Prediction of Motor Outcome after Acute Stroke using Diffusional Kurtosis Imaging

描述(由申请人提供)：大约三分之一的中风患者在首次中风后遭受持续性运动障碍。康复干预是促进运动康复的关键，旨在提高患者独立管理日常活动的能力。关于具体康复方案的设计的决定受 临床评估患者的运动恢复潜力，以及其他因素。弥散张量成像(DTI)是一种有希望的工具，用于量化与中风相关的微结构损伤，被认为与最终的功能恢复有关。对于慢性卒中，几项DTI研究表明，运动功能恢复不良与患侧皮质脊髓束水扩散的低各向异性有关。对于急性中风， 然而，相应的DTI结果并没有得到可靠的证明。由于延迟的康复治疗往往导致较差的运动结果，改进的神经成像技术用于评估卒中急性期的康复潜力，对于计划适当和及时的康复干预具有潜在的价值。在脑组织中，扩散障碍的存在，如细胞膜和细胞器，导致水的扩散明显是非高斯的。因为DTI仍然假设水的扩散是高斯的，所以它表征组织微结构的能力必然是不完整的。为了克服这一局限性，我们开发了一种临床上可行的扩散磁共振成像方法，它可以解释弥漫性非高斯性(即峰度)，称为扩散峰度成像(DKI)。 此外，从DTI或DKI获得的扩散度量是大块物理属性，与组织属性没有明确的联系。为了解决第二个局限性，我们开发了一种称为大脑微环境建模(CMM)的技术，该技术通过利用DKI得出的扩散度量来估计特定组织的微结构属性，如轴突(即轴突和树突)密度、取向分布和间隔扩散系数。我们的总体假设是，我们的新CMM方法获得的组织特性是缺血性脑损伤的敏感生物标志物，可能是急性缺血性卒中后运动功能恢复的可靠预后指标。这一假设将通过以下具体目标进行检验：(1)确定CMM指标与组织学定义的缺血性中风后脑细胞结构之间的关系；以及(2)调查CMM指标与中风后自发和康复诱导的运动恢复之间的关系。该项目的成功完成将为自发性和康复诱导的中风康复提供敏感的和生物物理学上可解释的生物标记物。

DESCRIPTION (provided by applicant): Approximately one-third of all stroke patients endure persistent motor disability after their initial stroke. Rehabilitative interventions are crucial fo promoting motor recovery aimed at improving patients' ability to independently manage daily activities. Decisions regarding the design of specific rehabilitation protocols are governed by the clinical assessment of a patient's potential for motor recovery, among other factors. Diffusion tensor imaging (DTI) is a promising tool for quantifying stroke- related microstructural brain damage thought to be associated with eventual functional recovery. For chronic stroke, several DTI studies have demonstrated that poor motor function recovery is associated with low fractional anisotropy of water diffusion in the ipsilesional corticospinal tract. For acute stroke, however, corresponding DTI results have not been reliably demonstrated. Since delayed efforts for rehabilitation often lead to worse motor outcome, improved neuroimaging techniques for evaluating the potential for recovery during the acute stages of stroke would potentially be valuable for the planning of appropriate and timely rehabilitative intervention. In brain tissue, he presence of diffusion barriers, such as cellular membranes and organelles, causes water diffusion to be markedly non-Gaussian. Because DTI nonetheless assumes water diffusion to be Gaussian, its ability to characterize tissue microstructure is necessarily incomplete. To overcome this limitation, we have developed a clinically feasible diffusion MRI method that accounts for diffusional non-Gaussianity (i.e. kurtosis) called diffusional kurtosis imaging (DKI). Furthermore, diffusion metrics obtained from either DTI or DKI are bulk physical properties with no explicit link to tissue properties. To address this second limitation, we have developed a technique called cerebral microenvironment modeling (CMM) that provides estimates of specific tissue microstructural properties, such as neurite (i.e. axons and dendrites) density, orientation distribution and compartmental diffusion coefficients, by utilizing the diffusion metrics derived from DKI. Our overall hypothesis is that tissue properties obtained from our new CMM method are sensitive biomarkers of ischemic brain injury, which may be reliable prognostic indicators of motor function recovery after acute ischemic stroke. This hypothesis will be tested by the following Specific Aims: (1) to determine the relationship between CMM metrics and histologically defined brain cytoarchitecture after ischemic stroke; and (2) to investigate the association between CMM metrics and spontaneous and rehabilitation-induced motor recovery after stroke. Successful completion of this project will provide sensitive and biophysically interpretable biomarkers of spontaneous and rehabilitation-induced stroke recovery.