Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

17th International Conference on the Use of Computers in Radiation Therapy

物理学;计算机科学

Driscoll, Brandon^1 ; Jaffray, David^1,2,3 ; Coolens, Catherine^1,2,3

Department of Radiation Physics, Princess Margaret Cancer Centre, 610 University Avenue, Toronto, ON, M5G 2M9, Canada^1

Department Radiation Oncology, University of Toronto, 150 College St, Toronto, ON, M5S 3E2, Canada^2

Techna Institute, University Health Network, 124-100 College Street, Toronto, ON, M5G 1L5, Canada^3

关键词: Analysis system;    Dynamic imaging;    Functional imaging;    Image transfer;    Kinetic modelling;    Proof of concept;    Remote analysis;    Very large datum;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/489/1/012089/pdf
DOI  :  10.1088/1742-6596/489/1/012089

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Purpose: To provide clinicians & researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.