Solving the MRI motion problem with Framewise Integrated Real-Time MRI Monitoring (FIRMM) software

项目摘要/摘要 此SBIR/STTR应用程序的目标是提供一种准确且非侵入性测量的技术 患者在结构磁共振成像(MRI)扫描期间的头部运动(框架集成 核磁共振实时监测-结构[FIRMM-S])。因为结构性核磁共振扫描可以产生高分辨率 而且不会使患者暴露在辐射中，它已经成为一种非常有价值的诊断工具， 尤其是对大脑进行成像。去年，仅在美国，就有超过800万例脑部核磁共振检查， 估计耗资200-300亿美元。不幸的是，大脑核磁共振成像受到以下事实的限制：在 扫描可能会导致生成的图像不太理想，甚至无法使用。据估计占所有大脑的20% 核磁共振成像被运动毁了，每年浪费20-40亿美元。目前，有两种主要的战略来 战斗头部运动：重复扫描和麻醉，这两种方法都不够充分。重复扫描，这将 包括获取额外的图像(以确保获取足够的可用图像)，从而增加扫描时间 和成本，并且可能导致可用图像太少或不必要的额外图像。麻醉，这是用来 可能会移动的病人(如幼儿)，存在严重的安全风险，有时 不必要的给药(即患者可以在没有麻醉的情况下保持不动)。 本赠款中建议的基于软件的FIRMM-S解决方案使用MR图像(因为它们正在被收集)来 在核磁共振扫描过程中实时计算患者的头部运动。实时运动的可用性 信息将使麻醉使用更知情，并减少过度扫描，使这些方法 更安全、更高效。有了实时运动信息，扫描操作员将确切知道 已获取可用的图像，防止获取过多或过少的额外图像。 此外，向医生提供有关患者运动的量化信息将使他们能够做出 关于麻醉的知情决定，防止不必要的镇静。 提议的解决方案还包含一种对抗头部运动的全新方法：患者生物反馈。 这项技术可以将头部运动信息转换为适合年龄的视觉生物反馈 有耐心的。通过向患者提供反馈，这项技术帮助儿科和成人患者保持更多 仍然，提高图像质量。拟议的研究重点是为FIRMM-S提供概念验证 (第一阶段)以及建立和验证FIRMM-S的临床就绪版本(第二阶段)。FIRMM-S装置 为扫描操作员、医生和患者提供实时运动信息，目标是使 MR扫描更安全、更快、成本更低。

Project Abstract/Summary The goal of this SBIR/STTR application is to deliver a technology that accurately and non-invasively measures a patient’s head motion during a structural magnetic resonance imaging (MRI) scan (Framewise Integrated Real-Time MRI Monitoring -structural [FIRMM-s]). Because structural MRI scanning produces high-resolution images and does not expose patients to radiation, it has become an immensely valuable diagnostic tool, particularly for imaging the brain. Last year, in the United States alone, there were over 8 million brain MRIs, costing an estimated $20-30 billion. Unfortunately, brain MRIs are limited by the fact that head motion during the scan can cause the resulting images to be suboptimal or even unusable. An estimated 20% of all brain MRIs are ruined by motion, wasting $2-4 billion annually. Currently, there are two predominant strategies to combat head motion: repeat scanning and anesthesia, both of which are inadequate. Repeat scanning, which consists of acquiring extra images (to ensure enough usable ones were acquired), increases scanning time and cost, and can result in too few usable images or unnecessary, extra images. Anesthesia, which is given to patients who are likely to move (such as young children), presents a serious safety risk and is sometimes administered unnecessarily (i.e. the patient could hold still without anesthesia). The software-based FIRMM-s solution proposed in this grant uses MR images (as they are being collected) to compute a patient’s head motion in real time during an MRI scan. The availability of real time motion information will enable more informed anesthesia use and reduce excess scanning, making these methods safer and more efficient. Armed with real time motion information, scan operators will know exactly how many usable images have been acquired, preventing the acquisition of too many or too few extra images. Additionally, providing physicians with quantitative information about patient motion will allow them to make an informed decision regarding anesthesia, preventing unnecessary sedation. The proposed solution also contains an entirely new method for combating head motion: patient biofeedback. The technology can translate the head motion information into age-appropriate, visual biofeedback for the patient. By providing feedback to patients, the technology helps both pediatric and adult patients remain more still, improving image quality. The proposed research focuses on delivering proof-of-concept for FIRMM-s (Phase I) and building and validating a clinical-ready version of FIRMM-s (Phase II). The FIRMM-s device provides scan operators, physicians, and patients with real time motion information, with the goal of making MR scans safer, faster, and less expensive.