Evaluation of novel markers of on-set of PD using machine learning and routine CT brain imaging

使用机器学习和常规 CT 脑成像评估 PD 发病的新标志物

• 批准号: 2432201
• 金额: --
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2432201
• 关键词: Evaluation; novel; markers; set; PD

This project addresses the priority area of early detection of PD onset to allow timely administration of new treatments. The main goal in this project is to develop and evaluate an artificial intelligence (AI)-based tool to analyse routine computer tomography (CT) brain scans in hospital libraries to detect PD onset before routine diagnosis. This will lead to a new way to detect people at risk of developing PD and to earlier diagnosis. PD is a common neurodegenerative disease (around 130, 000 people are affected in the UK, increasing by 2% per year). Currently, it is diagnosed on the basis of examination and movement disorder. We believe CT brain changes can serve as radiological markers detectable before the onset of movement symptoms. Project work will include developing an AI pipeline, based on deep learning methods, to analyse CT scans to detect the changes and evaluating the changes as markers of PD. This is an inter-disciplinary project which brings together experts in clinical neuroscience, radiology, electronics, computer science and statistics.

该项目的重点是早期发现帕金森病的发病，以便及时进行新的治疗。该项目的主要目标是开发和评估一种基于人工智能 (AI) 的工具，用于分析医院图书馆的常规计算机断层扫描 (CT) 脑部扫描，以便在常规诊断之前检测帕金森病的发病情况。这将带来一种新的方法来检测有患帕金森病风险的人并进行早期诊断。 PD 是一种常见的神经退行性疾病（在英国约有 130, 000 人受到影响，每年以 2% 的速度增加）。目前，它是根据检查和运动障碍来诊断的。我们相信 CT 脑部变化可以作为在运动症状出现之前可检测到的放射学标记。项目工作将包括开发基于深度学习方法的人工智能管道，以分析 CT 扫描以检测变化并评估变化作为 PD 标记。这是一个跨学科项目，汇集了临床神经科学、放射学、电子学、计算机科学和统计学方面的专家。