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A Framework to Design 3D Quantitative Magnetic Resonance Fingerprinting (MRF) Scans and Reduce Patient Anxiety

A Framework to Design 3D Quantitative Magnetic Resonance Fingerprinting (MRF) Scans and Reduce Patient Anxiety
设计 3D 定量磁共振指纹 (MRF) 扫描并减少患者焦虑的框架
批准号:
9768464
负责人:
Dan Ma
金额:
$20.0万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2021-05-31

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中文摘要
翻译
摘要 MRI扫描过程中的噪音是导致患者焦虑的主要原因,但这种噪音的来源主要是快速- 切换场,也是生成图像的重要组成部分。当前降低声学噪声的方法 扫描几乎完全依赖于减慢切换场,这在灵活性和声音方面都有限制 降低效果,并导致扫描效率降低。通过利用提供的新自由度 磁共振指纹(MRF),我们将开发一个系统框架来1)通过以下方式减少患者的焦虑 将扫描仪发出的声音更改为音乐,这允许使用快速切换场,同时提供 令人愉悦的声音;2)同时提供临床扫描所需的所有组织属性的定量信息 3)保持与传统(噪声)扫描相同的高效率。为此,我们首先将制定一种 声学模型,用于描述扫描仪系统的声学响应。第二,我们将生成一个框架 评估和优化任何声音输入的声音响应、图像质量和扫描时间。这一框架将 可用于优化具有1mm3各向同性分辨率和全脑覆盖范围的3D MRF扫描。最后,我们会 在患者研究中验证该框架,以评估患者的焦虑、图像质量、扫描效率和成功率 招募之前拒绝接受核磁共振扫描的患者。这些研究产生的结果可能会改善 任何接受磁共振扫描的患者的结果:定量扫描将提供更明确的信息 以定量地图的形式描述病变,悦耳的声音将显著改变患者的 在磁共振扫描过程中的经验,这可能会导致更好的遵从性和减少运动问题,并可能崩溃 在没有镇静的情况下,阻止儿童和焦虑的成年人接受核磁共振成像的障碍。
英文摘要
Abstract Loud noise during MRI scans is the leading cause of patients' anxiety, but the origin of this loud noise, mainly fast- switching fields, is also an essential component to generate images. Current methods that reduce acoustic noise during scans rely almost solely on slowing down the switching field, which have limitations in both flexibility and sound reduction effect, and result in reduced scan efficiency. By taking advantages of the new degrees of freedom provided by Magnetic Resonance Fingerprinting (MRF), we will develop a systematic framework to 1) reduce patients' anxiety by changing the sound emitted from the scanner to music, which allows the use of fast-switching fields while providing pleasing sound; 2) simultaneously provide quantitative information on all tissue properties needed for a clinical scan and 3) maintain the same high efficiency as compared to conventional (noisy) scans. To this end, first, we will develop an acoustic model to characterize the acoustic response of the scanner system. Second, we will generate the framework that evaluates and optimizes the acoustic response, image quality and scan time from any acoustic input. This framework will be used to optimize 3D MRF scans with 1 mm3 isotropic resolution and with whole brain coverage. Finally, we will validate the framework on a patient study to assess patients' anxiety, image quality, scan efficiency and success rate of recruiting patients who previously refused to have an MRI scan. The results generated in these studies could improve the outcomes of any patients who undergo an MR scan: the quantitative scans will provide more definitive information for lesion characterization in the form of quantitative maps, and the pleasing sound will significantly change patients' experience during the MR scans, which could lead to greater compliance and reduced motion issue, and could break down the barriers that keep children and anxious adults from receiving MRIs without sedation.
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