From the Department of Neurology, UT Health McGovern Medical School, Houston, TX.
Neurology. 2021 Nov 16;97(20 Suppl 2):S42-S51. doi: 10.1212/WNL.0000000000012794.
This article reviews common imaging modalities used in diagnosis and management of acute stroke. Each modality is discussed individually and clinical scenarios are presented to demonstrate how to apply these modalities in decision-making.
Advances in neuroimaging provide unprecedented accuracy in determining tissue viability as well as tissue fate in acute stroke. In addition, advances in machine learning have led to the creation of decision support tools to improve the interpretability of these studies.
Noncontrast head computed tomography (CT) remains the most commonly used initial imaging tool to evaluate stroke. Its exquisite sensitivity for hemorrhage, rapid acquisition, and widespread availability make it the ideal first study. CT angiography (CTA), the most common follow-up study after noncontrast head CT, is used primarily to identify intracranial large vessel occlusions and cervical carotid or vertebral artery disease. CTA is highly sensitive and can improve accuracy of patient selection for endovascular therapy through delineations of ischemic core. CT perfusion is widely used in endovascular therapy trials and benefits from multiple commercially available machine-learning packages that perform automated postprocessing and interpretation. Magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) can provide valuable insights for outcomes prognostication as well as stroke etiology. Optical coherence tomography (OCT), positron emission tomography (PET), single-photon emission computerized tomography (SPECT) offer similar insights. In the clinical scenarios presented, we demonstrate how multimodal imaging approaches can be tailored to gain mechanistic insights for a range of cerebrovascular pathologies.
本文综述了在急性脑卒中的诊断和治疗中常用的影像学方法。逐个讨论每种方法,并提供临床场景以演示如何在决策中应用这些方法。
神经影像学的进步提供了前所未有的准确性,可确定组织活力和急性脑卒中的组织转归。此外,机器学习的进步导致了决策支持工具的创建,以提高这些研究的可解释性。
非对比头部 CT(NCCT)仍然是评估中风最常用的初始影像学工具。其对出血的极高灵敏度、快速采集和广泛的可用性使其成为理想的首选研究方法。CT 血管造影(CTA)是 NCCT 之后最常见的后续研究,主要用于识别颅内大血管闭塞和颈内或椎动脉疾病。CTA 具有高度的敏感性,并通过对缺血核心的描绘来提高血管内治疗患者选择的准确性。CT 灌注在血管内治疗试验中得到广泛应用,并受益于多个商业化的机器学习软件包,这些软件包可进行自动后处理和解释。磁共振成像(MRI)和磁共振血管造影(MRA)可为预后结果以及中风病因提供有价值的信息。光学相干断层扫描(OCT)、正电子发射断层扫描(PET)、单光子发射计算机断层扫描(SPECT)也提供了类似的见解。在提出的临床场景中,我们展示了如何针对一系列脑血管病理学定制多模态成像方法,以获得机制见解。