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

开发用于评估 MR 的流量和血管量化软件

• 批准号: 8369059
• 负责人: Ewart Mark Haacke
• 金额: $ 8.01万
• 依托单位: MAGNETIC RESONANCE INNOVATIONS, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8369059
• 关键词: Address; Algorithms; Anatomy; Angiography; Anisotropy; Area; Arteries; Attenuated; Basal Ganglia; Behavior; Blood Vessels; Brain; Characteristics; Chronic; Clinical; Computer software; Data; Dementia; Deposition; Detection; Development; Diagnosis; Disease; Evaluation; Factor Analysis; Fatty acid glycerol esters; Goals; Growth; Image; Image Analysis; Iron; Label; Lead; Lesion; Liquid substance; Location; Magnetic Resonance; Magnetic Resonance Imaging; Manuals; Maps; Measures; Minor; Modeling; Morphologic artifacts; Multiple Sclerosis; Muscle; Neck; Neurodegenerative Disorders; Optics; Patients; Phase; Predisposition; Process; Protocols documentation; Publishing; Radiation; Recovery; Reporting; Shapes; Signal Transduction; Site; Stroke; Structure; System; Techniques; Thalamic Nuclei; Thalamic structure; Thyroid Gland; Time; Tissues; Training; Traumatic Brain Injury; Veins; Venous Insufficiency; Weight; Work; computerized data processing; design; driving force; hemodynamics; image processing; improved; innovation; interest; novel; programs; software development; tool; white matter

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.

描述（由申请人提供）：对临床环境中对多发性硬化症，创伤性脑损伤，中风和痴呆症的临床环境中产生的神经血管成像数据的全面定量分析的需求大大增加。我们在该项目中的目标是设计和开发可以快速准确分析此类数据的高级图像处理软件。为了实现这一目标，我们提出了一系列新型算法，以从以下MR成像序列中处理数据，在上述应用中广泛使用：时间分解的3D对比增强了MR血管造影（CE-MRA），用于评估血管解剖学的评估，用于时间分解的2D相比流动（PC-MRI）的量化（PC-MRI），以评估均值（PC-MRI），并评估均值（PC-MRI），并评估均值（PC-MRI），并评估了体面的体重效率（PC-MRI）。铁沉积在大脑中，流体减弱了反转恢复（FLAIR）成像，以检测白质超强度（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图像中的脉管系统；基础神经节和丘脑中的自动组织分割，用于用SWI进行铁定量的两区分析；最后，适应模糊c均值的自适应方法，形状因子分析，紧凑性和分数各向异性，以量化病变和WMH。为了利用不同成像序列提供的优点，将使用共同注册算法来改善CE-MRA和PC-MRI之间的血管分割，以及3D T1加权成像和SWI之间。完成该项目后，我们预计处理效率会增加数量，并且准确性将大大提高。由此产生的软件不仅可以帮助我们公司的发展，还可以改善神经血管疾病的诊断和治疗。 公共卫生相关性：对对神经血管疾病的大量临床MR成像数据的更全面和准确分析的需求巨大增加，例如多发性硬化症，创伤性脑损伤，中风和痴呆症是我们公司开发更先进的图像处理软件的推动力。在这个项目中，我们提出了一种综合方法，以开发一组用于成像序列的处理软件，以评估神经血管形系统的解剖结构和功能。结果将导致更好地获取有关神经血管疾病中存在的大脑脉管系统，流动，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加工吞吐量和准确性来帮助我们公司的增长，还可以改善神经血管疾病患者的诊断和治疗。