The ability to detect or predict glaucoma could help to prevent blindness through early, precision treatment. Optical coherence tomography (OCT) has considerably advanced diagnostic capabilities, but the basic mechanisms involved in glaucoma are still not well understood.
Researchers in NYU Langone Health’s Advanced Ophthalmic Imaging Laboratory are focusing on new technologies that can accelerate understanding of glaucoma and other neurodegenerative diseases. The team has recently shown, for example, that visible light OCT allows visualization and quantification of retinal pigment epithelium sublayers with high repeatability, providing clinically useful information on ocular diseases affecting their morphology.
“Visible OCT lets us map the retina in 3D with very high resolution. We can discriminate between healthy eyes and glaucomatous eyes using visible OCT oximetry thereby measuring retinal metabolism,” says Joel S. Schuman, MD, the Elaine Langone Professor of Ophthalmology and founder of the Advanced Ophthalmic Imaging program. Dr. Schuman is an inventor of OCT, which has become the standard of care around the world for noninvasive imaging of the visual system.
“We hope to detect glaucoma earlier than we can otherwise—before it can do significant damage,” he says. “We also hope to be able to assess glaucoma both in its early and late stages to determine whether or not progression is occurring.”
Stepping Beyond Conventional OCT
The Advanced Ophthalmic Imaging Laboratory is directed by Chaim (Gadi) Wollstein, MD, a professor of ophthalmology. The team includes ophthalmologists, engineers, software specialists, statisticians, and trainees. “It’s a wide variety of people,” Dr. Wollstein says. “That’s what it takes to make advances in technology.”
Visible OCT is just one OCT advancement under research. The team is using adaptive optics OCT to image the lamina cribrosa—the complex meshwork within the optic nerve supporting the retinal ganglion cell (RGC) axons. They also hope to visualize the RGC bodies to understand what makes certain eyes develop glaucoma.
“We’re looking at both primate and human eyes in vivo, which is very unique to our group’s work,” Dr. Wollstein explains. “We describe that the lamina cribrosa is actually different in the healthy eye compared to the glaucomatous eye, which may give us clues as to which patients would have a faster progression of glaucoma.”
Mapping the Trabecular Meshwork
Since the late 2000s, the Advanced Ophthalmic Imaging team has been developing techniques for visualizing the trabecular meshwork, or outflow system, in humans. These imaging techniques aim to improve glaucoma assessment and guidance of minimally invasive glaucoma surgery.
“We’re developing new techniques for mapping the tissue in a way that can be done by physicians in the clinic. We will be there within the next year or two,” Dr. Schuman says. The researchers are also evaluating the benefit of adipose-derived stem cell injections in the trabecular meshwork to repair and restore the function of the outflow system.
Supporting Neurological Inquiry
In other NIH-funded work, the lab is using both conventional and prototype OCT devices to identify biomarkers of disease in Alzheimer’s. Dr. Wollstein says a recent study defines the role of OCT criteria and machine learning in multiple sclerosis and optic neuritis diagnosis.
“We are working closely with our colleagues in neurology to perform the assessments and interpret the data,” Dr. Wollstein notes.
In a pilot study, the team is testing repetitive transorbital alternating current stimulation, a technology that provides mild electric current to stimulate neurons to improve function of RGCs and the optic nerve.
The goal is to help neuronal cells that are damaged, but not dead, function better.
AI-powered Precision Treatment
To better analyze the data from OCT imaging and image processing, the researchers are applying artificial intelligence. “We hope to predict who will get glaucoma. For those who have it, who will get worse more quickly,” says Dr. Schuman. “Wouldn’t it be nice if we could treat people less intensively if we knew their disease was going to progress slowly?”