Williamson Jordan N, Peng Rita Huan-Ting, Sung Joohwan, Rajabtabar Darvish Mahmood, Chen Xiaoxi, Ali Mehreen, Li Sheng, Yang Yuan
Grainger College of Engineering, Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States of America.
Carle Foundation Hospital, Stephenson Family Clinical Research Institute, Clinical Imaging Research Center, Urbana, IL, United States of America.
Prog Biomed Eng (Bristol). 2025 Sep 11;7(4). doi: 10.1088/2516-1091/adfeaa.
Stroke is a leading cause of adult disability worldwide, with approximately 101 million survivors globally. Over 60% of these individuals live with from long-term, often lifelong, movement impairments that significantly hinder their ability to perform essential daily activities and maintain independence. Post-stroke movement disabilities are highly associated with structural and functional changes in motor descending pathways, particularly the corticospinal tract and other indirect motor pathways via the brainstem. For decades, neuroengineers have been working to quantitively evaluate the post-stroke changes of motor descending pathways, aiming to establish a precision prognosis and tailoring treatments to post-stroke motor impairment. However, a clear and practicable technique has not yet been established as a breakthrough to change the standard of care for current clinical practice. In this review, we outline recent progress in neuroimaging, neuromodulation, and electrophysiological approaches for assessing structural and functional changes of motor descending pathways in stroke. We also discuss their limitations and challenges, arguing the need of artificial intelligence and large multi-modal data registry for a groundbreaking advance to this important topic.
中风是全球成年人残疾的主要原因，全球约有1.01亿幸存者。其中超过60%的人长期甚至终身存在运动障碍，这严重阻碍了他们进行基本日常活动和保持独立的能力。中风后的运动障碍与运动下行通路的结构和功能变化高度相关，特别是皮质脊髓束和通过脑干的其他间接运动通路。几十年来，神经工程师一直致力于定量评估中风后运动下行通路的变化，旨在建立精确的预后并针对中风后的运动障碍量身定制治疗方案。然而，尚未建立一种明确且可行的技术作为改变当前临床实践护理标准的突破。在这篇综述中，我们概述了神经影像学、神经调节和电生理方法在评估中风后运动下行通路结构和功能变化方面的最新进展。我们还讨论了它们的局限性和挑战，认为需要人工智能和大型多模态数据登记库才能在这个重要课题上取得突破性进展。
