to track the probe.
- Okay, that's pretty cool.
- That's right. - Yeah.
So all this, is you take it to the hospital or?
- Yeah, they are all very portable.
We can all put it in a suitcase
and just bring it up, do a scan and bring it back down.
So it's not, it's pretty, yeah, convenient.
- Yeah, that's pretty cool.
That's pretty cool how it's easy
to use all this in the hospital.
- Yeah.
- What are the challenging aspects
of all these components in your research?
- So I guess it's trying to,
so we start by taking a clinical problem from patients.
So getting the geometry and stuff from the hospital
and then converting it to an engineering problem
where we do computational fluid dynamics,
to different simulations, different analysis,
to see how engineering knowledge
can help with a clinical problem.
So I guess getting the accuracy of a clinical problem
to the engineering and then bringing back,
bringing it back to clinical perspective
requires quite a bit of accuracy and position.
So I guess that's one of the challenges in trying
to make it as close to the patient condition as possible.
- Okay. - Yeah.
- So trying to take a problem from the hospital
and then putting it back in research.
- Yeah, that's right.
- So all this research, once you're done
or once all this research is done,
where do you see your research going forward from there?
- So I think, because we are getting heaps of data
and all this data will be really useful
with the artificial intelligence
and machine learning coming in
and the rise of different computation, computer vision
and computer, you know, work,
it'd be good to see how that could also come into place
and seeing how I can look at correlations
and predictions of AVF with the knowledge
of computational machine learning and stuff like that.
So that'll be quite cool to see how that can help
with a further prediction for my work essentially.