Visual biofeedback to reduce head motion during MRI scans

视觉生物反馈可减少 MRI 扫描期间的头部运动

• 批准号: 10019735
• 负责人: Todd William Deckard
• 金额: $ 154.92万
• 依托单位: TURING MEDICAL TECHNOLOGIES INC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-11 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10019735
• 关键词: 10 year old; Adolescent; Adult; Age; Anesthesia procedures; Award; Back; Behavioral; Biofeedback; Brain; Brain imaging; Child; Childhood; Client satisfaction; Clinical; Clinical Research; Code; Cognitive; Color; Computer software; Data; Delirium; Diagnosis; Diagnostic; Elderly; Ensure; Face; Feedback; Feeds; Functional Magnetic Resonance Imaging; Funding; Goals; Grant; Head; Human; Image; Imaging technology; Impaired cognition; Institution; Investigation; Kinetics; Left; Legal patent; Longevity; MRI Scans; Magnetic Resonance Imaging; Measurement; Measures; Medical; Methods; Monitor; Morphologic artifacts; Motion; Movement; National Institute of Mental Health; Output; Participant; Patients; Phase; Physicians; Predisposition; Questionnaires; Radiation; Randomized; Recovery; Research; Research Subjects; Resolution; Rewards; Risk; Robin bird; Running; Safety; Sampling; Scanning; Sedation procedure; Seeds; Small Business Technology Transfer Research; System; Technology; Testing; Time; Training; Translating; United States; Visual; Work; awake; base; biobehavior; cognitive development; cohort; combat; connectome; cost; cost estimate; data quality; effectiveness evaluation; experience; falls; functional MRI scan; high resolution imaging; improved; neuroimaging; neuropsychiatric disorder; non-invasive monitor; novel; prevent; product development; prototype; research study; sedative; software development; tool; visual feedback; volunteer; wasting

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.

项目摘要/摘要 这项STTR应用的目标是提供一种大脑MRI技术， 从我们的Framewise集成实时MRI监测（FIRMM）到MRI扫描的测量 参与者通过行为训练减少头部运动。因为核磁共振扫描会产生高- 分辨率的图像，并且不会使患者暴露于辐射，它已成为一种非常有价值的诊断方法。 这是一种工具，特别是对大脑进行成像。去年，仅在美国，就有超过800万的大脑 核磁共振成像，估计耗资200 - 300亿美元。不幸的是，脑部核磁共振成像受到头部运动的限制， 在扫描过程中，可能导致所得到的图像是次优的或甚至不可用。据估计， 脑部MRI被运动破坏，每年浪费20 - 40亿美元。目前，有两种主要战略 为了对抗头部运动：重复扫描和麻醉，这两种方法都是不够的。重复扫描， 包括获取额外的图像（以确保获取足够的可用图像）， 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， 给可能移动的患者（如幼儿），存在严重的安全风险， 有时不必要地施用（即，患者可以在没有麻醉的情况下保持静止）。麻醉永远不会 功能性磁共振成像（fMRI）的一种选择，它要求参与者保持清醒。 基于软件的FIRMM-生物反馈解决方案在这项授权中提出使用MR图像（因为它们正在 收集）以在MRI扫描期间计算患者的头部运动的真实的时间。真实的时间的可用性 运动信息将使更多的知情麻醉使用，并减少过度扫描，使这些 方法更安全、更高效。有了真实的时间运动信息，扫描操作员将准确地知道 已经采集了多少可用图像，防止采集过多或过少的额外图像。 此外，为医生提供关于患者运动的定量信息将允许他们做出评估。 关于麻醉的知情决定，防止不必要的镇静。 所提出的解决方案侧重于一种全新的生物行为方法，用于对抗头部运动： 生物反馈该技术可以将头部运动信息转化为与年龄相适应的视觉信息， 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童和成人患者保持更安静，提高图像质量。的 拟议的研究重点是为FIRMM生物反馈（第一阶段）提供概念验证， 验证FIRMM-生物反馈的产品版本（第二阶段）。FIRMM生物反馈技术提供了 为患者和研究对象提供真实的头部运动信息，目标是使MR扫描更安全， 更快、更愉快、更便宜。