Azzam Mohamed, Xu Ziyang, Liu Ruobing, Li Lie, Meng Soh Kah, Challagundla Kishore B, Wan Shibiao, Wang Jieqiong
Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, United States.
Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt.
Brief Funct Genomics. 2025 Jan 15;24. doi: 10.1093/bfgp/elae042.
The study of brain age has emerged over the past decade, aiming to estimate a person's age based on brain imaging scans. Ideally, predicted brain age should match chronological age in healthy individuals. However, brain structure and function change in the presence of brain-related diseases. Consequently, brain age also changes in affected individuals, making the brain age gap (BAG)-the difference between brain age and chronological age-a potential biomarker for brain health, early screening, and identifying age-related cognitive decline and disorders. With the recent successes of artificial intelligence in healthcare, it is essential to track the latest advancements and highlight promising directions. This review paper presents recent machine learning techniques used in brain age estimation (BAE) studies. Typically, BAE models involve developing a machine learning regression model to capture age-related variations in brain structure from imaging scans of healthy individuals and automatically predict brain age for new subjects. The process also involves estimating BAG as a measure of brain health. While we discuss recent clinical applications of BAE methods, we also review studies of biological age that can be integrated into BAE research. Finally, we point out the current limitations of BAE's studies.
脑龄研究在过去十年中兴起，旨在根据脑部影像扫描估计一个人的年龄。理想情况下，在健康个体中，预测的脑龄应与实际年龄相符。然而，在患有脑部相关疾病时，脑结构和功能会发生变化。因此，受影响个体的脑龄也会改变，使得脑龄差距（BAG）——脑龄与实际年龄之间的差异——成为脑健康、早期筛查以及识别与年龄相关的认知衰退和疾病的潜在生物标志物。随着人工智能在医疗保健领域的近期成功，追踪最新进展并突出有前景的方向至关重要。这篇综述文章介绍了脑龄估计（BAE）研究中使用的近期机器学习技术。通常，BAE模型涉及开发一个机器学习回归模型，以从健康个体的影像扫描中捕捉与年龄相关的脑结构变化，并自动预测新受试者的脑龄。该过程还包括估计BAG作为脑健康的一种度量。在讨论BAE方法近期临床应用的同时，我们还回顾了可整合到BAE研究中的生物年龄研究。最后，我们指出了BAE研究当前的局限性。
