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Artificial Intelligence Getting Smarter! Innovations from the Vision Field

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AI. Photograph of retina

One of many health risks premature infants face is retinopathy of prematurity (ROP), a leading cause of childhood blindness worldwide. ROP causes abnormal blood vessel growth in the light-sensing eye tissue called the retina. Left untreated, ROP can lead to lead to scarring, retinal detachment, and blindness. It’s the disease that caused singer and songwriter Stevie Wonder to lose his vision.

Now, effective treatments are available—if the disease is diagnosed early and accurately. Advancements in neonatal care have led to the survival of extremely premature infants, who are at highest risk for severe ROP. Despite major advancements in diagnosis and treatment, tragically, about 600 infants in the U.S. still go blind each year from ROP. This disease is difficult to diagnose and manage, even for the most experienced ophthalmologists. And the challenges are much worse in remote corners of the world that have limited access to ophthalmic and neonatal care.

Caption: Image of a neonatal retina prior to AI processing. Left: Image of a premature infant retina showing signs of severe ROP with large, twisted blood vessels; Right: Normal neonatal retina by comparison. Credit: Casey Eye Institute, Oregon Health and Science University, Portland, and National Eye Institute, NIH

Artificial intelligence (AI) is helping bridge these gaps. Prior to my tenure as National Eye Institute (NEI) director, I helped develop a system called i-ROP Deep Learning (i-ROP DL), which automates the identification of ROP. In essence, we trained a computer to identify subtle abnormalities in retinal blood vessels from thousands of images of premature infant retinas. Strikingly, the i-ROP DL artificial intelligence system outperformed even international ROP experts [1]. This has enormous potential to improve the quality and delivery of eye care to premature infants worldwide.

Of course, the promise of medical artificial intelligence extends far beyond ROP. In 2018, the FDA approved the first autonomous AI-based diagnostic tool in any field of medicine [2]. Called IDx-DR, the system streamlines screening for diabetic retinopathy (DR), and its results require no interpretation by a doctor. DR occurs when blood vessels in the retina grow irregularly, bleed, and potentially cause blindness. About 34 million people in the U.S. have diabetes, and each is at risk for DR.

As with ROP, early diagnosis and intervention is crucial to preventing vision loss to DR. The American Diabetes Association recommends people with diabetes see an eye care provider annually to have their retinas examined for signs of DR. Yet fewer than 50 percent of Americans with diabetes receive these annual eye exams.

The IDx-DR system was conceived by Michael Abramoff, an ophthalmologist and AI expert at the University of Iowa, Iowa City. With NEI funding, Abramoff used deep learning to design a system for use in a primary-care medical setting. A technician with minimal ophthalmology training can use the IDx-DR system to scan a patient’s retinas and get results indicating whether a patient should be sent to an eye specialist for follow-up evaluation or to return for another scan in 12 months.

Caption: The IDx-DR is the first FDA-approved system for diagnostic screening of diabetic retinopathy. It’s designed to be used in a primary care setting. Results determine whether a patient needs immediate follow-up. Credit: Digital Diagnostics, Coralville, IA.

Many other methodological innovations in AI have occurred in ophthalmology. That’s because imaging is so crucial to disease diagnosis and clinical outcome data are so readily available. As a result, AI-based diagnostic systems are in development for many other eye diseases, including cataract, age-related macular degeneration (AMD), and glaucoma.

Rapid advances in AI are occurring in other medical fields, such as radiology, cardiology, and dermatology. But disease diagnosis is just one of many applications for AI. Neurobiologists are using AI to answer questions about retinal and brain circuitry, disease modeling, microsurgical devices, and drug discovery.

If it sounds too good to be true, it may be. There’s a lot of work that remains to be done. Significant challenges to AI utilization in science and medicine persist. For example, researchers from the University of Washington, Seattle, last year tested seven AI-based screening algorithms that were designed to detect DR. They found under real-world conditions that only one outperformed human screeners [3]. A key problem is these AI algorithms need to be trained with more diverse images and data, including a wider range of races, ethnicities, and populations—as well as different types of cameras.

How do we address these gaps in knowledge? We’ll need larger datasets, a collaborative culture of sharing data and software libraries, broader validation studies, and algorithms to address health inequities and to avoid bias. The NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) project and NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program project will be major steps toward addressing those gaps.

So, yes—AI is getting smarter. But harnessing its full power will rely on scientists and clinicians getting smarter, too.

References:

[1] Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks. Brown JM, Campbell JP, Beers A, Chang K, Ostmo S, Chan RVP, Dy J, Erdogmus D, Ioannidis S, Kalpathy-Cramer J, Chiang MF; Imaging and Informatics in Retinopathy of Prematurity (i-ROP) Research Consortium. JAMA Ophthalmol. 2018 Jul 1;136(7):803-810.

[2] FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems. Food and Drug Administration. April 11, 2018.

[3] Multicenter, head-to-head, real-world validation study of seven automated artificial intelligence diabetic retinopathy screening systems. Lee AY, Yanagihara RT, Lee CS, Blazes M, Jung HC, Chee YE, Gencarella MD, Gee H, Maa AY, Cockerham GC, Lynch M, Boyko EJ. Diabetes Care. 2021 May;44(5):1168-1175.

Links:

Retinopathy of Prematurity (National Eye Institute/NIH)

Diabetic Eye Disease (NEI)

NEI Research News

Michael Abramoff (University of Iowa, Iowa City)

Bridge to Artificial Intelligence (Common Fund/NIH)

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program (NIH)

[Note: Acting NIH Director Lawrence Tabak has asked the heads of NIH’s institutes and centers to contribute occasional guest posts to the blog as a way to highlight some of the cool science that they support and conduct. This is the second in the series of NIH institute and center guest posts that will run until a new permanent NIH director is in place.]


Preventing Glaucoma Vision Loss with ‘Big Data’

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Credit: University of California San Diego

Each morning, more than 2 million Americans start their rise-and-shine routine by remembering to take their eye drops. The drops treat their open-angle glaucoma, the most-common form of the disease, caused by obstructed drainage of fluid where the eye’s cornea and iris meet. The slow drainage increases fluid pressure at the front of the eye. Meanwhile, at the back of the eye, fluid pushes on the optic nerve, causing its bundled fibers to fray and leading to gradual loss of side vision.

For many, the eye drops help to lower intraocular pressure and prevent vision loss. But for others, the drops aren’t sufficient and their intraocular pressure remains high. Such people will need next-level care, possibly including eye surgery, to reopen the clogged drainage ducts and slow this disease that disproportionately affects older adults and African Americans over age 40.

Sally Baxter
Credit: University of California San Diego

Sally Baxter, a physician-scientist with expertise in ophthalmology at the University of California, San Diego (UCSD), wants to learn how to predict who is at greatest risk for serious vision loss from open-angle and other forms of glaucoma. That way, they can receive more aggressive early care to protect their vision from this second-leading cause of blindness in the U.S..

To pursue this challenging research goal, Baxter has received a 2020 NIH Director’s Early Independence Award. Her research will build on the clinical observation that people with glaucoma frequently battle other chronic health problems, such as high blood pressure, diabetes, and heart disease. To learn more about how these and other chronic health conditions might influence glaucoma outcomes, Baxter has begun mining a rich source of data: electronic health records (EHRs).

In an earlier study of patients at UCSD, Baxter showed that EHR data helped to predict which people would need glaucoma surgery within the next six months [1]. The finding suggested that the EHR, especially information on a patient’s blood pressure and medications, could predict the risk for worsening glaucoma.

In her NIH-supported work, she’s already extended this earlier “Big Data” finding by analyzing data from more than 1,200 people with glaucoma who participate in NIH’s All of Us Research Program [2]. With consent from the participants, Baxter used their EHRs to train a computer to find telltale patterns within the data and then predict with 80 to 99 percent accuracy who would later require eye surgery.

The findings confirm that machine learning approaches and EHR data can indeed help in managing people with glaucoma. That’s true even when the EHR data don’t contain any information specific to a person’s eye health.

In fact, the work of Baxter and other groups have pointed to an especially important role for blood pressure in shaping glaucoma outcomes. Hoping to explore this lead further with the support of her Early Independence Award, Baxter also will enroll patients in a study to test whether blood-pressure monitoring smart watches can add important predictive information on glaucoma progression. By combining round-the-clock blood pressure data with EHR data, she hopes to predict glaucoma progression with even greater precision. She’s also exploring innovative ways to track whether people with glaucoma use their eye drops as prescribed, which is another important predictor of the risk of irreversible vision loss [3].

Glaucoma research continues to undergo great progress. This progress ranges from basic research to the development of new treatments and high-resolution imaging technologies to improve diagnostics. But Baxter’s quest to develop practical clinical tools hold great promise, too, and hopefully will help one day to protect the vision of millions of people with glaucoma around the world.

References:

[1] Machine learning-based predictive modeling of surgical intervention in glaucoma using systemic data from electronic health records. Baxter SL, Marks C, Kuo TT, Ohno-Machado L, Weinreb RN. Am J Ophthalmol. 2019 Dec; 208:30-40.

[2] Predictive analytics for glaucoma using data from the All of Us Research Program. Baxter SL, Saseendrakumar BR, Paul P, Kim J, Bonomi L, Kuo TT, Loperena R, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark CR, Cohn E, Gebo K, Mayo K, Mockrin S, Schully SD, Ramirez A, Ohno-Machado L; All of Us Research Program Investigators. Am J Ophthalmol. 2021 Jul;227:74-86.

[3] Smart electronic eyedrop bottle for unobtrusive monitoring of glaucoma medication adherence. Aguilar-Rivera M, Erudaitius DT, Wu VM, Tantiongloc JC, Kang DY, Coleman TP, Baxter SL, Weinreb RN. Sensors (Basel). 2020 Apr 30;20(9):2570.

Links:

Glaucoma (National Eye Institute/NIH)

All of Us Research Program (NIH)

Video: Sally Baxter (All of Us Research Program)

Sally Baxter (University of California San Diego)

Baxter Project Information (NIH RePORTER)

NIH Director’s Early Independence Award (Common Fund)

NIH Support: Common Fund


The Amazing Brain: Making Up for Lost Vision

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Recently, I’ve highlighted just a few of the many amazing advances coming out of the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. And for our grand finale, I’d like to share a cool video that reveals how this revolutionary effort to map the human brain is opening up potential plans to help people with disabilities, such as vision loss, that were once unimaginable.

This video, produced by Jordi Chanovas and narrated by Stephen Macknik, State University of New York Downstate Health Sciences University, Brooklyn, outlines a new strategy aimed at restoring loss of central vision in people with age-related macular degeneration (AMD), a leading cause of vision loss among people age 50 and older. The researchers’ ultimate goal is to give such people the ability to see the faces of their loved ones or possibly even read again.

In the innovative approach you see here, neuroscientists aren’t even trying to repair the part of the eye destroyed by AMD: the light-sensitive retina. Instead, they are attempting to recreate the light-recording function of the retina within the brain itself.

How is that possible? Normally, the retina streams visual information continuously to the brain’s primary visual cortex, which receives the information and processes it into the vision that allows you to read these words. In folks with AMD-related vision loss, even though many cells in the center of the retina have stopped streaming, the primary visual cortex remains fully functional to receive and process visual information.

About five years ago, Macknik and his collaborator Susana Martinez-Conde, also at Downstate, wondered whether it might be possible to circumvent the eyes and stream an alternative source of visual information to the brain’s primary visual cortex, thereby restoring vision in people with AMD. They sketched out some possibilities and settled on an innovative system that they call OBServ.

Among the vital components of this experimental system are tiny, implantable neuro-prosthetic recording devices. Created in the Macknik and Martinez-Conde labs, this 1-centimeter device is powered by induction coils similar to those in the cochlear implants used to help people with profound hearing loss. The researchers propose to surgically implant two of these devices in the rear of the brain, where they will orchestrate the visual process.

For technical reasons, the restoration of central vision will likely be partial, with the window of vision spanning only about the size of one-third of an adult thumbnail held at arm’s length. But researchers think that would be enough central vision for people with AMD to regain some of their lost independence.

As demonstrated in this video from the BRAIN Initiative’s “Show Us Your Brain!” contest, here’s how researchers envision the system would ultimately work:

• A person with vision loss puts on a specially designed set of glasses. Each lens contains two cameras: one to record visual information in the person’s field of vision; the other to track that person’s eye movements enabled by residual peripheral vision.
• The eyeglass cameras wirelessly stream the visual information they have recorded to two neuro-prosthetic devices implanted in the rear of the brain.
• The neuro-prosthetic devices process and project this information onto a specific set of excitatory neurons in the brain’s hard-wired visual pathway. Researchers have previously used genetic engineering to turn these neurons into surrogate photoreceptor cells, which function much like those in the eye’s retina.
• The surrogate photoreceptor cells in the brain relay visual information to the primary visual cortex for processing.
• All the while, the neuro-prosthetic devices perform quality control of the visual signals, calibrating them to optimize their contrast and clarity.

While this might sound like the stuff of science-fiction (and this actual application still lies several years in the future), the OBServ project is now actually conceivable thanks to decades of advances in the fields of neuroscience, vision, bioengineering, and bioinformatics research. All this hard work has made the primary visual cortex, with its switchboard-like wiring system, among the brain’s best-understood regions.

OBServ also has implications that extend far beyond vision loss. This project provides hope that once other parts of the brain are fully mapped, it may be possible to design equally innovative systems to help make life easier for people with other disabilities and conditions.

Links:

Age-Related Macular Degeneration (National Eye Institute/NIH)

Macknik Lab (SUNY Downstate Health Sciences University, Brooklyn)

Martinez-Conde Laboratory (SUNY Downstate Health Sciences University)

Show Us Your Brain! (BRAIN Initiative/NIH)

Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

NIH Support: BRAIN Initiative


Moving Closer to a Stem Cell-Based Treatment for AMD

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In recent years, researchers have figured out how to take a person’s skin or blood cells and turn them into induced pluripotent stem cells (iPSCs) that offer tremendous potential for regenerative medicine. Still, it’s been a challenge to devise safe and effective ways to move this discovery from the lab into the clinic. That’s why I’m pleased to highlight progress toward using iPSC technology to treat a major cause of vision loss: age-related macular degeneration (AMD).

In the new work, researchers from NIH’s National Eye Institute developed iPSCs from blood-forming stem cells isolated from blood donated by people with advanced AMD [1]. Next, these iPSCs were exposed to a variety of growth factors and placed on supportive scaffold that encouraged them to develop into healthy retinal pigment epithelium (RPE) tissue, which nurtures the light-sensing cells in the eye’s retina. The researchers went on to show that their lab-grown RPE patch could be transplanted safely into animal models of AMD, preventing blindness in the animals.

This preclinical work will now serve as the foundation for a safety trial of iPSC-derived RPE transplants in 12 human volunteers who have already suffered vision loss due to the more common “dry” form of AMD, for which there is currently no approved treatment. If all goes well, the NIH-led trial may begin enrolling patients as soon as this year.

Risk factors for AMD include a combination of genetic and environmental factors, including age and smoking. Currently, more than 2 million Americans have vision-threatening AMD, with millions more having early signs of the disease [2].

AMD involves progressive damage to the macula, an area of the retina about the size of a pinhead, made up of millions of light-sensing cells that generate our sharp, central vision. Though the exact causes of AMD are unknown, RPE cells early on become inflamed and lose their ability to clear away debris from the retina. This leads to more inflammation and progressive cell death.

As RPE cells are lost during the “dry” phase of the disease, light-sensing cells in the macula also start to die and reduce central vision. In some people, abnormal, leaky blood vessels will form near the macula, called “wet” AMD, spilling fluid and blood under the retina and causing significant vision loss. “Wet” AMD has approved treatments. “Dry” AMD does not.

But, advances in iPSC technology have brought hope that it might one day be possible to shore up degenerating RPE in those with dry AMD, halting the death of light-sensing cells and vision loss. In fact, preliminary studies conducted in Japan explored ways to deliver replacement RPE to the retina [3]. Though progress was made, those studies highlighted the need for more reliable ways to produce replacement RPE from a patient’s own cells. The Japanese program also raised concerns that iPSCs derived from people with AMD might be prone to cancer-causing genomic changes.

With these challenges in mind, the NEI team led by Kapil Bharti and Ruchi Sharma have designed a more robust process to produce RPE tissue suitable for testing in people. As described in Science Translational Medicine, they’ve come up with a three-step process.

Rather than using fibroblast cells from skin as others had done, Bharti and Sharma’s team started with blood-forming stem cells from three AMD patients. They reprogrammed those cells into “banks” of iPSCs containing multiple different clones, carefully screening them to ensure that they were free of potentially cancer-causing changes.

Next, those iPSCs were exposed to a special blend of growth factors to transform them into RPE tissue. That recipe has been pursued by other groups for a while, but needed to be particularly precise for this human application. In order for the tissue to function properly in the retina, the cells must assemble into a uniform sheet, just one-cell thick, and align facing in the same direction.

So, the researchers developed a specially designed scaffold made of biodegradable polymer nanofibers. That scaffold helps to ensure that the cells orient themselves correctly, while also lending strength for surgical transplantation. By spreading a single layer of iPSC-derived RPE progenitors onto their scaffolds and treating it with just the right growth factors, the researchers showed they could produce an RPE patch ready for the clinic in about 10 weeks.

To test the viability of the RPE patch, the researchers first transplanted a tiny version (containing about 2,500 RPE cells) into the eyes of a rat with a compromised immune system, which enables human cells to survive. By 10 weeks after surgery, the human replacement tissue had integrated into the animals’ retinas with no signs of toxicity.

Next, the researchers tested a larger RPE patch (containing 70,000 cells) in pigs with an AMD-like condition. This patch is the same size the researchers ultimately would expect to use in people. Ten weeks after surgery, the RPE patch had integrated into the animals’ eyes, where it protected the light-sensing cells that are so critical for vision, preventing blindness.

These results provide encouraging evidence that the iPSC approach to treating dry AMD should be both safe and effective. But only a well-designed human clinical trial, with all the appropriate prior oversights to be sure the benefits justify the risks, will prove whether or not this bold approach might be the solution to blindness faced by millions of people in the future.

As the U.S. population ages, the number of people with advanced AMD is expected to rise. With continued progress in treatment and prevention, including iPSC technology and many other promising approaches, the hope is that more people with AMD will retain healthy vision for a lifetime.

References:

[1] Clinical-grade stem cell-derived retinal pigment epithelium patch rescues retinal degeneration in rodents and pigs. Sharma R, Khristov V, Rising A, Jha BS, Dejene R, Hotaling N, Li Y, Stoddard J, Stankewicz C, Wan Q, Zhang C, Campos MM, Miyagishima KJ, McGaughey D, Villasmil R, Mattapallil M, Stanzel B, Qian H, Wong W, Chase L, Charles S, McGill T, Miller S, Maminishkis A, Amaral J, Bharti K. Sci Transl Med. 2019 Jan 16;11(475).

[2] Age-Related Macular Degeneration, National Eye Institute.

[3] Autologous Induced Stem-Cell-Derived Retinal Cells for Macular Degeneration. Mandai M, Watanabe A, Kurimoto Y, Hirami Y, Takasu N, Ogawa S, Yamanaka S, Takahashi M, et al. N Engl J Med. 2017 Mar 16;376(11):1038-1046.

Links:

Facts About Age-Related Macular Degeneration (National Eye Institute/NIH)

Stem Cell-Based Treatment Used to Prevent Blindness in Animal Models of Retinal Degeneration (National Eye Institute/NIH)

Kapil Bharti (NEI)

NIH Support: National Eye Institute; Common Fund


Regenerative Medicine: The Promise and Peril

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Retinal pigment epithelial cells

Caption: Scanning electron micrograph of iPSC-derived retinal pigment epithelial cells growing on a nanofiber scaffold (blue).
Credit: Sheldon Miller, Arvydas Maminishkis, Robert Fariss, and Kapil Bharti, National Eye Institute/NIH

Stem cells derived from a person’s own body have the potential to replace tissue damaged by a wide array of diseases. Now, two reports published in the New England Journal of Medicine highlight the promise—and the peril—of this rapidly advancing area of regenerative medicine. Both groups took aim at the same disorder: age-related macular degeneration (AMD), a common, progressive form of vision loss. Unfortunately for several patients, the results couldn’t have been more different.

In the first case, researchers in Japan took cells from the skin of a female volunteer with AMD and used them to create induced pluripotent stem cells (iPSCs) in the lab. Those iPSCs were coaxed into differentiating into cells that closely resemble those found near the macula, a tiny area in the center of the eye’s retina that is damaged in AMD. The lab-grown tissue, made of retinal pigment epithelial cells, was then transplanted into one of the woman’s eyes. While there was hope that there might be actual visual improvement, the main goal of this first in human clinical research project was to assess safety. The patient’s vision remained stable in the treated eye, no adverse events occurred, and the transplanted cells remained viable for more than a year.

Exciting stuff, but, as the second report shows, it is imperative that all human tests of regenerative approaches be designed and carried out with the utmost care and scientific rigor. In that instance, three elderly women with AMD each paid $5,000 to a Florida clinic to be injected in both eyes with a slurry of cells, including stem cells isolated from their own abdominal fat. The sad result? All of the women suffered severe and irreversible vision loss that left them legally or, in one case, completely blind.


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