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Development of an Open-Source Preclinical Imaging Informatics Platform for Cancer Research

开发用于癌症研究的开源临床前成像信息学平台

基本信息

批准号：
10474402
负责人：
Daniel Scott Marcus
金额：
$ 72.21万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10474402
关键词：
Advisory Committees Animal Experiments Animal Model Animals Architecture Big Data Biology Clinical Research Clinical Trials Collaborations Collection Complex Computer software Data Data Commons Data Set Databases Detection Development Drug Evaluation Environment Genetically Engineered Mouse High Performance Computing Image Image Enhancement Industry Informatics Institution Internet Intervention Laboratories Malignant Neoplasms Metadata Modeling Mus Pathology Patients Pharmaceutical Preparations Physiology Positron-Emission Tomography Precision Medicine Initiative Privatization Procedures Process Protocols documentation Reproducibility Research Research Personnel Research Support Resources Running Services Site Technology The Cancer Imaging Archive Time Tumor Burden Tumor-Derived Vertebral column animal imaging anticancer research automated image analysis automated segmentation base cancer imaging clinical imaging co-clinical trial computational pipelines data management data mining data sharing design disease diagnosis drug development ex vivo imaging experimental study handheld mobile device imaging informatics in vivo instrument mathematical analysis mathematical model member multimodality multiparametric imaging multiscale data novel novel therapeutic intervention open data open source portability pre-clinical precision medicine preclinical imaging preclinical study predicting response predictive marker programs public health relevance radiomics serial imaging software development treatment response tumor tumor xenograft web interface

项目摘要

ABSTRACT Preclinical imaging is widely used in cancer research to devise novel tumor detection strategies, assess tumor burden and physiology/biology, as well as to validate novel therapeutic strategies and predictive and biomarkers of response to therapy. More recently, the use of patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs) has ushered an era of co-clinical trials where preclinical studies can inform clinical trials, thus potentially bridging the translational gap in cancer research. However, differences in the deployment of the instruments, differences in imaging formats and protocols, differences in animal models, and variability in analytic pipelines among other factors result in non-tractable data and poor reproducibility. Importantly, current databases are not compatible with complexity and growing demands in preclinical cancer imaging which include big data needs and collection of metadata/annotation to support NCI’s precision medicine initiative. Thus, there is an unmet need to develop a unifying imaging informatics and workflow management platform to support cancer research, which will ultimately support the premise of translational precision medicine. We propose to develop an open-source preclinical imaging informatics platform—Preclinical Imaging XNAT- enabled Informatics (PIXI)—to manage the workflow of preclinical imaging laboratories, harmonize imaging databases, and enable deployment of analytic and computational pipelines in preclinical imaging. PIXI will be based on XNAT as the underlying informatics architecture. XNAT is used by over 200 academic institutions and industry entities as the backbone for data management across a wide range of imaging applications in clinical research, and thus offers a robust platform for the development and deployment of PIXI. Through this effort, we will 1) develop the PIXI database and server to capture preclinical imaging associated data, metadata, and preclinical imaging workflow and experiments; 2) develop the PIXI “point-of-service” interface, notebook capabilities, and software development kit (SDK); and 3) develop the PIXI container-based application (“App”) environment to implement portable analytic pipelines. Overall, the development of a preclinical imaging informatics platform is expected to have a profound impact on the management of preclinical imaging in cancer research which will ultimately support translational precision medicine.

摘要