Relationship Between Eye movement and Eye Muscle on Ultrasound

The advancement of bioimaging technologies has significantly progressed in recent years, which can be used to image many parts of the body. However, despite these developments, the human eye remains relatively understudied in dynamic imaging. By utilizing ultrasound imaging, we can learn more about the movement of the eye muscles while the eye is moving, particularly the medial rectus muscle (MRM). This can provide new avenues for diagnostic capabilities. The purpose of this study was to analyze the relationship between eye movement and the MRM echo-intesnity (echo-texture) on ultrasound. We hypothesized that there is a periodic relationship between eye movement and muscle echo-texture. In this study, we utilized eye data from multiple subjects. Our team obtained IRB approval to obtain images, with all participants providing consent before enrolling in the imaging study. The participants were asks to move their gaze from left to right and vice versa, following a target. This gave us series of image stacks, containing an average of 220 frames. Using MATLAB App Designer, we created an application that can load image stacks of ultrasound; shade in, annotate, and trace the MRM; and save the tracings as a MATLAB cell struct file. That file was then subsequently processed in another code, using MATLAB regionprops function, to produce a figure that quantifies the muscle echo-intensity (tracings) over gaze (frames). The results suggested that there is a periodic relationship between MRM echo intensity and eye movement. More data must be collected to acquire a more accurate interpretation.

Hello everyone, I’m Zeinab and my URSP research was analyzing the relationship between eye movement and extrocular muscle movement on ultrasound images. This was in collaboration with the Bioengineering Department at George Mason.

So extrocular muscles are just a fancy word for eye muscles. The eye muscles we focused on for this research was this muscle, the medial rectus muscle. And it’s the muscle that is closest to the nose on both eyes. So this right here is the right eye. Here we have, this would be the nose and this muscle is basically in charge of moving this eye toward the nose.
So it’s in charge of moving the right eye to the left and on the opposite side same thing.
It’s in charge of moving the left eye to the right. And any problems with this muscle could result in double vision or being cross-side. So how would a doctor and eye doctor examine that or examine the eyes in general?

Well there are different methods to take images of the eye, there’s retinal imaging, which is probably the one most people have had taken before. That provides information on the optic nerves and your vision. In serious cases, the doctor might want to look at the bone structure or muscles in the surrounding areas of the eyes. And that’s when they would use X-ray or CT or MRI imaging. These are all very innovative, but the problem is they provide still images. What if we want to somehow image or compile a video of the eye while the eye is moving or look at it in real time?

That’s when we turn the ultrasound imaging. A clinician or a technician will run a small probe on your eyelid or under the eyelid. The patient might keep their eye closed or open depending on the procedure. And that will get you this image right here. Ocular ultrasound imaging is used a lot. It can be used to find foreign bodies such as tumors and blood pooling and to evaluate any trauma in the eye, evaluate the optic nerve, any lens detachments. However, there are no studies on evaluating how the muscle changes.
And we can only see that change when the eye is moving. So that’s the topic we wanted to research.

What is the relationship between eye movement and the medial rectus muscle’s echo intensity? And by echo intensity, I mean the ultrasound image pixel intensity of the muscle,
which can kind of quantify as the general shape of it.

For my research, we conducted ocular ultrasound on multiple participants,
multiple trials. In order to process those movements and segment that muscle intensity,
we used MATLAB app designer to trace the MRM on each ultrasound session, tracing every 5 to 10 frames. And then we used MATLAB to convert those tracing into a figure and quantify the results.

All right, so first we have one example of an ultrasound image stack that we took. This is the right eye. And here’s the pupil area right here. So we asked the participant to move their eye left and right while looking at a target. I know it looks like it’s going up and down,
but that’s just because of the position of the probe. And down here is the medial rectus muscle. And as you can see, you can already see the muscle changing. The echo intensity and the shape is changing while the participant is moving their eye left and right.

And just the screen recording of how I did this,as you can see, I have the image stacks loaded here on the MATLAB app. There are 224 frames in this one. I can move them around and I traced every 5 frames or so. And to demonstrate right here is the medial rectus muscle. And so I traced right around that outline. I normally do this zoomed in, but for demonstration purposes, I zoomed out. And then I would go to the next frame. Again, normally I would do it every 5 to 10 frames, but I’ll just trace this one right here. And then after that, I would save the annotations of all the traced muscles
as a MATLAB cell-struct file.

All right, so after processing that, here is one of the ultrasound sessions. And this is the figure that we were able to generate. The y-axis is the muscle intensity while the x-axis is the frame. And again, we can correspond frame with time or as the muscle, as the eye moves. Excuse me. And so these blue dots are representatives of the tracings that I did
and this red line is the periodic regression that we fitted it with. And to kind of illustrate that right here, you can see the beginning frames, the beginning segments that I did. They’re kind of similar. So the muscle was hardly moving, which means the eye was probably not moving. And so if I press play right here, we can see that is true. Okay, right now for those first few seconds, the eye was not moving. So we can say up to frame 60, 50 or so. The eye wasn’t moving and so the muscle wasn’t moving. The muscle wasn’t changing. You could see the shaded areas that I would do were probably not, not too different from each other.
And so right now, the eye moves to the left. It moves to leftmost and this is probably where the leftmost is. And so the muscle echo intensity, you can see here it’s a lot smaller. It’s almost really thin. That means the echo intensity was going down, which again is shown here. That makes sense. So much so that right here, when the eye just changes direction,
so probably around 80, right here. Around frame 80, the eye starts to change direction. And so the muscle is getting bigger as the eye is moving to the right. And that again makes sense. The eye moves to the right, the muscle echo intensity just gets bigger and bigger. Up until this peak right here, again, the eye changes direction and starts to move to the left. And we have that cycle again, comes back now. And again, notice the muscle echo intensity is very big and then it starts to get small again. So we can conclude that at every peak, that’s represented at the eye changing direction because the muscle changes shape.
And so we can say that there is a relationship between gaze and muscle echo intensity. These results suggest it. They don’t necessarily say it, but they suggest it.

Now, there were some limitations to these methods. First off, it was very time consuming.
Tracing every 10 frames took about 10 minutes. Tracing every be 5 frames took longer, about 15, 20 minutes. Now, that doesn’t seem long, but every participant conducted 6 trials. So compiling all the tracings were just one participant takes anywhere between an hour to an hour and a half. Another limitation was that some of these images of the eyes
were bit unclear, which made me not trace it at all sometimes. So if you can see in this image right here, there’s a giant gap between these two frames. I didn’t take any images here or any tracings here because it was just hard to see on the ultrasound. And so that created this giant decrease in the regression. And that would not create some accurate results. Another thing was that there were some problems with the coding and the apps.
And so we spent a lot of time troubleshooting and debugging. And finally, the results were very promising. However, we would need more participants, more data in order to reach a better conclusion.

And so our next steps would be to gather more data from more participants. And then again, because tracing is time consuming, we would want to look into possibly making the tracing process automatic using machine learning processes. And then we can analyze how the maximum muscle thickness changes as the eye moves as well. And for long term, we can examine the same relationship with the other five extracurricular muscles.

All right, so to conclude, again, we found a periodic relationship between the MRM and gaze. In general, ultrasound is a very useful imaging technology. This type of research is very novel and innovative. Research on the eye and eye movement, though fairly understudied, has a promising future with these types of developments. And special thanks to OSCARS for their URSP funding, our participants of the study, the Department of Bioengineering, especially Dr. Wei and the Biomechanics Lab. Thank you very much for watching.