跳至主要内容
临床试验/NCT04986020
NCT04986020Unknown不适用

Identifying New Biomarkers of Parkinson's From Routine Brain Imaging

University of Plymouth0 个研究点目标入组 20,000 人开始时间: 2021年8月1日最近更新:
适应症

试验速览

阶段
不适用
入组人数
20,000
主要终点
The presence of novel putative biomarkers of future PD development as defined by a deep-learning method

研究概览

简要总结

The study will use routine computer tomography (CT), magnetic resonance spectroscopy (MRI) and nuclear medicine (NM) brain imaging data to produce new diagnostic tests for the onset of Parkinson's disease. This will enable hopefully earlier diagnosis than is currently possible. This will entail the analysis of anonymised CT/MRI/NM brain images collected prior to the point when these subjects were diagnosed with PD.

详细描述

We intend to use historical CT/MRI/nuclear medicine brain scans to identify novel imaging biomarkers of prodromal Parkinson's disease. The primary data source for the study will be MRI and CT brain scans, whilst nuclear medicine imaging brain imaging (DAT scans) will be used to validate models produced and provide a functional outcome measure of brain dopamine uptake. We shall utilise a an artificial intelligence approach to compare scans of PD cases with matched controls in order to identify these imaging biomarkers.

A list of participants with a diagnosis will be compiled. This list, together with relevant clinical data, will be linked with historical CT/MRI/nuclear medicine scans carried out over the preceding years. A control group of matched non-PD scans will also be compiled.

The dataset will be anonymised and a bespoke ML pipeline will be used to identify imaging featureswhich may be indicative of prodromal PD. This initial stage will be carried out at University Hospital Plymouth NHS Trust (UHPNT), the Royal Cornwall Hospital NHS Trust (RCHNT) and Cornwall Partnership NHS Trust (CPNT). If successful, findings will be validated in a larger sample of scans compiled from hospitals regionally and nationally.

研究设计

研究类型
Observational
观察模型
Case Control
时间视角
Retrospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • A clinical diagnosis of Parkinson's

排除标准

  • No clinical diagnosis of Parkinson's

结局指标

主要结局

The presence of novel putative biomarkers of future PD development as defined by a deep-learning method

时间窗: 3 years

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Stephen Mullin

Clinical Lecturer in Neurology

University of Plymouth

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