Visual biofeedback to reduce head motion during MRI scans
Visual biofeedback to reduce head motion during MRI scans
批准号:
10442332
负责人:
Ken Bruener
金额:
$30.0万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-11 至 2023-05-31
关键词:
AdultAgeAnesthesia proceduresAwardBackBehavioralBiofeedbackBrainBrain imagingChildChildhoodClient satisfactionClinical ResearchComputer softwareDiagnosticEnsureFeedbackFeedsFunctional Magnetic Resonance ImagingGoalsGrantHeadImageImaging technologyMRI ScansMagnetic Resonance ImagingMeasurementMethodsMonitorMotionParentsParticipantPatientsPhasePhysiciansRadiationResearchResearch SubjectsResolutionRiskSafetyScanningSedation procedureTechnologyTimeTrainingTranslatingUnited StatesVisualawakebasebiobehaviorcombatcostcost estimatehigh resolution imagingimprovednon-invasive monitorpreventsoftware developmenttoolwasting
中文摘要
项目摘要/家长奖摘要(不变)
这个应用程序的目标是提供一种反馈头部运动测量的脑MRI技术
从我们的帧集成实时MRI监控(FIRMM)派生到MRI扫描参与者的顺序
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
不会使患者暴露在辐射中,它已成为一种非常有价值的诊断工具,特别是对
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,花费了
估计为200-300亿美元。不幸的是,脑部核磁共振成像受到扫描过程中头部运动可能
导致生成的图像不是最优的,甚至无法使用。据估计,20%的脑部核磁共振成像都被毁了
通过行动,每年浪费20-40亿美元。目前,有两种主要的策略来对抗Head
运动:重复扫描和麻醉,这两种方法都不充分。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),增加扫描时间和成本,以及
可能会导致可用图像太少或不必要的额外图像。麻醉,这是给符合以下条件的患者
可能会移动(如幼儿),存在严重的安全风险,有时会被注射
不必要的(即患者可以在没有麻醉的情况下保持不动)。麻醉从来不是功能性的选择
磁共振成像(FMRI),这需要参与者保持清醒。基于软件的FIRMM-生物反馈解决方案
在这项拨款中建议使用磁共振图像(当它们被收集时)来实时计算患者的头部运动
核磁共振扫描期间的时间。实时运动信息的可获得性将使麻醉更知情
使用并减少过多的扫描,使这些方法更安全、更高效。配备实时运动功能
信息,扫描操作员将确切地知道已获取了多少可用图像,从而防止
获取过多或过少的额外图像。此外,为医生提供量化信息
关于病人的行动将使他们能够做出关于麻醉的明智决定,防止
不必要的镇静剂。建议的解决方案侧重于一种全新的生物行为方法
对抗头部运动:受试者生物反馈。该技术可以将头部运动信息转化为
为扫描参与者提供适合年龄的视觉生物反馈。通过向患者和研究提供反馈
受试者,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。拟议的研究重点是为FIRMM提供概念验证-
生物反馈(第一阶段)以及建立和验证FIRMM的产品版本--生物反馈(第二阶段)。这个
FIRMM-生物反馈技术为患者和研究对象提供实时的头部运动
信息,目标是使磁共振扫描更安全、更快、更愉快、更便宜。
英文摘要
Project Abstract/Summary of Parent Award (no change)
The goal of this 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.
期刊论文(0)
专著(0)
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会议论文
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批准号:10697965
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项目类别:
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资助金额:$106.28万
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财政年份:2023
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依托单位:
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财政年份:2022
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负责人:Ken Bruener
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依托单位:
Commercialization readiness of visual biofeedback to reduce head motion during MRI scans
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批准号:10382713
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项目类别:
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资助金额:$113.69万
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财政年份:2021
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资助金额:$113.69万
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财政年份:2021
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依托单位:
Visual biofeedback to reduce head motion during MRI scans
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批准号:10199977
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项目类别:
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依托单位:
Visual biofeedback to reduce head motion during MRI scans
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批准号:10437644
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项目类别:
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资助金额:$182.53万
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财政年份:2019
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负责人:Ken Bruener
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依托单位:
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