Ong Joshua, Waisberg Ethan, Masalkhi Mouayad, Kamran Sharif Amit, Lowry Kemper, Sarker Prithul, Zaman Nasif, Paladugu Phani, Tavakkoli Alireza, Lee Andrew G
Department of Ophthalmology and Visual Sciences, University of Michigan Kellogg Eye Center, Ann Arbor, MI 48105, USA.
University of Cambridge, Cambridge CB2 1TN, UK.
Brain Sci. 2023 Jul 30;13(8):1148. doi: 10.3390/brainsci13081148.
Spaceflight associated neuro-ocular syndrome (SANS) is a unique phenomenon that has been observed in astronauts who have undergone long-duration spaceflight (LDSF). The syndrome is characterized by distinct imaging and clinical findings including optic disc edema, hyperopic refractive shift, posterior globe flattening, and choroidal folds. SANS serves a large barrier to planetary spaceflight such as a mission to Mars and has been noted by the National Aeronautics and Space Administration (NASA) as a high risk based on its likelihood to occur and its severity to human health and mission performance. While it is a large barrier to future spaceflight, the underlying etiology of SANS is not well understood. Current ophthalmic imaging onboard the International Space Station (ISS) has provided further insights into SANS. However, the spaceflight environment presents with unique challenges and limitations to further understand this microgravity-induced phenomenon. The advent of artificial intelligence (AI) has revolutionized the field of imaging in ophthalmology, particularly in detection and monitoring. In this manuscript, we describe the current hypothesized pathophysiology of SANS and the medical diagnostic limitations during spaceflight to further understand its pathogenesis. We then introduce and describe various AI frameworks that can be applied to ophthalmic imaging onboard the ISS to further understand SANS including supervised/unsupervised learning, generative adversarial networks, and transfer learning. We conclude by describing current research in this area to further understand SANS with the goal of enabling deeper insights into SANS and safer spaceflight for future missions.
航天相关神经-眼部综合征（SANS）是一种在经历长期太空飞行（LDSF）的宇航员中观察到的独特现象。该综合征的特征在于独特的影像学和临床发现，包括视盘水肿、远视性屈光偏移、眼球后部扁平化和脉络膜皱褶。SANS对诸如火星任务等行星际太空飞行构成了重大障碍，美国国家航空航天局（NASA）已指出，鉴于其发生可能性及其对人类健康和任务执行的严重性，它具有高风险。虽然它是未来太空飞行的一大障碍，但SANS的潜在病因尚未完全了解。国际空间站（ISS）上目前的眼科成像为深入了解SANS提供了更多见解。然而，太空飞行环境对进一步了解这种微重力诱发的现象带来了独特的挑战和限制。人工智能（AI）的出现彻底改变了眼科成像领域，尤其是在检测和监测方面。在本手稿中，我们描述了SANS目前假设的病理生理学以及太空飞行期间的医学诊断局限性，以进一步了解其发病机制。然后，我们介绍并描述了各种可应用于国际空间站上眼科成像的人工智能框架，以进一步了解SANS，包括监督/无监督学习、生成对抗网络和迁移学习。我们通过描述该领域目前的研究来得出结论，以进一步了解SANS，目标是更深入地洞察SANS，并为未来任务实现更安全的太空飞行。
