Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
Department of Neurology, Upstate Medical University, Syracuse, New York, USA.
J Neuroimaging. 2022 Sep;32(5):798-807. doi: 10.1111/jon.13003. Epub 2022 May 14.
Mechanical thrombectomy (MT) for ischemic stroke due to large vessel occlusion is standard of care. Evidence-based guidelines on eligibility for MT have been outlined and evidence to extend the treatment benefit to more patients, particularly those at the extreme ends of a stroke clinical severity spectrum, is currently awaited. As patient selection continues to be explored, there is growing focus on procedure selection including the tools and techniques of thrombectomy and associated outcomes. Artificial intelligence (AI) has been instrumental in the area of patient selection for MT with a role in diagnosis and delivery of acute stroke care. Machine learning algorithms have been developed to detect cerebral ischemia and early infarct core, presence of large vessel occlusion, and perfusion deficit in acute ischemic stroke. Several available deep learning AI applications provide ready visualization and interpretation of cervical and cerebral arteries. Further enhancement of AI techniques to potentially include automated vessel probe tools in suspected large vessel occlusions is proposed. Value of AI may be extended to assist in procedure selection including both the tools and technique of thrombectomy. Delivering personalized medicine is the wave of the future and tailoring the MT treatment to a stroke patient is in line with this trend.
机械取栓（MT）治疗大动脉闭塞引起的缺血性脑卒中是标准的治疗方法。已经制定了基于循证的 MT 适应证指南，目前正在等待进一步的证据将治疗获益扩展至更多患者，特别是那些处于脑卒中临床严重程度谱两端的患者。随着患者选择的不断探索，人们越来越关注手术选择，包括取栓的工具和技术以及相关结果。人工智能（AI）在 MT 患者选择方面发挥了重要作用，在诊断和提供急性脑卒中治疗方面都有应用。已经开发了机器学习算法来检测脑缺血和早期梗死核心、大血管闭塞和急性缺血性脑卒中的灌注缺损。一些现有的深度学习 AI 应用程序可提供颈椎和脑动脉的直观可视化和解读。建议进一步增强 AI 技术，以潜在地包括在疑似大血管闭塞中自动使用血管探测工具。AI 的价值可能会扩展到辅助手术选择，包括取栓的工具和技术。提供个性化药物治疗是未来的趋势，为脑卒中患者量身定制 MT 治疗符合这一趋势。
