Free-Breathing Perfusion MRI of the Abdomen with Predictive Motion Correction

描述(申请人提供)：随着人口老龄化，肾脏疾病的发病率也在增加。诊断成像在检测和监测包括肾细胞癌(RCC)在内的肾脏疾病中起着关键作用。然而，对于60岁或以上的肾病患者来说，在成像过程中使用静脉造影剂的风险会上升。本研究的目的是开发无对比度磁共振成像(MRI)技术在肾癌中的应用。核磁共振检查程序将包括血流定量以检测肾脏肿瘤。呼吸运动补偿是腹部磁共振成像中的一个主要挑战。像核磁共振灌注成像这样的功能程序需要准确的运动补偿，因为屏气或呼吸门控等替代方法增加了检查的时间和患者的压力。本研究的目的是增强ASL MRI在肾癌和腹部灌注MRI中的应用。该建议的具体目的是：1)使用计算机模拟和活体呼吸运动数据来识别和评估候选呼吸运动预测(RMP)算法；2)将最好的RMP算法与2D回波平面成像(EPI)和3D梯度和自旋回波(GRASE)MRI相结合，以实现腹部快速自由呼吸的MRI采集，使用呼吸运动模型优化这些技术，然后在人体志愿者身上比较它们的性能；3)将最好的2D EPI和3D GASE RMP技术与脉冲连续ASL(PCASL)MRI序列相结合，并评估和优化其在人体志愿者中的性能；4)在肾癌患者中应用最佳RMP灌注(2D和3D pCASL)技术来评估肿瘤的血流灌注，并将结果与金标准(CT增强)进行比较。本研究将检验的假设包括：1)可以预测未来的肾脏运动1 S的误差为&lt；2 mm；2)使用回溯性图像后处理的3D Grase结合RMP将提供比2D EPI更优越的运动校正，具有预期的图像切片平移；3)3D Grase pCASL结合RMP将提供更高的灌注信噪比，且运动伪影比使用2D EPI pCASL+RMP更少；4)PCASL结合RMP可以以90%的能量检测RCC肿瘤边界。RMP方法将允许自由呼吸和实时跟踪感兴趣的器官，同时将丢弃的图像数据降至最低。动脉自旋标记、弥散加权成像(DWI)和血氧水平依赖(BOLD)等运动敏感功能MRI序列在评估器官健康和肿瘤活动方面具有实用价值，也将受益。该技术可被进一步开发用于生理运动阻碍准确诊断或治疗(例如，放射治疗)的其他感兴趣的解剖区域或应用。

DESCRIPTION (provided by applicant): The incidence of renal diseases is growing as the population ages. Diagnostic imaging serves a key role in detecting and monitoring renal diseases including renal cell carcinoma (RCC). Yet the risk of intravenous contrast agents used in imaging procedures rises for individuals with renal disease and aged 60 years or older. The objectives of the proposed research are to develop contrast free magnetic resonance imaging (MRI) techniques for application in RCC. The MRI procedures will include perfusion quantification to detect renal tumors. Respiratory motion compensation is a major challenge in MRI of the abdomen. Functional procedures like perfusion MRI require accurate motion compensation since alternatives like breathholds or respiratory gating increase the length of the exam and the strain on the patient. The objectives of the proposed research are to enhance ASL MRI for application in RCC and abdominal perfusion MRI. The specific aims of this proposal are to: 1) identify and evaluate candidate respiratory motion prediction (RMP) algorithms using computer simulations and in vivo respiratory motion data; 2) integrate the best RMP algorithms with 2D echo planar imaging (EPI) and 3D gradient and spin echo (GRASE) MRI to allow fast free-breathing MRI acquisitions of the abdomen, optimize the techniques using a respiratory motion phantom, and then compare their performances in human volunteers; 3) integrate the best 2D EPI and 3D GRASE RMP techniques with pulsed continuous ASL (pCASL) MRI sequences, and evaluate and optimize its performance in human volunteers; 4) apply the best RMP perfusion (2D vs. 3D pCASL) technique in human subjects with RCC to assess tumor perfusion and compare the results to the gold standard (CT with contrast). The hypotheses that will be tested in this study include: 1) kidney motion can be predicted 1 s into the future with an error of <2 mm; 2) 3D GRASE with RMP using retrospective image post-processing will provide superior motion correction than 2D EPI with prospective image slice translation; 3) 3D GRASE pCASL with RMP will provide superior perfusion signal-to-noise ratio (SNR) and less motion artifact than using 2D EPI pCASL with RMP; 4) pCASL with RMP can detect RCC tumor boundaries with >90% power. The RMP method will permit free-breathing and real-time tracking of the organ of interest while minimizing discarded image data. Motion sensitive functional MRI sequences like arterial spin labeling, diffusion weighted imaging (DWI), and blood oxygenation level dependent (BOLD) that have utility in assessing organ health and tumor activity will also benefit. The technique may be further developed for other anatomical regions of interest or applications where physiological motion impedes accurate diagnosis or therapy (e.g., radiotherapy).