Optimization of Diffusion-Tensor MRI for Tractography

描述（由申请人提供）：开发准确的、无创的方法来绘制与脑病理相关的白质纤维束是神经外科社区至关重要的目标。然而，传统的光纤跟踪是基于自旋回波回波平面扩散张量图像采集（SE-EPI-DTI），存在bo相关的图像失真和伪影。因此，很大比例的白质纤维束扭曲，和/或早期终止，而其他的则完全未被发现。这严重限制了纤维追踪技术的临床潜力。相比之下，螺旋桨- dti（周期性旋转重叠平行线与增强重建）是相对免疫的bo相关的伪影。但是，PROPELLER-DTI的成像时间明显长于传统的SE-EPI-DTI。本研究的主要目标是在加速版本的PROPELLER-DTI （Turboprop-DTI）中最大限度地减少噪声和图像伪影，以便为临床环境中的牵引造影提供优化的数据采集和重建技术。我们的具体目标是：(i)将生理信息纳入Turboprop-DTI图像重建中，以降低噪声；（ii）开发改进的Turboprop-DTI重建方法，以进一步降低噪声和图像伪像；（iii）开发具有临床可接受成像时间的优化Turboprop-DTI采集方案；（iv）比较SE-EPI-DTI和优化的Turboprop-DTI数据集获得的示管造影结果。光纤跟踪结果的准确性和再现性在很大程度上取决于DTI图像的噪声水平和伪影的数量。本研究将解决这些问题，并开发一种基于螺旋桨的成像方法，该方法对临床环境中的白质纤维跟踪进行了优化。这项研究的成功完成将加速光纤跟踪作为一种常规使用和强大的诊断工具的发展。

DESCRIPTION (provided by applicant): The development of accurate, noninvasive methods for mapping white matter fiber-tracts in relation to brain pathologies is a goal of critical importance to the neurosurgical community. However, conventional fiber- tracking is based on spin-echo echo-planar diffusion tensor image acquisitions (SE-EPI-DTI), which suffer from BO-related image distortions and artifacts. Thus, a large percentage of white matter fiber-bundles are distorted, and/or terminated early, while others are completely undetected. This severely limits the clinical potential of fiber-tracking techniques. In contrast, PROPELLER-DTI (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) is relatively immune to BO-related artifacts. However, the imaging time in PROPELLER-DTI is markedly longer than in conventional SE-EPI-DTI. The broad objective of this research is to minimize noise and image artifacts in an accelerated version of PROPELLER-DTI (Turboprop-DTI), in order to provide a data acquisition and reconstruction technique that is optimized for tractography in a clinical setting. Our specific aims are to: (i) Incorporate physiological information in Turboprop-DTI image reconstruction in order to reduce noise, (ii) Develop improved reconstruction methods for Turboprop-DTI to further reduce noise and image artifacts, (iii) Develop optimized Turboprop-DTI acquisition schemes with clinically acceptable imaging time, and (iv) Compare tractography results obtained from SE-EPI-DTI and optimized Turboprop-DTI datasets. The accuracy and reproducibility of fiber-tracking results depend greatly on the noise levels and amount of artifacts of the DTI images. This study will address these issues and develop a PROPELLER-based imaging method that is optimized for white matter fiber- tracking in a clinical setting. The successful completion of this research will accelerate the development of fiber-tracking as a routinely used and powerful diagnostic tool.