Automated analysis of lesions and atrophy in MS

MS 病变和萎缩的自动分析

• 批准号: 6793527
• 负责人: Eric Halgren
• 金额: $ 14.4万
• 依托单位: CORTECHS LABS, INC.
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-29 至 2005-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6793527
• 关键词: atrophy; automated data processing; brain disorder diagnosis; brain disorders; computer assisted medical decision making; computer data analysis; computer program /software; computer system design /evaluation; human data; image processing; magnetic resonance imaging; molecular pathology; multiple sclerosis; white matter

DESCRIPTION (provided by applicant): The overall goal of this project is to develop software which can quantitatively analyze MRI data from patients with multiple sclerosis (MS). The outcome of this project will be commercialized as: an MS image-processing service for clinical trials; a GE-specific extension of our AutoAlign MR alignment software; and finally as medical device software providing MS specific functionality (MS CAD, computer aided diagnosis) for patient care use. The proposed software, with its utilization of advanced registration, segmentation and quantification techniques, is intended to solve persistent problems in this field. MS is an incurable, neurodegenerative disease that affects approximately 1 in 1000 persons. It is the prototypical inflammatory autoimmune disorder of the central nervous system and may be the most common cause of neurological disability in young adults. To maintain functioning and alleviate symptoms, patients must undergo lifelong treatment, frequently including expensive interferon drug therapy. The appearance of new symptoms, remissions, and exacerbations over periods of years is characteristic of the clinical course of MS. Because of this variability, clinicians have sought paraclinical tests to guide treatment decisions when patients experience progressing MS attacks. MRI is recommended during the initial diagnosis by the International Panel on MS Diagnosis and is extensively utilized to monitor disease progression after a positive MS diagnosis has been determined. In the typical clinical setting, MRI evaluations of MS patients are limited to visual inspections by radiologists, and no quantification of this information is performed. Furthermore, while multicenter MS clinical trials typically utilize serial MRI scans, this information is confounded by MR registration problems because of fundamental, acquisition-level variability between scans and scanners. The technology in this project addresses all of these challenges, and should lead to greater clinical utility of MR evaluations in MS. Based on the 4 specific aims detailed below, during phase I of this project a software prototype which will be created to demonstrate the feasibility of this quantified MR approach to facilitate more accurate MS disease monitoring. Our first specific aim is to implement methods to provide a mask of the cerebral white matter, to aid in the detection, quantification and differentiation of MS lesions in various MR modalities. Our second specific aim is to develop algorithms to correct for patient motion between consecutive multimodal MRI scans, which is a prerequisite for multispectral MS lesion analysis. Our third specific aim is to develop prototype techniques for automatically identifying, quantifying and differentiating white matter abnormalities (i.e., putative MS lesions) on standard MR modalities. Our fourth specific aim is to validate this prototype against "gold standard" methods.

描述（由申请人提供）：该项目的总体目标是开发可以定量分析多发性硬化症患者（MS）的MRI数据的软件。该项目的结果将被商业化为：用于临床试验的MS图像处理服务；我们的自动对准MR Alignment软件的特定于GE特定扩展；最后，作为医疗设备软件提供了MS特定功能（MS CAD，计算机辅助诊断），可用于患者护理。提出的软件及其利用高级注册，分割和量化技术，旨在解决该领域的持续问题。 MS是一种无法治愈的神经退行性疾病，影响约1000人中有1人。它是中枢神经系统的典型炎症自身免疫性疾病，可能是年轻人神经疾病的最常见原因。为了保持功能和减轻症状，患者必须接受终身治疗，通常包括昂贵的干扰素药物治疗。多年来，新症状，缓解和加剧的出现是MS临床过程的特征。由于这种可变性，临床医生已寻求旁囊测试以指导患者经历MS攻击进展时的治疗决策。在国际MS诊断方面，建议在初次诊断期间对MRI进行MRI，并在确定阳性MS诊断后广泛用于监测疾病进展。在典型的临床环境中，MS患者的MRI评估仅限于放射科医生的视觉检查，并且未对此信息进行量化。此外，尽管多中心MS临床试验通常使用串行MRI扫描，但由于扫描和扫描仪之间的基本，获取级别的可变性，因此MR注册问题会混淆此信息。该项目中的技术应对所有这些挑战，并应导致MS中MR评估的临床实用性更大。 基于下面详细介绍的4个特定目标，在该项目的I阶段期间，将创建一个软件原型，以证明这种量化的MR方法的可行性，以促进更准确的MS疾病监测。我们的第一个具体目的是实施提供掩盖大脑白质的方法，以帮助以各种MR模态以MS病变的检测，定量和分化。我们的第二个具体目的是开发算法以纠正连续多模式MRI扫描之间的患者运动，这是多光谱MS MS病变分析的先决条件。我们的第三个具体目的是开发用于自动识别，量化和区分白质异常（即推定的MS病变）的原型技术。我们的第四个具体目的是验证该原型针对“黄金标准”方法。