Since the dawn of human spaceflight, scientists have carefully studied the effects of space and microgravity on astronauts. After decades of observations and examinations, one truth is certain: space is brutal on the human body. Muscles atrophy, bones lose mass, limbs stretch and — more unknown — eyesight can degrade in ways not yet fully understood.

To better understand the loss of vision caused by space flight, University of California San Diego researchers used U.S. National Science Foundation (NSF) ACCESS allocations on the Expanse system at the San Diego Supercomputer Center (SDSC) to predict who is most at risk for developing eyesight issues — before liftoff. The team — led by researchers at the Shiley Eye Institute and Viterbi Family Department of Ophthalmology in collaboration with the Halıcıoğlu Data Science Institute (HDSI) at the UC San Diego School of Computing, Information and Data Science — used artificial intelligence (AI), trained on high resolution eye scans, to predict individuals at highest risk.

According to NASA, around 29 percent of crew members who participated in short-duration space flights reported a degradation of distance or near-visual acuity. For crew members in long-duration missions, that number spiked to 60 percent. In 2017, scientists first used the name Spaceflight Associated Neuro-ocular Syndrome (SANS) to describe this vision degradation caused by space flights. While symptoms — including optic disc (beginning of the optic nerve which goes to the brain) swelling, vision shifts and structural distortions — often resolve within weeks to months post-flight, in some cases they do not resolve for years after long-duration missions.

“Our models showed promising accuracy, even when trained on limited data,” said lead author Alex Huang, M.D., Ph.D., a professor of ophthalmology at UC San Diego School of Medicine and HDSI affiliate faculty. “We’re essentially using AI to give doctors a predictive tool for a condition that develops in space, before astronauts even leave Earth.”

Huang added that tools such as the one his team developed can support risk management and, in the future, preventative measures prior to launch.

The AI system was trained using optical coherence tomography (OCT) scans — microscope-like images of the optic nerve — collected before and during space flight. The researchers also used data from head-down tilt bedrest studies on Earth. In this procedure, participants lay in a continuous six-degree head-down tilt, 24-hours a day, mimicking the effects of weightlessness by shifting fluids toward the head.

Watch the short video - New AI Tool Predicts Vision Loss in Astronauts

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Predicting the Unpredictable — with Help from a Supercomputer

To overcome the challenge of limited astronaut data, the team used deep learning — a form of AI that mimics how the brain processes images. They broke each eye scan into thousands of slices, creating a much larger dataset for training the models. The researchers also used data augmentation and transfer learning, which help the AI generalize from small samples.

Then, with the help of NSF ACCESS allocations on SDSC’s Expanse system, the team trained and tested their models. The best version could predict SANS with up to 82 percent accuracy, using only preflight scans. Even models trained on Earth-based bedrest data performed well, suggesting that SANS-like changes in these simulations closely mirror changes in actual spaceflight.

“One of the most exciting findings was how similar the AI’s attention patterns were across both space and Earth data,” said Mark Christopher, Ph.D., a UC San Diego ophthalmology data scientist and co-author of the study. “This strengthens the case for using Earth-based models to study space health — a promising development towards advancing human spaceflight research.”

To better understand what the AI was “seeing,” the researchers used class activation maps — visual heatmaps that highlight areas of interest. The models consistently focused on specific eye layers involved in fluid balance and pressure — like the back of the eye’s retinal nerve fiber layer and retinal pigment epithelium — giving scientists new clues about the biology behind SANS.

While the researchers caution that their models are not yet ready for clinical use, they see enormous potential in future versions. These AI tools could one day help NASA personalize astronaut care, guide countermeasure development and even predict the severity of optic changes during future long-term spaceflight missions.

“The results and models from this study are early, but it’s a strong foundation,” Huang said. “With more data and refinement, this could become an essential part of astronaut health planning.”

The study was published in the American Journal of Ophthalmology.

Huang is the Alfred Vogt Endowed Chair in Ophthalmology and a glaucoma specialist. The Ophthalmologist named Huang the #1 Rising Star in the World in 2017 and recognized him on The Ophthalmologist Power 100 List in 2020. In 2021, Huang received the Association for Research in Vision and Ophthalmology  Foundation Pfizer Ophthalmics Carl Camras Translational Research Award.

This research was supported by NASA’s Human Research Program (grant nos. 80NNSSC20K1034, NNJ15KK11B and NNJ11ZSA002NA), the National Eye Institute (grant nos. R00EY030942 and P30EY022589) and the Research to Prevent Blindness program. The use of SDSC’s Expanse was allocated by NSF ACCESS (grant no. TG-CIS220009).

This research is also highlighted here: https://today.ucsd.edu/story/inside-uc-san-diegos-out-of-this-world-impact

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