Portable, Low Field Brain Magnetic Resonance Imaging (MRI) for Acute Stroke

摘要 神经影像学是脑损伤患者护理的基石。高磁场磁铁和访问 成像解释已经阻止了磁共振成像（MRI）成为一种普遍的 可用的工具。我们的团队已经证明了在便携式设备上获取临床有用图像的可行性， 低场核磁共振在本提案中，我们将验证便携式移动的MRI的使用和成功部署 进入急性中风状态。在目前的实践中，所有的病人，包括那些危重病人，必须 运输到集中的、受控访问的环境，以在单个时间点获得MRI， 不可接近的范例。我们的假设是，一个高度便携式，低场MRI可以部署到几乎任何 设置在一个提供实时自动神经成像分析的平台上。该解决方案的开发 结合工程和技术创新（低场MRI），方法创新 （成像重建技术，自动诊断的机器学习方法）和概念 创新（改变临床工作流程，以适应能够即时护理的非侵入性方法， 连续MRI）。我们的主要理由是，我们可以扩大现有的治疗，促进决策， 当我们将MRI的可用性重新定位在一个近乎普遍的 规模基本的见解是，低场，便携式MRI解决方案，包括先进的成像方法， 质量、重建和解释，可以使成像实际上可用于任何患者。我们将带来 MRI技术和解释到个别病人的床边，并在这样做创造了一个平台， 磁共振成像和分析在前所未有的规模。因为仪器便宜，没有 冷却要求，并在标准15 A 120 V电源上运行，项目成功将 使缺血性和出血性卒中的诊断MR成像大众化。在这份提案中，我们将开发， 量化和验证过渡到临床护理所需的确定性措施。行程已 仔细选择，因为大量的公共卫生负担和现有的治疗方案， 可用，但由于急性神经成像的要求，目前受到限制。我们已经开发出一种 高度协作和多学科框架，与低场MRI，机器学习， 中风、多中心研究、临床和转化研究。在我们的团队中， 立即将这一令人兴奋的解决方案应用于各种新颖的环境（例如救护车、低/中等收入 国家）。我们的行业合作伙伴Hyperfine是世界上第一家开发真正便携式MRI的公司 在过去的三年里，与我们的学术团队合作。随着我们未来的发展， 排除故障，并微调我们的解决方案在两个领先的机构（耶鲁大学和麻省理工学院），我们已经组装了一个 广泛的科学团队，结合技术，临床工作流程和卫生系统因素，使我们的 该解决方案可随时部署在任何临床环境中，以改善整个人类健康领域的患者护理。

Abstract Neuroimaging is a cornerstone of patient care for patients with brain injury. High field magnets and access to imaging interpretation have prevented magnetic resonance imaging (MRI) from becoming a universally available tool. Our group has demonstrated the feasibility of acquiring clinically useful images on a portable, low-field MRI. In this proposal, we will validate the use and successful deployment of a portable, mobile MRI into the acute stroke setting. In current practice, all patients, including those that are critically ill, must be transported to a centralized, controlled-access environment to obtain an MRI at a single time point, in a highly inaccessible paradigm. Our hypothesis is that a highly portable, low-field MRI can be deployed into nearly any setting on a platform that provides real-time, automated neuroimaging analysis. Development of this solution incorporates engineering and technological innovation (low field MRI), methodological innovation (imaging reconstruction techniques, machine learning approaches to automated diagnosis), and conceptual innovation (changing clinical workflow to accommodate a non-invasive method capable of point-of-care and serial MRI). Our key rationale is that we can expand already available treatments, facilitate decision making, and inform new approaches to patient care when we reposition the availability of MRI on a near-universal scale. The fundamental insight is that a low field, portable MRI solution, including advanced methods in image quality, reconstruction, and interpretation, can make imaging available to virtually any patient. We will bring MRI technology and interpretation to an individual patient's bedside and in doing so create a platform for MR imaging and analysis on an unprecedented scale. Because the instrument is inexpensive, does not have cooling requirements and operates on a standard 15A 120V electrical source, project success would democratize diagnostic MR imaging for ischemic and hemorrhagic stroke. In this proposal, we will develop, quantify, and validate the measure of certainty required for transition into clinical care. Stroke has been carefully chosen because of the substantial public health burden and existing treatment options that are available but currently limited because of the requirement for acute neuroimaging. We have developed a highly collaborative and multidisciplinary framework, with leading experts in low field MRI, machine learning, stroke, multicenter studies, clinical and translational research. Embedded as well in our team is the expertise to immediately take this exciting solution to a variety of novel settings (e.g. ambulance, low/middle income countries). Our industry partner, Hyperfine, is the first company in the world to develop a truly portable MRI solution, in collaboration with our academic team over the last three years. As we prospectively develop, troubleshoot, and fine-tune our solution at two leading institutions (Yale and MGH), we have assembled a broad scientific team to incorporate technological, clinical workflow, and health systems factors so that our solution is ready to deploy in any clinical setting to improve patient care across human health.