Visual biofeedback to reduce head motion during MRI scans

项目摘要/摘要 这个STTR应用程序的目标是提供一种反馈头部运动的脑MRI技术 从我们的帧集成实时MRI监测(FIRMM)到MRI扫描的测量结果 参与者通过行为训练来减少头部运动。因为核磁共振扫描会产生高- 图像分辨率高，不会使患者暴露在辐射中，已成为极具价值的诊断工具 工具，尤其是用于对大脑进行成像的工具。去年，仅在美国，就有超过800万个大脑 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头部运动的限制 在扫描过程中，可能会导致生成的图像不太理想，甚至无法使用。估计有20%的人 大脑核磁共振成像被运动破坏了，每年浪费20-40亿美元。目前，主要有两种策略 对抗头部运动：重复扫描和麻醉，这两种方法都不够充分。重复扫描， 这包括获取额外的图像(以确保获取足够的可用图像)，增加扫描 时间和成本，并可能导致可用图像太少或不必要的额外图像。麻醉，这是 给可能移动的患者(如幼儿)，具有严重的安全风险，并 有时不必要地给药(即患者可以在没有麻醉的情况下保持不动)。麻醉永远不会 功能磁共振成像(FMRI)的一种选择，它要求参与者处于清醒状态。 本赠款中建议的基于软件的FIRMM-生物反馈解决方案使用MR图像(因为它们是 收集)以在MRI扫描期间实时计算患者的头部运动。实时的可用性 运动信息将使麻醉使用更加知情，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，扫描操作员将准确地知道 已获取多少可用图像，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。 提出的解决方案聚焦于一种全新的对抗头部运动的生物行为方法：受试者 生物反馈法。这项技术可以将头部运动信息转化为适合年龄的视觉信息 扫描参与者的生物反馈。通过向患者和研究对象提供反馈，FIRMM- 生物反馈技术帮助儿科和成人患者保持更多静止，提高图像质量。这个 拟议的研究重点是交付FIRMM的概念验证--生物反馈(第一阶段)和建立和 验证FIRMM的产品版本--生物反馈(第二阶段)。FIRMM-生物反馈技术提供 患者和研究对象拥有实时的头部运动信息，目的是使磁共振扫描更安全， 更快，更享受，更便宜。

Project Abstract/Summary The goal of this STTR application is to deliver a brain MRI technology that feeds back head motion measurements derived from our Framewise Integrated Real-Time MRI Monitoring (FIRMM) to MRI scan participants in order to reduce head motion via behavioral training. Because 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). Anesthesia is never an option for functional MRI (fMRI), which requires participants to be awake. The software-based FIRMM-biofeedback 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 focuses on a completely new biobehavioral method for combating head motion: subject biofeedback. The technology can translate the head motion information into age-appropriate, visual biofeedback for the scan participant. By providing feedback to patients and research subjects, the FIRMM- biofeedback technology helps both pediatric and adult patients remain more still, improving image quality. The proposed research focuses on delivering proof-of-concept for FIRMM-biofeedback (Phase I) and building and validating a product version of FIRMM-biofeedback (Phase II). The FIRMM-biofeedback technology provides patients and research subjects with real time head motion information, with the goal of making MR scans safer, faster, more enjoyable and less expensive.