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: 9908756
• 负责人: Todd William Deckard
• 金额: $ 96.61万
• 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 2020-06-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9908756
• 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; Data Quality; Delirium; Diagnosis; Diagnostic; Effectiveness; 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; Structure; System; Technology; Testing; Time; Training; Translating; United States; Visual; Work; awake; base; biobehavior; cognitive development; cohort; combat; connectome; cost; experience; falls; feeding; functional MRI scan; high resolution imaging; improved; neuroimaging; neuropsychiatric disorder; non-invasive monitor; novel; off-patent; 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 STR应用程序的目标是提供脑部MRI技术，以使头运动反馈 从我们的框架集成的实时MRI监测（FIRMM）到MRI扫描得出的测量值 为了通过行为训练减少头部运动。 分辨率图像，不会使患者暴露于辐射 工具，特别是用于成像大脑。 MRI不幸的是，大脑MRI的成本估计为20亿美元。 在扫描过程中，可以导致产生的图像次优甚至不可用。 大脑MRI被运动毁了，每年浪费2-4亿美元。 对抗头部运动：重复扫描和麻醉，这两者都不足够。 包括获取额外的图像 时间和成本，可能会导致太少的可用图像或不必要的额外图像。 给予可能移动的患者（例如幼儿） 有时会施加不必要的（即，患者可以保持静止不动，而无需麻醉） 功能性MRI（fMRI）的选项，它要求参与者清醒。 该赠款中基于软件的Firmm-Biofeack Backback解决方案使用MR图像（因为它们正在 收集）在MRI扫描中实时计算患者的头部运动。 运动信息信息将使更多明智的麻醉使用并减少多余的扫描，从而使这些 方法更安全，效率更高。 获取了多少个可用图像） 此外，向医生提供有关动作的定量信息将使他们能够做一个 关于麻醉的明智决定，防止不必要的煽动。 支撑的解决方案着重于一种打击头运动的新型生物行为方法：受试者 生物反馈。 扫描参与者的生物反馈。 生物反馈技术可帮助小儿患者保持静止，从而提高图像质量 支撑研究的重点是Firmm-Biofeepback（I阶段）和建筑物的概念证明 验证firmm-biofeatback的产品版本（第二阶段）。 具有实时头部运动信息的患者和研究对象，目的是使MR扫描更安全， 更快，更有趣，更便宜。