Sensing intracranial bioimpedance through anatomic windows for classifying stroke type

摘要 根据疾病控制中心(CDC)在参考文献中的说法：时间的损失就是大脑的损失--每一分钟都很重要 为了中风。中风是美国第五大死因，位居世界第二，将使美国损失惨重。 到2030年，每年增加1830亿美元。每年仅在美国就有80万人中风，而且 在美国，中风是导致严重、长期残疾的主要原因。有两个 中风的主要类型：缺血性和出血性。缺血性中风涉及血液或脂肪斑块阻塞 脑血管出血的定义是血管破裂或脑出血。每种类型都需要 显著不同的治疗方法，以及错误类型的治疗可能会产生致命的后果。这使得 中风类型识别对接受治疗至关重要。因此，神经监测和及时干预是 是急性中风恢复的关键，但目前还没有能够检测到复发中风的床边监护仪， 发病时存在出血性转化和/或进行性卒中。今天的护理标准依赖于监测 一般病人的生命体征和定期CT/MRI扫描以成像颅内状态；不幸的是，大量的时间 两次扫描之间的时间间隔延迟了可能检测到的条件的重大后果变化。伴随着每一分钟 干预前的时间相当于永久性残疾几率的增加，实时监测不仅可以节省 生命，但拯救这一弱势群体的生活质量。我们建议开发一种小尺寸的，关于- 一种能够标测颅内空间并区分缺血性和出血性中风的场景装置。 在这个计划中，我们将在考虑到翻译的情况下，采取重要的一步来开发这项技术 并在对接受监测的高危患者进行的临床前人体研究中证明了可行性 在因中风入院后。我们将开发一种用于颅内监测的非侵入性传感方法(AIM I)，这是中风使用的一项关键创新，并在接受监测的患者队列中验证这种感知能力 卒中后(AIM II)。通过评估我们的非侵入性颅内监护新方法的可行性 在严格控制的患者队列中(中风后监测)，我们可以验证我们检测1)存在的能力 2)辨证中风类型。这项技术不仅有可能作为监护仪辅助临床 用于检测中风复发或病情恶化的高危患者中的中风发作，也用于现场检测 用于移动笔画类型识别。因为该系统具有体积小、无创、相对 价格低廉(颅内生物阻抗监测系统为1万美元)，并有可能区分 中风类型第一次接触患者时，这项技术有可能很容易转化为和 被诊所接受，用于诊断或跟踪中风患者。我们预计到 该计划结束后，我们将能够优化和微型化我们的技术，并进行更大规模的 人体研究，以证明我们的颅内阻抗监测技术的有效性。

ABSTRACT “Time lost is brain lost - every minute counts” – according to the Center for Disease Control (CDC) in reference to strokes. Stroke is the 5th leading cause of death in the United States, 2nd in the world and will cost the U.S. $183 billion annually by 2030. Every year 800,000 people will suffer a stroke in the U.S. alone and this high incidence contributes to stroke being a leading cause of serious, long-term disability in the US. There are two primary types of stroke: ischemic and hemorrhagic. Ischemic stroke involves blood or fatty plaque blocking a vessel of the brain while hemorrhagic is defined by a vessel rupture or brain bleed. Each type requires significantly different treatments, and treatment of the wrong type could have lethal consequences. This makes stroke type identification crucial to receiving treatment. Thus, neurologic monitoring and timely intervention are key for acute stroke recovery, yet currently no bedside monitor capable of detecting a recurrent stroke, hemorrhagic transformation and/or evolving stroke at onset exists. Today’s standard-of-care relies on monitoring general patient vitals and periodic CT/MRI scans to image the intracranial state; unfortunately, the large time periods between scans delays possible detection of a high-consequence change in condition. With every minute of pre-intervention time equating to an increase in lasting disability odds, a real-time monitor could not only save lives, but save the quality of life for this vulnerable population. We propose to develop a small form-factor, on- scene device capable of mapping the intracranial space and differentiating ischemic from hemorrhagic stroke. During this program we will take the significant step of developing this technology with translation in mind and demonstrating proof of feasibility in a pre-clinical human study of high-risk patients undergoing monitoring after being admitted for stroke. We will develop a non-invasive sensing approach to intracranial monitoring (Aim I), a key innovation for stroke use, and validate this sensing ability in a cohort of patients being monitored following stroke (Aim II). By assessing the feasibility of our novel approach to non-invasive intracranial monitoring in a tightly controlled patient cohort (post-stroke monitoring), we can validate our ability to 1) detect the presence of stroke and 2) differentiate stroke type. This technology has the potential to not only aid in the clinic as a monitor for detecting stroke onset within patients at high-risk for recurrent stroke or worsening status, but also in the field for mobile stroke type discrimination. Because this system has a small form-factor, is non-invasive, is relatively inexpensive (<$10k for an intracranial bioimpedance monitoring system), and is potentially able to discriminate stroke type at first contact with the patient, this technology has the potential of being easily translated to and accepted by the clinic for the benefit of diagnosing or tracking patients experiencing a stroke. We expect that by the end of this program we will be in a position to optimize and miniaturize our technology and to conduct a larger human study to demonstrate efficacy of our intracranial impedance monitoring technique.