Bonmatí Luis Martí, Miguel Ana, Suárez Amelia, Aznar Mario, Beregi Jean Paul, Fournier Laure, Neri Emanuele, Laghi Andrea, França Manuela, Sardanelli Francesco, Penzkofer Tobias, Lambin Phillipe, Blanquer Ignacio, Menzel Marion I, Seymour Karine, Figueiras Sergio, Krischak Katharina, Martínez Ricard, Mirsky Yisroel, Yang Guang, Alberich-Bayarri Ángel
Medical Imaging Department, La Fe University and Polytechnic Hospital & Biomedical Imaging Research Group Grupo de Investigación Biomédica en Imagen (GIBI230) at La Fe University and Polytechnic Hospital and Health Research Institute, Valencia, Spain.
Matical Innovation SL, Madrid, Spain.
Front Oncol. 2022 Feb 24;12:742701. doi: 10.3389/fonc.2022.742701. eCollection 2022.
The CHAIMELEON project aims to set up a pan-European repository of health imaging data, tools and methodologies, with the ambition to set a standard and provide resources for future AI experimentation for cancer management. The project is a 4 year long, EU-funded project tackling some of the most ambitious research in the fields of biomedical imaging, artificial intelligence and cancer treatment, addressing the four types of cancer that currently have the highest prevalence worldwide: lung, breast, prostate and colorectal. To allow this, clinical partners and external collaborators will populate the repository with multimodality (MR, CT, PET/CT) imaging and related clinical data. Subsequently, AI developers will enable a multimodal analytical data engine facilitating the interpretation, extraction and exploitation of the information stored at the repository. The development and implementation of AI-powered pipelines will enable advancement towards automating data deidentification, curation, annotation, integrity securing and image harmonization. By the end of the project, the usability and performance of the repository as a tool fostering AI experimentation will be technically validated, including a validation subphase by world-class European AI developers, participating in Open Challenges to the AI Community. Upon successful validation of the repository, a set of selected AI tools will undergo early validation in observational clinical studies coordinated by leading experts in the partner hospitals. Tool performance will be assessed, including external independent validation on hallmark clinical decisions in response to some of the currently most important clinical end points in cancer. The project brings together a consortium of 18 European partners including hospitals, universities, R&D centers and private research companies, constituting an ecosystem of infrastructures, biobanks, AI experimentation and cloud computing technologies in oncology.
变色龙项目旨在建立一个泛欧健康影像数据、工具和方法库，目标是设定一个标准，并为未来癌症管理的人工智能实验提供资源。该项目为期4年，由欧盟资助，致力于生物医学成像、人工智能和癌症治疗领域一些最具雄心的研究，涉及目前全球发病率最高的四种癌症：肺癌、乳腺癌、前列腺癌和结直肠癌。为此，临床合作伙伴和外部合作者将向该库中填充多模态（磁共振成像、计算机断层扫描、正电子发射断层扫描/计算机断层扫描）影像及相关临床数据。随后，人工智能开发者将启用一个多模态分析数据引擎，以促进对存储在该库中的信息进行解读、提取和利用。人工智能驱动流程的开发和实施将推动数据去识别、管理、注释、完整性保障和图像协调自动化的发展。到项目结束时，将从技术上验证该库作为促进人工智能实验工具的可用性和性能，包括由世界级欧洲人工智能开发者参与的验证子阶段，这些开发者将参加面向人工智能社区的开放挑战。在该库成功验证后，一组选定的人工智能工具将在合作医院的顶尖专家协调的观察性临床研究中进行早期验证。将评估工具性能，包括针对癌症当前一些最重要临床终点的标志性临床决策进行外部独立验证。该项目汇聚了18个欧洲合作伙伴组成的联盟，包括医院、大学、研发中心和私营研究公司，构成了肿瘤学领域基础设施、生物样本库、人工智能实验和云计算技术的生态系统。
