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

描述（由申请人提供）：随着人口老龄化，肾脏疾病的发病率正在增长。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，对于患有肾脏疾病和年龄在60岁或以上的个体，在成像过程中使用静脉造影剂的风险增加。拟议的研究的目标是开发无对比度磁共振成像（MRI）技术在RCC中的应用。MRI程序将包括灌注定量，以检测肾肿瘤。呼吸运动补偿是腹部MRI的主要挑战。像灌注MRI这样的功能性程序需要精确的运动补偿，因为屏气或呼吸门控等替代方法会增加检查时间和患者的压力。拟议的研究的目标是增强ASL MRI在RCC和腹部灌注MRI中的应用。该提议的具体目的是：1）使用计算机模拟和体内呼吸运动数据来识别和评估候选呼吸运动预测（RMP）算法; 2）将最佳RMP算法与2D回波平面成像（EPI）和3D梯度和自旋回波（GRASE）MRI集成，以允许腹部的快速自由呼吸MRI采集，使用呼吸运动体模优化技术，3）将最佳的2D EPI和3D GRASE RMP技术与脉冲连续ASL（pCASL）MRI序列相结合，评估和优化其在人类志愿者中的性能; 4）在患有RCC的人类受试者中应用最佳RMP灌注（2D与3D pCASL）技术以评估肿瘤灌注并将结果与金标准（具有造影剂的CT）进行比较。本研究将检验的假设包括：1）肾脏运动可预测未来1 s，误差<2 mm; 2）使用回顾性图像后处理的RMP的3D GRASE将提供比使用前瞻性图像切片平移的2D EPI更好的上级运动校正; 3）与使用2D EPI pCASL和RMP相比，3D GRASE pCASL和RMP将提供上级灌注信噪比（SNR）和更少的运动伪影; 4）pCASL与RMP联合检测RCC肿瘤边界的能力>90%。RMP方法将允许自由呼吸和实时跟踪感兴趣的器官，同时最大限度地减少丢弃的图像数据。运动敏感的功能性MRI序列，如动脉自旋标记、弥散加权成像（DWI）和血氧水平依赖性（BOLD），在评估器官健康和肿瘤活动方面也将受益。该技术可以进一步开发用于其他感兴趣的解剖区域或生理运动阻碍准确诊断或治疗的应用（例如，放射疗法）。

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).