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能够定量分析多发性硬化症（MS）患者的 MRI 数据的软件。该项目的成果将被商业化为： 用于临床试验的 MS 图像处理服务；我们的 AutoAlign MR 对准软件的 GE 特定扩展；最后作为医疗设备软件，提供 MS 特定功能（MS CAD，计算机辅助诊断）以供患者护理使用。所提出的软件利用先进的配准、分割和量化技术，旨在解决该领域长期存在的问题。 MS 是一种无法治愈的神经退行性疾病，大约千分之一的人受到影响。它是典型的中枢神经系统炎症性自身免疫性疾病，可能是年轻人神经功能障碍的最常见原因。为了维持功能和缓解症状，患者必须接受终生治疗，通常包括昂贵的干扰素药物治疗。多年来新症状的出现、缓解和恶化是多发性硬化症临床病程的特征。由于这种变异性，当患者经历多发性硬化症发作时，临床医生寻求临床旁测试来指导治疗决策。国际多发性硬化症诊断专家组建议在初次诊断时使用 MRI，并在确定多发性硬化症阳性诊断后广泛用于监测疾病进展。在典型的临床环境中，多发性硬化症患者的 MRI 评估仅限于放射科医生的目视检查，并且不会对该信息进行量化。此外，虽然多中心 MS 临床试验通常使用连续 MRI 扫描，但由于扫描和扫描仪之间基本的采集级别差异，该信息会因 MR 配准问题而混淆。该项目中的技术解决了所有这些挑战，并且应该会导致 MR 评估在 MS 中具有更大的临床实用性。 基于下面详述的 4 个具体目标，在该项目的第一阶段，将创建一个软件原型，以证明这种量化 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标是实施提供大脑白质掩模的方法，以帮助在各种 MR 模式中检测、量化和区分 MS 病变。我们的第二个具体目标是开发算法来纠正连续多模态 MRI 扫描之间的患者运动，这是多光谱 MS 病变分析的先决条件。我们的第三个具体目标是开发原型技术，用于在标准 MR 模式上自动识别、量化和区分白质异常（即推定的 MS 病变）。我们的第四个具体目标是根据“黄金标准”方法验证此原型。