Episode 011 | January 18, 2022

Keratoconus is a severe eye disease that affects the cornea, causing it to become weak and develop a conical bulge. Keratoconus, if undiagnosed and entreated, can lead to partial or complete blindness in people affected by it. However, the equipment needed to diagnose keratoconus is expensive and non-portable, which makes early detection of keratoconus inaccessible to large populations in low and middle income countries. This makes it a leading cause for partial or complete blindness amongst such populations. Doctors from Sankara Eye Hospital, Bengaluru and researchers from Microsoft Research India have been working together to develop SmartKC, a low-cost and portable diagnostic system that can enable early detection and mitigation of keratoconus. Join us as we speak to Dr. Kaushik Murali from Sankara Eye Hospital and Dr. Mohit Jain from Microsoft Research India.

Dr. Kaushik Murali, President Medical Administration, Quality & Education, Sankara Eye Foundation India (Sri Kanchi Kamakoti Medical Trust) which is among the largest structured community eye hospital network in India, (www.sankaraeye.com) with an objective of providing world class eye care with a social impact. 

A paediatric ophthalmologist, Dr. Kaushik has completed a General Management Programme and is an alumnus of Insead. He has done a course on Strategic Management of Non Profits at the Harvard Business School. He has been certified in infection control, risk management for health care and digital disruption. He is a member of Scalabl, a global community promoting entrepreneurship.  

Dr. Kaushik is a member of the Scientific Committee of Vision 2020, the Right to Sight India. He is currently involved in collaborative research projects among others with the University of Bonn & Microsoft.

Dr. Kaushik has received many recognitions, key among them being the Bernadotte Foundation for Children's Eyecare Travel Grant, Mother Teresa Social Leadership Scholarship ,International Eye Health Hero, All India Ophthalmological Society best research, International Association for Prevention of Blindness (IAPB) Eye Health Hero, Indian Journal of Ophthalmology Certificate of Merit. 

Beyond the medical world, he is part of the National Management Team of Young Indians – Confederation of Indian Industry (CII). He represented India at G20 Young Entrepreneur Alliance 2018 at Argentina and led the Indian delegation for the Inaugural India- Israel Young Leaders Forum in 2019. More recently, he led the first citizen’s cohort for a workshop on Strategic Leadership at LBSNAA (Lal Bahadur Shastri National Academy of Administration). 

Mohit Jain is a Senior Researcher in the Technology and Empowerment (TEM) group at Microsoft Research India. His research interests lie at the intersection of Human Computer Interaction and Artificial Intelligence. Currently, he focuses on developing end-to-end systems providing low-cost smartphone-based patient diagnostic solutions for critical diseases. Over the past decade, he has worked on technological solutions for the developing regions focusing on health, accessibility, education, sustainability, and agriculture.

He received his Ph.D. in Computer Science & Engineering from the University of Washington, focusing on extending interactivity, accessibility and security of conversational systems. While pursuing his Ph.D., he also worked as a Senior Research Engineer in the Cognitive IoT team at IBM Research India. Prior to that, he graduated with a Masters in Computer Science from the University of Toronto, and a Bachelors in Information and Communication Technology from DA-IICT.

For more information about the SmartKC project, and for project related code, click here.

For more information about the Microsoft Research India click here.

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Transcript 

Dr. Murali Kaushik: Sitting in an eye hospital, often we have ideas, but we have no clue whom to ask. But honestly, now we know that there is a team at MSR that we can reach out to saying that hey, here is a problem, we think this warrants attention. Do you think you guys can solve it? And we found that works really well. So, this kind of a collaboration is, I think, a phenomenal impact that this project has brought together, and we hope that together we will be able to come up with few more solutions that can align with our founders’ dream of eliminating needless blindness from India. 

[Music]

Sridhar Vedantham: Welcome to the Microsoft Research India podcast, where we explore cutting-edge research that’s impacting technology and society. I’m your host, Sridhar Vedantham.

[Music]

Sridhar Vedantham: Keratoconus is a severe eye disease that affects the cornea, causing it to become weak and develop a conical bulge. Keratoconus, if undiagnosed and entreated, can lead to partial or complete blindness in people affected by it. However, the equipment needed to diagnose keratoconus is expensive and non-portable, which makes early detection of keratoconus inaccessible to large populations in low and middle income countries. This makes it a leading cause for partial or complete blindness amongst such populations. Doctors from Sankara Eye Hospital, Bengaluru and researchers from Microsoft Research India have been working together to develop SmartKC, a low-cost and portable diagnostic system that can enable early detection and mitigation of keratoconus. Join us as we speak to Dr. Kaushik Murali from Sankara Eye Hospital and Dr. Mohit Jain from Microsoft Research India.

[Music]

Sridhar Vedantham: So, Dr. Kaushik and Mohit, welcome to the podcast. 

Mohit Jain: Hi, Sridhar. 

Dr. Kaushik Murali: Hi Sridhar, pleasure to be here. 

Sridhar Vedantham: It's our pleasure to host you, Doctor Kaushik, and for me this is going to be a really interesting podcast for a couple of reasons. One is that the topic itself is kind of so far afield from what I normally here at Microsoft Research and the second is I think you're the first guest we are having on the podcast who's actually not part of MSR, so basically a collaborator. So, this is really exciting for me. So let me jump right into this. We're going to be talking about something called keratoconus, so could you educate us a little bit as to what keratoconus actually is and what its impact is? 

Dr. Kaushik Murali: So, imagine that you were a 14-year-old who was essentially near sighted. You wore glasses and you were able to see. But with passing time, your vision became more distorted rather than being blurred, which is what you would have expected if just your minus power kept increasing, especially for distance. And to add to your misery, you started seeing more glare and more halos at nighttime. Words that you started to read had shadows around them or even started to look doubled. This essentially is the world of a person with Keratoconus. Literally it means cone shaped. Keratoconus is a condition of the cornea, which is the transparent front part of the eye, similar to your watch glass, where instead of it normally retaining its dome shape, it is characterized by progressive thinning and weakening of the central part, what we call as a stroma, and this makes the cornea take on a conical shape. In a few, this can actually even progress beyond what I describe, where the central cornea overtime becomes scarred and the person could no longer be corrected, with just optical devices like a glass or a contact lens but may actually end up requiring a corneal transplant.  

Sridhar Vedantham: I see, and what are the causes for this? 

Dr. Kaushik Murali: So there have been very many causes that have been attributed, so it's thought to be multifactorial. So, this again makes it a little tricky in terms of us not being able to prevent the condition, so to speak. But multiple risk factors are known. Ultraviolet exposure, chronic allergies; habitual eye rubber is thought to be more prone for this. Essentially, you end up seeing it more during the pubertal age group, and more in men. 

Sridhar Vedantham: I see. And how widespread is this problem, really? Because frankly, I'm of course as lay a person as you can get, and I hadn't really heard of eye disease called keratoconus until I spoke to Mohit at some point and then of course after reading papers and so on. But what is the extent of the issue and is it really that widespread a problem? 

Dr. Kaushik Murali: So, unlike most other conditions, there is no real population-based survey where we have screened every household to arrive at numbers. But largely, we base our estimation on small surveys that have been done across different parts of the world. Based on this, we estimate that it is approximately affecting about one in 2000 individuals. So, in the US, for example, it is thought to affect almost about 55 people in about 100,000, who had been diagnosed with keratoconus. But in countries like India, it is thought to be more widespread. So there was actually a survey in central India where they found almost 2300 people out of 100,000 people being affected with keratoconus. So, the numbers are quite large. And again, all of this could be underestimated simply because we don't have enough ability to screen. And what makes this number even scarier is this is a disease that typically affects people between the age group of 10 and 25. So, once they're affected and they’re progressively going to have their vision come down, they're going to spend most of their protective years not being able to see clearly. 

Sridhar Vedantham: OK, that is kind of scary. 

Mohit Jain: I would just like to add to that is that there is actually a combination of demographics, genetic and weather condition which makes India a really good host for this disease. So, apparently Indian population tend to have a thinner and steeper cornea to begin with and moreover the hot and humid climate of India actually contribute towards keratoconus because it causes irritation which leads to frequent rubbing of the eye and that can actually start the process of distortion of the cornea. 

Sridhar Vedantham: OK, so that just made the problem sound a little scarier because there are these conditions that cannot be altered, right? I mean climate and stuff like that we can't really change. Uh, OK, doctor, so, this is basically a well-established and recognized disease, right? So, what are the barriers and hurdles actually to effective diagnosis and treatment of this disease? 

Dr. Kaushik Murali: So, in any health intervention the barriers typically are availability, accessibility and affordability. And when you look at a condition like keratoconus, all these barriers actually again come into play. So, the clinical gold standard for diagnosing keratoconus essentially entails us being able to map the curvature of the corneal surface using a technique known as corneal topography. So, here we either use something called as a Placido base, where you project a disc kind of structure onto the cornea and capture an image using tomographers, or you use certain other technology to map out the surface of the cornea, both the anterior and the posterior surface. But all these devices, by and large are non-portable and are expensive. And these are typically available again at secondary or tertiary eye hospitals. India is a land of diversity. We have some of the best health care in cities like Bangalore where we are sitting and doing this recording while you move about 150 to 200 kilometers away, it's a completely different world out there. The cost of each of these tests again, makes this diagnosis very inaccessible to large sections of population, not only in India but in similar middle and low income countries. And to add to this, you have the bogey of the pandemic. So, with COVID-19 in play the last two years with restrictions on travel, it has become very difficult for young children to actually undergo annual eye exams where we could have even proactively tried to pick up some of these conditions. 

Sridhar Vedantham: OK, alright, Mohit, let me bring you in here. I'm curious as to what Microsoft Research is doing as part of this particular research collaboration, right? Because keratoconus sounds very, very far afield from Microsoft Research’s typical computer science focus. 

Mohit Jain: So, I think one of the key pillars of MSR India is societal impact. So, if we can develop a diagnostic tool which can save even a handful of children getting blind, we think it has huge societal impact and Microsoft Research India completely, I think, supports such kind of technological solutions. With respect to the computer science research lab, we have developed a solution which actually uses cutting edge AI, especially in the field of image processing and then also we have developed a full end to end system. So hence there are like enough computer science research problem, really hard ones, that we actually solve as part of this research collaboration. 

Sridhar Vedantham: OK, so that's a good lead into me to ask you to talk a little bit about the solution that's been developed here. 

Mohit Jain: So, I think the solution has actually 3 core components. So the first component is actually a Placido disc like what Dr. Kaushik said that like there has to be something which projects concentric rings over the cornea. So, we actually 3D printed a Placido disc. So, we actually attach that Placido to the back of a smartphone camera and then capture an image of the cornea with the Placido projected over the cornea of a human. And the second component we have is actually a smart phone app which has inbuilt AI in it. So, in real time it actually helps the person who is capturing the image to actually get a perfect image because I think one of the core design principles that we had while working on this was to make sure that anyone can use this app to actually diagnose. We don't want like medical technician to be only be able to use it. So, there is some kind of AI assistance to help capture perfect image of the eye. And the third then we have like an image processing pipeline which takes this captured image as input and converts that into corneal topography heat maps. So, basically it gives a curvature heat map, which tells you like what is the curvature at each point of the cornea, and that is the kind of output that you also get from a medical grade corneal topographer. 

Sridhar Vedantham: So, the way you explain it sounds very simple, but I'm sure there were a bunch of challenges, while you know, both Sankara and MSR was doing the research. Can you give me a sense of what kind of challenges you faced? 

Mohit Jain: Yes, yes, I think the most trickiest part of this project was to actually do it in a portable setting. So right now the corneal topographer, that is like a $10,000 device which is there in Sankara hospital. There is actually a headrest and a chin rest. So, basically your whole face like the patient face is very very stable and hence the image capture process is fairly easy. Apart from that the topographer has a lot of specific hardware. For example, it has a specific hardware to determine how far is the eye from the camera, so which is actually called as a working distance, and getting that parameter right is very crucial. Like even a few millimeters of actually predicting that value wrong can completely change the generated heat map. So, we have to actually design a very innovative solution to figure out this working distance directly just from the captured image and the second part was that, like we actually did a lot of iteration on the Placido disc and also on the AI assistance which was actually running on the smart phone to actually help capture the best image, even without any kind of a support system in place, like without any headrest or chin rest. 

Sridhar Vedantham: Dr. Kaushik was there anything you wanted to add to that in terms of challenges from a medical point of view? 

Dr. Kaushik Murali: So, from the medical point of view, we are people of habit. When I say that, there is certain things that we are comfortable about and certain things that puts us off. So, one of the key challenges we gave to the MSR team was saying that the interface and reports had to be similar to what we were used to seeing. So, I think the challenge also came to the team in terms of ensuring that the heat maps were similar to the heat maps that we were used to seeing using a regular topographer and how we actually were able to match with it. So, the minute we were able to get that kind of familiarity built in, we found our doctors also being able to accept it much better. And once that was done then automatically the learning curve that came in in terms of using the device or interpreting the images came down very very fast. So, we were able to adapt to this much faster. We were even able to get some of our colleagues from other units to read these heat maps that we generated, just to validate it. Because we were also concerned saying that when you are putting it out as a screening device you should end up overestimating the disease. Because there is an indirect cost to a person and imagine the psychological impact to a parent if you tell him your young child may have a possible problem. So we didn't want to do that, so we were very finicky about the validation. So, it went through multiple iterations almost to the effect that Mohit and his team could have lunch on a Thursday, only after they finished a call with us. 

(Laughs) 

Mohit Jain: To add to that, this is actually a very crucial point. Initially what we were thinking, so there are like these two values called as sensitivity and specificity. So just to give you some context here, sensitivity is actually if the person has keratoconus, are we able to diagnose it as keratoconus. So that's the sensitivity. Specificity is that if the person does not have Keratoconus are we actually even diagnosing that correctly? So, we were thinking that we need to get really high sensitivity. We cannot leave anyone who has keratoconus undiagnosed. But we can have low specificity that even someone who does not have keratoconus, we can say that he or she has keratoconus and still it's OK because then he or she will actually go to a doctor and get checked up, maybe for a second time and then it will be diagnosed that he or she does not have keratoconus. But Dr. Kaushik specifically was really against that. OK, so he actually made our problem statement harder, saying that we want both sensitivity and specificity to be above 92%, OK. Because he does not want like parents to be unnecessarily worrying that their kid who is like in his teens right now and he has like this very serious eye condition. So hence we actually have to like, as what Dr. Kaushik said, like you have to go through multiple iteration to even like get the specificity right. And right now, I think we are at a stage where we have like both the numbers which are above 94% for a small trial that we did with Sankara, with more than 100 patients, and in future we plan to actually extend that trial and like do it in many more patients. 

[Music] 

Sridhar Vedantham: A question for both you, Mohit, as well as Doctor Kaushik, so, whoever wants to answer it. You know, you just put out some numbers there in terms of percentages, right, to say that this solution works well, but typically these need to be tagged against some kind of industry benchmark or some kind of medical benchmark given the established machines and equipment already that are already being used, right? So how does this SmartKC stack up against those? 

Dr. Kaushik Murali: So once the MSR team had come up with a complete solution and they had tested in their lab the reliability of the solution, so to speak, with the images that they had with them, we then apply to our Ethics Committee for a prospective study. So, we enrolled subjects coming to our hospital, and we had them get their cornea image with the SmartKC as well as with the Placido based topography system that we have in our hospital that we would typically have used in any case. One index that the device that we use in the hospital uses to identify keratoconus, is an index called as the percentage probability of keratoconus, or the PPK value. This if it is more than 45% is supposed to indicate the presence of keratoconus. So, what we found was with the SmartKC, the sensitivity of PPK value was 94.1% and the specificity was 100%, which was pretty comparable to what we had with our other device which stood at about 94.1% sensitivity and 95.5% specificity. More importantly, whenever you use any device as a screening tool is how repeatable is it, and how is the inter-rater agreement. If two different people use the same device on the same person, are they actually reading it out the same. So again, in this we found those indices to be really, really high. So, there's something called as the Cohen’s Kappa value. This was about 0.94 for our tool, which compared to 0.96 for the device that we have in the hospital. This essentially indicates a fair agreement between two experts diagnosing keratoconus based on the images that we are generating using the SmartKC. 

Sridhar Vedantham: Wow, that's impressive. Uh, I had another question. You know, whenever I went into an eye hospital, there always seemed to be somebody who is well trained as a technician operating various machines. How does it work with this? I mean do you need any specific training on SmartKC? How intensive is that and are there any particular type of people you look for or some kind of skill level in people who can operate a SmartKC unit? 

Dr. Kaushik Murali: So, currently most of the data that was collected has been done by our optometry interns at the Sankara College of Optometry, so the skill set that was required was not very high. Like Mohit mentioned earlier, there is some assistant in terms of even how you can capture an image. So, the eventual endpoint for us would be this being used at a peripheral vision center or at some Primary Health Center as a part of a school screening program where a lay person can pick up this device and actually capture an image and at least be able to counsel the person about them having to have a further examination. So, the training that would probably be required is largely in terms of what the condition that they are screening for and what the next action needs to be. it's more counseling skill I would say rather than anything really technical. The machine does at all. It gives them a heat map, it tells them what the value is, it kind of literally puts up a red flag saying “Boss, be careful, there is a problem here”. 

Sridhar Vedantham: So, I'm guessing that's all part of the technology that's been built into it, say you know various guardrails to ensure that whoever is operating it is doing it in the right way, Mohit? 

Mohit Jain: Yes, yes Sridhar. So, basically in the latest version of the app, what we have done is that like the operator, whoever is actually capturing the image, he or she doesn't even have to click the capture button. So, you just have to place the SmartKC on a patient eye and it automatically tries to align it appropriately with the eye and once the alignment is right, once the image does not have any kind of a blur and the focus is appropriate, the light is fine, it automatically captures three images. So, that actually makes the process really easy for the operator. And he or she needs to go through very minimal training to get up and running with the device. 

Sridhar Vedantham: Nice. And you know we have referred earlier to the cost of current machines that are there that are used in eye hospitals and so on, right? And one of the guiding principles behind developing SmartKC was for something to be portable, inexpensive and easy to use in the field. One thing that I don't think we've spoken about yet is actually how inexpensive SmartKC is, and I'm also curious to find out whether the equipment that you use needs to be high end. For example, do you need a high-end mobile phone to do it and how does the whole system work? 

Mohit Jain: Yes, so currently for developing our research prototype, we actually end up spending like almost like $33 is the amount that we are end up spending making the device, apart from the smartphone. The smartphone that we are using is a slightly high end one, so it is around like a $400 device that we have used for the current prototype. But moving ahead we are actually for the next round of data collection with Sankar Hospital, we are actually trying out with like three different devices and starting from like $100 device, $200 device and the $300 device, so that we can actually see that with whether it works on all the devices. However, based on our current work, we hypothesize that, actually, it can work on any standard smartphone. It just needs a decent camera. By the way, nowadays even the $100 device have like a 20-megapixel camera. So, I think that's already taken care by the by the most of the latest smartphone. So, I think yeah, it should ideally work in all of them, but we will only know for sure once we have the second round of testing. 

Sridhar Vedantham: Cool. Uh, so you know, given that you've put in so much work and you've come up with something that sounds like a fantastic solution, what kind of impact do you think a SmartKC can have or what kind of impact do you hope SmartKC will have? 

Mohit Jain: So right now, actually, we have discussed a few use cases with Dr. Kaushik, and I think the most interesting use case is what Dr. Kaushik initially referred to is the teacher use case. The biggest impact SmartKC could have is that, let's say, all the teachers in India, even the rural one, urban one, semi urban or even like low-income community even in urban India they have access to SmartKC. And every year maybe twice a year or thrice a year they screen every children in their school for keratoconus. And because the numbers are really high, the numbers are like two to three children out of everyone hundred children will have keratoconus, so with that in mind, we should be able to get like a few cases from every school. So, if these are diagnosed very early on, then there is a very very high likelihood that they could have been treated just by simple glasses or contact lens, and they don't have to go through surgery or corneal transplant or blindness, which is the worst-case situation. By the way, I think earlier when we are talking about corneal transplant, so globally 27% of the corneal transplant happens to actually fix keratoconus. So it is, it is a very deadly disease. 

Dr. Kaushik Murali: So, I'm going to take off on a tangent. I'm actually going to look beyond just this particular solution. So, although I am here representing Sankara at this podcast, a couple of my colleagues actually did a deep dive into this entire solution. Dr. Anand and Dr. Pallavi were there, as well as some of our faculty from the College of Optometry. What this project has actually impacted us is to think of how we can actually leverage technology. Sitting in an eye hospital, often we have ideas, but we have no clue whom to ask. But honestly, now we know that there is a team at MSR that we can reach out to saying that hey, here is a problem, we think this warrants attention. Do you think you guys can solve it? And we found that works really well. So, this ability to collaborate between complete extremes of people, one end you have medical specialists have no clue about what engineering is. Today I think Mohit knows more optometry than even I do. 

(Laughs) 

So they actually borrowed textbooks from us to read. So, this kind of a collaboration is, I think, a phenomenal impact that this project has brought together, and we hope that together we will be able to come up with few more solutions that can align with our founders’ dream of eliminating needless blindness from India. 

Sridhar Vedantham: Nice, congratulations Mohit.  

Mohit Jain: Thank you. (Laughs). 

Sridhar Vedantham: I'll come to you for my next eye test. 

Dr. Kaushik Murali: You will soon start referring to him as Doctor Mohit. 

(Laughs) 

Sridhar Vedantham:  All right. I think I've got all the information that I really wanted. But one thing is, you know, if people want to adopt SmartKC and they want to take it out there in the field, what do they need to do? And are there any particular requirements or criteria that they need to fulfil, etc? I mean, how do people get hold of this? 

Mohit Jain: So right now, we have actually made everything open source. So, even the 3D print for the Placido disc, the STL file of that is open source. So, anyone can download it and just like you take a printout, you can actually go to a makerspace and get a 3D print of that. Even the app which is actually AI assisted app which is running on the smartphone, we have only written it for an Android phone, so you can actually download it and you can install it on your Android phone and connect that SmartKC Placido attachment and can click an image of eye. The image processing pipelines code is also completely open source, so the selected image you can then run on it to actually generate corneal topography heat map. So, that is that is the current state. Going ahead we are actually putting everything on the cloud so that once you have the Placido disc and you capture an image, it automatically goes to the cloud and gives you the final output. 

Sridhar Vedantham: Excellent. So I will add links to various things onto the podcast page once we're done with this. Dr. Kaushik, any final thoughts before we close this podcast? 

Dr. Kaushik Murali: So quite often we look at challenges as challenges, but I think essentially this collaboration has looked at an opportunity and how we can actually work on it. All it required was to put some method to the madness and what came up as one discussion is today, I think, churned out into three different projects that are currently underway. So, this is something that is a potential. It would be lovely if similar technology companies can collaborate with medical institutions across India. We don't have to look elsewhere for solutions. It's all here. It's up to us to figure it out and run with it. 

Sridhar Vedantham: That's a great note to end the podcast on. So, once again thank you so much, Dr. Kaushik and Dr. Mohit. Thank you so much. 

(Laughs) 

Mohit Jain: Thank you, Sridhar. 

[Music ends]