Development of flow and vascular quantification software for the assessment of MR

描述（由申请人提供）：对多发性硬化、创伤性脑损伤、中风和痴呆等疾病的临床环境中产生的神经血管成像数据进行全面定量分析的需求大幅增加。我们在这个项目中的目标是设计和开发先进的图像处理软件，可以快速，准确地分析这些数据。为了实现这一目标，我们提出了一系列新颖的算法来处理来自在上述应用中广泛使用的以下MR成像序列的数据：时间分辨3D对比增强MR血管造影术（CE-MRA）用于评估血管解剖结构，时间分辨2D相位对比血流成像（PC-MRI）用于评价血管血流动力学，磁敏感加权成像（SWI）用于定量脑内铁沉积，液体衰减反转恢复（FLAIR）成像用于检测白色高信号（WMH）和病变。将设计和实施各种工具来解决这些问题，包括：组织相似性映射和主动形状模型，以分割CE-MRA和PC-MRI图像中的血管系统;基底节和丘脑中的自动组织分割，用于SWI铁定量的两个感兴趣区域分析;最后，自适应方法结合模糊C均值，形状因子分析，紧凑性和分数各向异性量化病变和WMH。为了利用不同成像序列提供的优势，将使用共配准算法来改善CE-MRA和PC-MRI之间以及3D T1加权成像和SWI之间的血管分割。在完成这个项目后，我们预计将实现处理效率的成倍提高和准确性的显着提高。由此产生的软件不仅有助于我们公司的发展，还将改善神经血管疾病的诊断和治疗。 公共卫生相关性：对神经血管疾病（如多发性硬化症、创伤性脑损伤、中风和痴呆）的大量临床MR成像数据进行更全面、更准确分析的需求大幅增加，这是我们公司开发更先进图像处理软件的驱动力。在这个项目中，我们提出了一个综合的方法来开发一套处理软件的成像序列，目标是评估的解剖结构和功能的神经血管系统。结果将导致更好地获得有关神经血管疾病中大脑血管系统，流量，血液动力学和铁含量的定量数据。该项目的完成不仅将通过提高处理量和准确性来帮助我们公司的发展，而且还将改善神经血管疾病患者的诊断和治疗。

DESCRIPTION (provided by applicant): There has been a huge increase in demand for comprehensive quantitative analysis of neurovascular imaging data produced in the clinical setting for diseases such as multiple sclerosis, traumatic brain injury, stroke and dementia. Our objective in this project is to design and develop advanced image processing software that can rapidly and accurately analyze such data. To achieve this objective, we propose a range of novel algorithms to process data from the following MR imaging sequences widely used in the aforementioned applications: time resolved 3D contrast enhanced MR angiography (CE-MRA) for the assessment of vascular anatomy, time resolved 2D phase contrast flow imaging (PC-MRI) for the evaluation of vascular hemodynamics, susceptibility weighted imaging (SWI) for quantifying iron deposition in the brain, and fluid attenuated inversion recovery (FLAIR) imaging for the detection of white matter hyperintensities (WMH) and lesions. A variety of tools will be designed and implemented to tackle these problems including: tissue similarity mapping and active shape models to segment the vasculature in both CE-MRA and PC-MRI images; automatic tissue segmentation in the basal ganglia and thalamus for a two-region of interest analysis for iron quantification with SWI; and finally adaptive approaches incorporating fuzzy C-means, shape factor analysis, compactness and fractional anisotropy to quantify lesions and WMHs. To exploit the advantages provided by different imaging sequences, co-registration algorithms will be used to improve segmentation of vessels between CE-MRA and PC-MRI, and between 3D T1 weighted imaging and SWI. Upon finishing this project, we expect a multi-fold increase in processing efficiency and a significant increase in accuracy will be achieved. The resulting software will not only help the growth of our company, but also improve the diagnosis and treatment of neurovascular diseases. PUBLIC HEALTH RELEVANCE: The huge increase in demand for a more comprehensive and accurate analysis of the vast amount of clinical MR imaging data for neurovascular diseases such as multiple sclerosis, traumatic brain injury, stroke and dementia is the driving force for th development of more advanced image processing software in our company. In this project, we propose an integrated approach to develop a set of processing software for imaging sequences that target the assessment of both anatomy and function of the neurovasculature system. The results will lead to a better access to quantitative data about the brain's vasculature, flow, hemodynamics and iron content present in neurovascular diseases. The completion of this project will not only help the growth of our company by increasing processing throughput and accuracy, but also improve the diagnosis and treatment of patients with neurovascular disease.