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PRIMAGE 项目:基于预测性计算多尺度分析的儿童癌症个体化评估,该方法由影像生物标志物提供支持。

PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.

机构信息

Medical Imaging Department, La Fe University and Polytechnic Hospital & Biomedical Imaging Research Group (GIBI230) at La Fe University and Polytechnic Hospital and Health Research Institute, Av. Fernando Abril Martorell 106, 46026, Valencia, Spain.

Quantitative Imaging Biomarkers in Medicine, QUIBIM SL, Edificio Europa, Av. de Aragón, 30, Planta 12, 46021, Valencia, Spain.

出版信息

Eur Radiol Exp. 2020 Apr 3;4(1):22. doi: 10.1186/s41747-020-00150-9.

Abstract

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours.

摘要

PRIMAGE 是一个致力于医学影像、人工智能和儿童癌症治疗的大型且雄心勃勃的研究项目之一。这是一个由欧盟委员会资助的 4 年期项目,有 16 个欧洲合作伙伴参与该联盟,其中包括欧洲小儿肿瘤学会、两个成像生物库和三个著名的欧洲儿科肿瘤学单位。该项目构建为一个观察性的基于计算机的研究,涉及用于机器学习和多尺度算法的训练和验证的高质量匿名数据集(成像、临床、分子和遗传学)。基于成像生物标志物、肿瘤生长模拟、置信得分的高级可视化以及机器学习方法,该开放式基于云的平台将为表型(诊断)、治疗分配(预测)和患者终点(预后)提供精确的临床辅助。决策支持原型将在两种儿科癌症:神经母细胞瘤和弥漫性内在脑桥胶质瘤上构建和验证。将在来自独立合作中心的数据上进行外部验证。最终结果将在项目结束时提供给科学界,并准备好转化为其他恶性实体瘤。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/037f/7125275/939990f9e0a9/41747_2020_150_Fig1_HTML.jpg

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