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Image based prediction of aggressive early lung cancer in lung cancer screening populations

Image based prediction of aggressive early lung cancer in lung cancer screening populations
基于图像的肺癌筛查人群中侵袭性早期肺癌的预测
批准号:
2876044
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
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英文摘要
1) Brief description of the context of the research including potential impactLung cancer screening invites high risk subjects to have a CT scan of their lungs to identify early treatable lung cancer. By 2028 approximately 500-750,000 subjects will have a CT scan of their lungs annually in the National UK lung cancer screening program. 2-3% of screened subjects will have a lung cancer. Lung cancers can show differing rates of growth and spread to lymph nodes, and some lung cancers, despite treatment can recur. Identifying potentially aggressive lung cancers at an early stage could transform lung cancer management worldwide. Cancers expected to be aggressive could be treatment with extra chemotherapy prior to surgery. Our study will analyse data from two UCL studies: SUMMIT and ASCENT. The SUMMIT study is one of the largest lung cancer screening studies in the world which has scanned >13,000 subjects annually to identify lung cancer. The ASCENT study comprises all SUMMIT study patients where a lung cancer was diagnosed. The cancers in the ASCENT study have been genotyped and have longitudinal outcome data collected.This study aims to correlate imaging features of lung cancer growth with clinical and genomic mutational markers of aggression.2) Aims and Objectives Identify image-based features of malignant lung nodules on low-dose CT scans that predict aggressive disease.Evaluate mediastinal lymph node change as a predictor of aggressive disease.Identify genomic signatures on imaging data that can predict aggressive disease.3) Novelty of Research MethodologyDefining aggression in early lung cancer. Aggression currently has no formal medical definition, but creating this could be valuable for many cancer typesUse of time-series deep learning models on medical imaging considering lung and extra-lung features to predict disease progressionNovel histopathological-genomic-imaging correlations to delineate a multidimensional risk score predictive of aggressive early lung cancer4) Alignment to EPSRC's strategies and research areasEPSRC Strategic Priorities: transforming health and healthcareEPSRC Research Portfolio and Priorities: healthcare technologies5) Any companies or collaborators involvedN/A
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海外基金
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  • 批准号:
    --
  • 项目类别:
    外国学者研究基金项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    YU BYUNGJUN
  • 依托单位:
Exploring the Intrinsic Mechanisms of CEO Turnover and Market Reaction: An Explanation Based on Information Asymmetry
  • 批准号:
    W2433169
  • 项目类别:
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  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    HAOFEI ZHANG
  • 依托单位:
含Re、Ru先进镍基单晶高温合金中TCP相成核—生长机理的原位动态研究
  • 批准号:
    52301178
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30.00万元
  • 批准年份:
    2023
  • 负责人:
    夏万顺
  • 依托单位: