FOR 5534: Fast Mapping of Quantitative MR-biosignatures at Ultra-high Magnetic Field

FOR 5534：超高磁场下定量 MR 生物特征的快速绘制

• 批准号: 500888779
• 金额: --
• 依托单位: Molekular-Neurologische Abteilung
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/500888779?language=en
• 关键词: 5534; Fast; Mapping; Quantitative; MR

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths, such as 7 Tesla, offers unique possibilities for non-invasive tissue characterization. Nevertheless, clinical applications are currently still rare, and present clinical research studies mostly focus on morphological imaging. Advanced tissue contrasts, such as chemical exchange saturation transfer (CEST), X-nuclei MRI and microstructural imaging, have already provided valuable information beyond morphology. The combined application of these MRI contrasts would provide a sound basis for highly insightful multispectral MRI. However, obtaining such an MR-signature scan is currently limited by long acquisition times, poor data quality due to radiofrequency field inhomogeneities, patient motion and the increasing difficulty of interpreting the large amount of complex multispectral data. To fully unleash the potential of 7T MRI, we aim to establish “MR biosignature imaging” augmenting morphological imaging. For this purpose, we will first establish the methodological base by developing complementary fast MR techniques for the unique non-invasive characterization of different tissues, their chemical composition and their microstructure. To turn MR-signatures into pathology-specific MR biosignatures for non-invasive tissue characterization, we will use three clinical research applications. We expect that the MR biosignatures, once established, will reveal early signs of neuro-degeneration, tissue degeneration in chronic diseases and provide insight into cancer risk factors. We are convinced that such an MR biosignature scan would provide a more comprehensive insight into disease processes than the sum of the individual contrasts. To achieve these goals, we will unify the efforts of MRI physicists, engineers, data scientists as well as clinicians. To enable the acquisition of high MR data quality, ‘smart’ hardware will be developed that combines radiofrequency (RF) coil technology with multiple receive and transmit elements as well as integrated multimodal RF coil load- and radar-based motion tracking technology. Data science will be employed to identify the most important data features of the MR-signature scan and to accelerate data acquisition. This research unit (RU) will build on a strong research environment and infrastructure in Erlangen. At the Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), outstanding research groups in the field of data science, machine learning and electrical engineering will contribute by working closely with the researchers of the University Hospital Erlangen (UKER), i.e. with three recently established research groups focusing on novel MR contrasts and UHF MRI, and with collaborating clinical researchers. A dedicated clinical 7T system will be used, offering unique possibilities for combining cutting-edge technological and clinical research.

磁共振成像（MRI）在超高场（UHF）强度，如7特斯拉，提供了独特的可能性，非侵入性组织定征。然而，目前临床应用仍然很少，目前的临床研究主要集中在形态学成像。先进的组织对比，如化学交换饱和转移（CEST），X-核MRI和显微结构成像，已经提供了形态学以外的有价值的信息。这些MRI对比度的组合应用将为具有高度洞察力的多光谱MRI提供良好的基础。然而，获得这样的MR签名扫描目前受到长的采集时间、由于射频场不均匀性导致的差的数据质量、患者运动以及解释大量复杂多光谱数据的难度增加的限制。为了充分发挥7 T MRI的潜力，我们的目标是建立“MR生物特征成像”增强形态成像。为此，我们将首先建立方法基础，开发互补的快速MR技术，用于不同组织的独特的非侵入性表征，它们的化学成分和微观结构。为了将MR签名转化为病理特异性MR生物签名，用于非侵入性组织表征，我们将使用三种临床研究应用。我们期望MR生物特征一旦建立，将揭示慢性疾病中神经变性、组织变性的早期迹象，并提供对癌症风险因素的深入了解。我们相信，这样的MR生物特征扫描将提供比单个对比的总和更全面的疾病过程的见解。为了实现这些目标，我们将统一MRI物理学家，工程师，数据科学家以及临床医生的努力。为了能够获得高质量的MR数据，将开发“智能”硬件，将射频（RF）线圈技术与多个接收和发射元件以及集成的多模式RF线圈负载和基于雷达的运动跟踪技术相结合。数据科学将用于识别MR签名扫描的最重要数据特征，并加速数据采集。这个研究单位（RU）将建立在埃尔兰根强大的研究环境和基础设施。在弗里德里希-亚历山大埃尔朗根-纽伦堡大学（FAU），数据科学，机器学习和电气工程领域的杰出研究小组将通过与大学医院埃尔兰根（UKER）的研究人员密切合作做出贡献，即与三个最近成立的研究小组合作，专注于新的MR对比和UHF MRI，并与临床研究人员合作。将使用专用的临床7 T系统，为结合尖端技术和临床研究提供独特的可能性。