ARVO 2024: Understanding the reading problem for patients with central vision loss

Susana Chung, OD, PhD, spoke with us to discuss her presentation titled, "How similar is reading with central vision loss to reading in normal peripheral vision?" at this year's ARVO meeting held in Seattle, Washington, from May 5 to May 9.

Video Transcript

Editor's note - This transcript has been edited for clarity.

Hattie Hayes:

Hi, my name is Hattie Hayes, and I'm the editor of Ophthalmology Times Europe. This year's ARVO conference is in Seattle, and we are speaking with attendees about what they're presenting at the meeting. With me today is Susanna Chung. She is going to be talking about her presentation from Sunday, "How similar is reading with central vision loss to reading in normal peripheral vision." Thank you so much for being here with me today. I'm really excited to have you.

Susana Chung, OD, PhD:

It's nice to be here. Thank you Hattie.

Hattie Hayes:

Tell me a little bit about this presentation at ARVO.

Susana Chung, OD, PhD:

Okay, sure. So, the talk that I just presented at ARVO today was about measuring reading performance in people who have central vision loss, and comparing this with what we call "the normal periphery." So the reason why we did this study was the following. In my lab, and also for the last, probably, 20 years, I have been very interested in understanding the reading problem for people who have central vision loss. And the leading cause for central vision loss is macular diseases, including age-related macular degeneration, AMD, which is the number one cause of vision loss in the elderly in Western countries. But it could also include other diseases, like Stargardt, [inaudible] or something like that, or even solar maculopathy. So when people have a macular problem, what they will experience is that if they look directly at something – like me, if I look directly at your face, your face will appear blurry. So it's not like the textbook will say, that it's a black hole. It's really not the experience of patients. They do not see a black spot there, they will just say "Things disappear. Things are not clear." If they look at your face, it's just they couldn't see your eyes. If they read, they...wouldn't see the letters, but they will kind of know there are letters, because they are phenomenons such as filling in [by] the brain. So for example, for patients who come to the low vision clinic, the number one complaint is reading. So almost everybody will say that, "Oh, I want to be able to read again, I want to see better, I want to be able to read better," especially for the older adults, because they retired, they may not have a lot of things to do. So, reading maybe their hobby. So a lot of what I have done in the past, [was] trying to understand what is so why is this so difficult for them to read? Is there something we can do to help them see better? Is there something we could enhance their reading? So not just myself, other people also were interested in the topic. But access to patients is difficult. But first because these people have wishing us they may not be able to come to the lab, they may be older, they will get tired easily, and you may not have as much time to kind of try different things to see how they respond to your intervention. So a lot of people, now myself included, I'm not just saying that other people did this, so have maybe used the younger people like students with normal vision as kind of like a testbed if you wanted, if you don't mind me using know what to try to say, Okay, how do they see in their peripheral vision, but with the assumption that peripheral vision is just peripheral vision. And maybe if we understand if we show some properties, how people with normal vision, see or read in the peripheral vision, then maybe we can apply this to people who have the central vision loss, who really have to rely on their peripheral vision. But the problem is that all along, nobody challenged the assumption, whether this is well. So this whole thing will only work on the very important assumption that people who have normal vision, basically the normal peripheral is read just like how people read with central vision loss, like the patient. So that was why we did this study, try to say okay, is our assumption valid? The short answer to the the whole thing is that no, it's not the same. So basically, if we want to understand reading, and in people who have central vision loss, using the normal adults, using that peripheral vision, it's really not the same. The properties are not the same as people of central vision loss, especially if we use the young adults.

Hattie Hayes:

And it sounds like you know, this is really challenging a lot of long-held assumptions about vision and how central vision loss works. So, you know, how do you think this might change how we do research in this area in the future?

Susana Chung, OD, PhD:

I think moving forward, if people accept this, then that will pretty much say that, the normal peripheral is not a good model for understanding people who have had central vision not so in a way it's also like for example, if people do animal model, whether the animal model tells us anything about the patients, right? I'm not saying, because I don't do animal research myself, but that's basically the same thing. It's a model that we use as a researcher, a good one for us to understand the population that we really want to study. So I think the results really [inaudible] of saying that that is not the case. And so the simple answer will be, if we really want to understand vision function or how we want to help people who have central vision loss, we will have to really use those [patients] as the participant and test it on them, instead of testing it on so-called, a model.

Hattie Hayes:

What do you think will be the biggest change in the eye care space in the next decade?

Susana Chung, OD, PhD:

I'm pretty sure most people will say will be AI, like artificial intelligence, right? So but I think there are many ways that AI can be applied to eye care, and also like patient care. First, like with diagnosis, so a lot of people have been doing that. So can we just basically with whatever data like, whether they they can be automatically diagnosed, or maybe treatment plan, like not just diagnosis, but maybe also giving you kind of like a suggestion how you should treat this patient, and things like that. So for example, one of the things that we [inaudible] will be presented in a couple of days at ARVO is actually using AI, or machine learning, basically, to kind of see whether we could predict what a patient is experiencing in their life just based on what the patients say. So we're just starting also trying to also apply AI to what we do. But I will have to say that maybe I'm just a lot more skeptical. AI to me is cold. A doctor should really be working with a patient, or more on a one-on-one basis, and I think a lot of patients, actually what they need, is not necessarily a diagnosis or just a treatment, it's really like they care given by a human. So I think that probably cannot be replaced by just a computer or like a machine; that is cold. So I will still highly suggest that we should not, kind of just, forego totally that part. But it is useful, for example, in rural areas, right, when they may not have as many technologies. So if a doctor will send some information to like a center and they could diagnose things, that will be very, very helpful.
It sounds like there's a lot of exciting things that you're bringing to ARVO, what have you most look forward to at this year's meeting?

Hattie Hayes:

It sounds like there's a lot of exciting things that you're bringing to ARVO, what have you most look forward to at this year's meeting?

Susana Chung, OD, PhD:

I told you that 2 things. One is that like, I'm very, very excited. I'm really looking forward to seeing my postdoc mentor because he was supposed to visit me like actually, March 2020, but then we all know what happened. Right? So COVID. And then there were a couple more opportunities. He's in Minnesota, and I'm in California. So, but then there were a few other things that happened, so every time he was here, and his wife was supposed to visit me something happened. So finally, hopefully, fingers crossed that nothing will happen, and then I will say that because it has been maybe 4 or 5 years. So that's number 1, and then the second thing is that it's actually almost, almost, I shouldn't brag about it. But so I'm actually running for the trustee of the visual psychophysics session, at ARVO. So we will know the results on Monday, but I'm kind of excited to become a trustee of ARVO, because I really feel like I would like to contribute to the organization and do whatever I could do for the visual psychophysics session.

Hattie Hayes:

Well sounds like this ARVO is kicking off a new and exciting time in your life, which I'm very happy to hear about. I'm glad that you're going to have a happy reunion and even more to look forward to for next year's meeting. I appreciate you sharing your expertise with me and with all of our viewers.