"Spaceflight-to-Eye Clinic": Terrestrial advances in ophthalmic healthcare delivery from space-based innovations

The phrase "Bench-to-Bedside" is a well-known phrase in medicine, highlighting scientific discoveries that directly translate to impacting patient care. Key examples of translational research include identification of key molecular targets in diseases and development of diagnostic laboratory tests for earlier disease detection. Bridging these scientific advances to the bedside/clinic has played a meaningful impact in numerous patient lives. The spaceflight environment poses a unique opportunity to also make this impact; the nature of harsh extraterrestrial conditions and medically austere and remote environments push for cutting-edge technology innovation. Many of these novel technologies built for the spaceflight environment also have numerous benefits for human health on Earth. In this manuscript, we focus on "Spaceflight-to-Eye Clinic" and discuss technologies built for the spaceflight environment that eventually helped to optimize ophthalmic health on Earth (e.g., LADAR for satellite docking now utilized in eye-tracking technology for LASIK). We also discuss current technology research for spaceflight associated neuro-ocular syndrome (SANS) that may also be applied to terrestrial ophthalmic health. Ultimately, various advances made to enable to the future of space exploration have also advanced the ophthalmic health of individuals on Earth.

Potential for GPT Technology to Optimize Future Clinical Decision-Making Using Retrieval-Augmented Generation

Advancements in artificial intelligence (AI) provide many helpful tools for healthcare, one of which includes AI chatbots that use natural language processing to create humanlike, conversational dialog. These chatbots have general cognitive skills and are able to engage with clinicians and patients to discuss patients' health conditions and what they may be at risk for. While chatbot engines have access to a wide range of medical texts and research papers, they currently provide high-level, generic responses and are limited in their ability to provide diagnostic guidance and clinical advice to patients on an individual level. The essay discusses the use of retrieval-augmented generation (RAG), which can be used to improve the specificity of user-entered prompts and thereby enhance the detail in AI chatbot responses. By embedding more recent clinical data and trusted medical sources, such as clinical guidelines, into the chatbot models, AI chatbots can provide more patient-specific guidance, faster diagnoses and treatment recommendations, and greater improvement of patient outcomes.

Longitudinal changes in pigment epithelial detachment composition indices (PEDCI): new biomarkers in neovascular age-related macular degeneration

PURPOSE

To evaluate novel, automated biomarkers, pigment epithelial detachment composition indices (PEDCI) in eyes with neovascular age-related macular degeneration (nAMD) undergoing anti-vascular endothelial growth factor (anti-VEGF) therapy through 24 months.

METHODS

Retrospective analysis of 37 eyes (34 patients) with PED associated with nAMD receiving as-needed anti-VEGF treatment was performed. Best-corrected visual acuity (BCVA) and optical coherence tomography images were acquired at a treatment-naïve baseline and 3-, 6-, 12-, 18-, and 24-month visits. Previously validated automated imaging biomarkers, PEDCI-S (serous), PEDCI-N (neovascular), and PEDCI-F (fibrous) within PEDs were measured. ANOVA analysis and Spearman correlation were performed.

RESULTS

Mean BCVA (in logMAR) was 0.60 ± 0.47, 0.45 ± 0.41, 0.49 ± 0.49, 0.61 ± 0.54, 0.59 ± 0.56, and 0.67 ± 0.57 at baseline, 3, 6, 12, 18, and 24 months respectively. Overall, BCVA showed minimal worsening of 0.07 ± 0.54 logMAR (p = 0.07). 13.38 ± 3.77 anti-VEGF injections were given through 24 months. PEDCI-F showed an increase of 0.116, 0.122, 0.036, and 0.006 at months 3, 6, 12, and 18 respectively and a decrease of 0.004 at month 24 (p = 0.03); PEDCI-S showed a decrease of 0.064, 0.130, 0.091, 0.092, and 0.095 at months 3, 6, 12, 18, and 24 respectively (p = 0.16); PEDCI-N showed a decrease of 0.052 at month 3 and an increase of 0.008, 0.055, 0.086, and 0.099 at months 6, 12, 18, and 24 respectively (p = 0.06). BCVA was negatively correlated with PEDCI-F (r = -0.28, p < 0.01), and positively correlated with PEDCI-N (r = 0.28, p < 0.01) and PEDCI-S (r = 0.15, p = 0.03).

CONCLUSION

Longitudinal analysis of PEDCI supports their utility as biomarkers that characterize treatment related effects by quantifying the relative composition of PEDs.

National Football League Game Officials Self-Rating of Knowledge in Neuro-Ophthalmic Principles and Practice: A Pilot Program to Improve Precision and Accuracy of Game Official Calls

BACKGROUND

To determine whether a neuro-ophthalmic curriculum would improve National Football League (NFL) game officials' self-rated knowledge and interest in neuro-ophthalmic principles to improve precision and accuracy of NFL play-calling.

METHODS

The formalized and structured neuro-ophthalmic principles (NOP) curriculum was introduced to 121 NFL game officials, 17 replay officials, and 4 officiating staff who attended the NFL Official Training Camp in Irving, Texas, on September 8 and 9, 2023. Before and after the lecture and videos were introduced, participants completed an optional hard-copy feedback form pertaining to self-reported NOP knowledge, likelihood of using said terms, and interest in future content of NOP applicable NFL officiating. Paired 2-tailed t tests were used for statistical analysis to directly compare the self-reported knowledge before and after the neuro-ophthalmic curriculum introduction.

RESULTS

One hundred forty-two participants completed the prelecture and postlecture feedback forms self-reported knowledge after the NOP curriculum was given to the NFL officiating staff. All (142/142) participants completed a survey. There was a statistically significant improvement in the mean ratings of the prelecture vs. postlecture understanding of the specific neuro-ophthalmic terms pertinent to NFL game officials (2.6 [95% CI, 2.3-3.0] vs. 7.9 [95% CI, 7.6-8.2], P < 0.001) and 2.7 [95% CI, 2.3-3.0] vs. 7.7 [95% CI, 7.4-8.0]), respectively. There was a statistically significant greater likelihood of using said terms prelecture vs. postlecture (2.9 [95% CI, 2.4-3.4] vs. 7.5 [95% CI, 7.2-7.9], P < 0.001).

CONCLUSIONS

This study found a statistically significant improvement in neuro-ophthalmic knowledge and a greater likelihood of using NOP terms following the NOP curriculum. NFL game officials, replay officials, and staff are interested in expanding their knowledge in the vision science of neuro-ophthalmic concepts and applications involved in play-calling. We hope that our pilot data will lead to a model of education that will improve the precision and accuracy of NFL play-calls by officials on game days.

Artificial intelligence in chorioretinal pathology through fundoscopy: a comprehensive review

BACKGROUND

Applications for artificial intelligence (AI) in ophthalmology are continually evolving. Fundoscopy is one of the oldest ocular imaging techniques but remains a mainstay in posterior segment imaging due to its prevalence, ease of use, and ongoing technological advancement. AI has been leveraged for fundoscopy to accomplish core tasks including segmentation, classification, and prediction.

MAIN BODY

In this article we provide a review of AI in fundoscopy applied to representative chorioretinal pathologies, including diabetic retinopathy and age-related macular degeneration, among others. We conclude with a discussion of future directions and current limitations.

SHORT CONCLUSION

As AI evolves, it will become increasingly essential for the modern ophthalmologist to understand its applications and limitations to improve patient outcomes and continue to innovate.

Ethical Considerations of Neuralink and Brain-Computer Interfaces

Neuralink is a neurotechnology company founded by Elon Musk in 2016, which has been quietly developing revolutionary technology allowing for ultra-high precision bidirectional communication between external devices and the brain. In this paper, we explore the multifaceted ethical considerations surrounding neural interfaces, analyzing potential societal impacts, risks, and call for a need for responsible innovation. Despite the technological, medical, medicolegal, and ethical challenges ahead, neural interface technology remains extremely promising and has the potential to create a new era of medicine.

Concerns with OpenAI's Sora in Medicine

Open AI's Sora represents a ground-breaking innovation in AI that can generate lifelike and imaginative visual scenes based on text prompts. However, Sora has also produced some new concerns surrounding artificial video generation in medicine. While Sora is highly promising to enhance patient education, facilitate remote consultations and simulate surgical procedures, AI-generated videos also bring technical, legal, and ethical challenges. In this paper, we explore the clinical and ethical implications of Sora's AI-generated videos in the field of medicine.

Gender differences in central serous chorioretinopathy based on the new multimodal imaging classification

PURPOSE

To analyse the gender-specific differences in central serous chorioretinopathy (CSCR) based on a new multimodal imaging classification system.

METHOD

This was a retrospective, multicentric, longitudinal, observational study in patients with a diagnosis of unilateral or bilateral CSCR. Visual acuity outcomes and differences based on 'Simple' and 'Complex' CSCR were analysed. The occurrence of choroidal neovascularization (CNVM) and number of recurrences were also compared. Regression analysis was used to evaluate baseline predictors of final visual acuity.

RESULTS

The study included 109 eyes of 58 patients (55 eyes of 28 female patients and 54 eyes of 30 male patients). Simple CSCR was seen in 8 (14.8%) eyes and 21 (38.2%) eyes in male and female groups respectively, while complex CSCR was seen in 46 (85.2%) eyes and 34 (61.8%) eyes in male and female groups respectively (p = 0.005). Recurrence was more commonly seen in males (34 eyes) than in females (23 eyes) (p = 0.03). Males (96.7%) were also significantly more likely to have a bilateral presentation (78.6% in females) (p = 0.03). Conversely, CNVM was more commonly seen in female eyes (8 eyes) than male eyes (4 eyes) (p = 0.23). On multivariable regression analysis, factors affecting reduced need for treatment were history of steroid use, good visual acuity at baseline, and simple CSCR. Factors affecting good final visual acuity were history of steroid use, good visual acuity at baseline, and younger age.

CONCLUSION

Males tended to have complex CSCR and recurrence compared to the female sub-group, while females exhibited CNVM more commonly than males.

SANS-CNN: An automated machine learning technique for spaceflight associated neuro-ocular syndrome with astronaut imaging data

Spaceflight associated neuro-ocular syndrome (SANS) is one of the largest physiologic barriers to spaceflight and requires evaluation and mitigation for future planetary missions. As the spaceflight environment is a clinically limited environment, the purpose of this research is to provide automated, early detection and prognosis of SANS with a machine learning model trained and validated on astronaut SANS optical coherence tomography (OCT) images. In this study, we present a lightweight convolutional neural network (CNN) incorporating an EfficientNet encoder for detecting SANS from OCT images titled "SANS-CNN." We used 6303 OCT B-scan images for training/validation (80%/20% split) and 945 for testing with a combination of terrestrial images and astronaut SANS images for both testing and validation. SANS-CNN was validated with SANS images labeled by NASA to evaluate accuracy, specificity, and sensitivity. To evaluate real-world outcomes, two state-of-the-art pre-trained architectures were also employed on this dataset. We use GRAD-CAM to visualize activation maps of intermediate layers to test the interpretability of SANS-CNN's prediction. SANS-CNN achieved 84.2% accuracy on the test set with an 85.6% specificity, 82.8% sensitivity, and 84.1% F1-score. Moreover, SANS-CNN outperforms two other state-of-the-art pre-trained architectures, ResNet50-v2 and MobileNet-v2, in accuracy by 21.4% and 13.1%, respectively. We also apply two class-activation map techniques to visualize critical SANS features perceived by the model. SANS-CNN represents a CNN model trained and validated with real astronaut OCT images, enabling fast and efficient prediction of SANS-like conditions for spaceflight missions beyond Earth's orbit in which clinical and computational resources are extremely limited.

Impact of COVID-19 on Neuro-Ophthalmology in the United States: A National Survey

PURPOSE

To evaluate the impacts of the COVID-19 on neuro-ophthalmology practice in the United States.

DESIGN

Cross-sectional study.

METHODS

The North American Neuro-ophthalmology Society distributed a survey on the impact of COVID-19 on neuro-ophthalmic practice to its members. The survey consisted of 15 questions regarding the impact of the pandemic on neuro-ophthalmic practice and perspectives.

RESULTS

Twenty-eight neuro-ophthalmologists practicing in the United States responded to our survey. In this survey, 64% of survey respondents were male (n = 18), while 36% were female (n = 10). The average age of a respondent was 55 years old. According to 77% of survey respondents, various neuro-ophthalmic diseases were reported to have worsened during the pandemic including idiopathic intracranial hypertension, compressive optic neuropathy, optic neuritis, and giant cell arteritis.

CONCLUSIONS

This survey represents one of the largest studies to describe the impact of the COVID-19 pandemic of neuro-ophthalmology. Given the underrepresentation of neuro-ophthalmology in the United States as described in the literature, this study strengthens the need for more neuro-ophthalmologists to provide timely care, particularly during the pandemic. Further interventions to incentivize the pursuit of neuro-ophthalmology training may help combat the effects of COVID-19 on neuro-ophthalmic conditions.

Pigment epithelial detachment composition indices in central serous chorioretinopathy as a biomarker for disease activity: A computational methodology and 1 year outcomes

PURPOSE

Investigation of pigment epithelial detachment (PED) characteristics in central serous chorioretinopathy (CSCR) is underrepresented in the literature. We present a novel computational approach to quantify PED composition indices (PEDCI) in CSCR and track changes over time.

METHODS

34 eyes with active CSCR were analyzed quarterly over a 1-year period. Cases were categorized into acute and chronic CSCR depending on a symptom duration of less than 3 months or more than 3 months respectively. PED, retinal and choroidal dimensions were manually measured, and interval changes were compared using repeated measures of variance ANOVA. PED composition analysis involved manual segmentation followed by automated sub segmentation of PED areas to identify serous, neovascular and fibrous tissues. PEDCI for each component was compared among cases of acute and chronic CSCR.

RESULTS

CMT and NSD-h decreased by 65.2 µm (p = 0.01), and 86.5 µm (p < 0.01) respectively at 12 months. At baseline, 7/17 acute CSCR eyes and 8/15 chronic CSCR eyes had a concomitant PED; acute cases had both serous and neovascular components (PEDCI-S: 16.95%, PEDCI-N: 40.3%), whereas chronic cases only had a neovascular component (PEDCI-S: 0%, PEDCI-N: 30.5%). At 12-month follow-up, 6/7 of acute CSCR group and 6/8 chronic CSCR group had a concomitant PED; PEDCI-S was largest for acute CSCR (53.4%) and PEDCI-N was largest for chronic CSCR (46.7%).

CONCLUSION

We identify a novel biomarker PEDCI to differentiate acute and chronic CSCR with higher PEDCI-S in acute CSCR, and higher PEDCI-N in chronic CSCR.

Apple Vision Pro and why extended reality will revolutionize the future of medicine

Apple unveiled its highly anticipated mixed-reality headset, called the Apple Vision Pro on June 5, 2023. The primary user interface relies on eye tracking, hand, gestures, cameras, and sensors, eliminating the need for physical controllers such as keyboards or touch screens. The refined capabilities of this technology can be utilized for diverse purposes, including but not limited to medical and surgical education, and remote medical consultations. All things considered, virtual reality is a highly promising area for the future of medicine, from improving medical education and vision screening to physical and psychological rehabilitation. We look forward to further innovations in this exciting area for years to come.

Anatomical considerations for reducing ocular emergencies during spaceflight

PURPOSE

The privatization of space travel is opening civilian spaceflight to an unprecedented number of individuals now and in the immediate future. The increase in the number and diversity of space travelers will mean increased exposure to both physiologic and pathologic changes observed during acute and prolonged microgravity.

AIMS

In this paper, we describe the anatomic, physiologic, and pharmacologic factors to consider that impact acute angle-closure glaucoma risk during spaceflight.

CONCLUSIONS

Based on these factors, we elaborate upon areas of medical considerations and provide future recommendations that may aid in reducing the risk of acute angle-closure glaucoma in the next era of spaceflight.

Advanced Visualization Engineering for Vision Disorders: A Clinically Focused Guide to Current Technology and Future Applications

Head-mounted visualization technology, often in the form of virtual, augmented, and mixed reality (VAMR), has revolutionized how visual disorders may be approached clinically. In this manuscript, we review the available literature on VAMR for visual disorders and provide a clinically oriented guide to how VAMR technology has been deployed for visual impairments. The chief areas of clinical investigation with VAMR are divided include (1) vision assessment, (2) vision simulation, and (3) vision rehabilitation. We discuss in-depth the current literature of these areas in VAMR and upcoming/future applications to combat the detrimental impact of visual impairment worldwide.

Prioritizing open science in space medicine: perspectives following the NASA "Transform to Open Science (TOPS)" Curriculum

The National Aeronautics and Space Administration (NASA) has recently made a long-term commitment towards fostering open science. The NASA Transform to Open Science (TOPS) initiative provides recommendations, best practices, and tools related to open science. The principles of open science include the transparent sharing of data, findings, and methods and is designed to accelerate the pace of discovery and foster collaboration. The goal of open science is to allow data, publications, software, and physical samples to be accessible to all, regardless of being a professional or an amateur. In this paper, we summarize several key points open science that were presented as part of NASA's Open Science 101 Module 1 at an in-person training event in Washington, D.C., and include how open science can be beneficial for researchers and society as a whole.

ChatGPT and Beyond: An overview of the growing field of large language models and their use in ophthalmology

ChatGPT, an artificial intelligence (AI) chatbot built on large language models (LLMs), has rapidly gained popularity. The benefits and limitations of this transformative technology have been discussed across various fields, including medicine. The widespread availability of ChatGPT has enabled clinicians to study how these tools could be used for a variety of tasks such as generating differential diagnosis lists, organizing patient notes, and synthesizing literature for scientific research. LLMs have shown promising capabilities in ophthalmology by performing well on the Ophthalmic Knowledge Assessment Program, providing fairly accurate responses to questions about retinal diseases, and in generating differential diagnoses list. There are current limitations to this technology, including the propensity of LLMs to "hallucinate", or confidently generate false information; their potential role in perpetuating biases in medicine; and the challenges in incorporating LLMs into research without allowing "AI-plagiarism" or publication of false information. In this paper, we provide a balanced overview of what LLMs are and introduce some of the LLMs that have been generated in the past few years. We discuss recent literature evaluating the role of these language models in medicine with a focus on ChatGPT. The field of AI is fast-paced, and new applications based on LLMs are being generated rapidly; therefore, it is important for ophthalmologists to be aware of how this technology works and how it may impact patient care. Here, we discuss the benefits, limitations, and future advancements of LLMs in patient care and research.

Barriers to care in neovascular age-related macular degeneration: Current understanding, developments, and future directions

Neovascular age-related macular degeneration is the advanced and irreversible stage of age-related macular degeneration, the leading cause of severe vision loss in older adults. While anti-vascular endothelial growth factor injections have been shown to preserve or improve vision quality in eyes with neovascular age-related macular degeneration, the treatment regimen can be demanding of patients and caregivers, leading to lower rates of adherence. Therefore, it is crucial that disparities and obstacles in neovascular age-related macular degeneration care are identified to improve access to treatment. Review of the current literature revealed 7 major categories of barriers: travel burden, psychological barriers, financial burden and socioeconomic status, treatment regimen, other comorbidities, provider-level barriers, and system-level barriers. We provide an overview of the major barriers to neovascular age-related macular degeneration care that have been reported, as well as gaps in research that need to be investigated further.

Radiation-induced ophthalmic risks of long duration spaceflight: Current investigations and interventions

PURPOSE

As the average duration of space missions increases, astronauts will experience longer periods of exposure to risks of long duration space flight including microgravity and radiation. The risks from long-term exposure to space radiation remains ill-defined. We review the current literature on the possible and known risks of radiation on the eye (including radiation retinopathy) after long duration spaceflight.

METHODS

A PubMed and Google Scholar search of the English language ophthalmic literature was performed from inception to July 11, 2022. The following search terms were utilized independently or in conjunction to build this manuscript: "Radiation Retinopathy", "Spaceflight", "Space Radiation", "Spaceflight Associated Neuro-Ocular Syndrome", "Microgravity", "Hypercapnia", "Radiation Shield", "Cataract", and "SANS". A concise and selective approach of references was conducted in including relevant original studies and reviews.

RESULTS

A total of 65 papers were reviewed and 47 papers were included in our review.

CONCLUSION

We discuss the potential and developing countermeasures to mitigate these radiation risks in preparation for future space exploration. Given the complex nature of space radiation, no single approach will fully reduce the risks of developing radiation maculopathy in long-duration spaceflight. Understanding and appropriately overcoming the risks of space radiation is key to becoming a multi-planetary species.

Retina Oculomics in Neurodegenerative Disease

Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.