Abstract
CompreHensive Digital ArchiVe of Cancer Imaging - Radiation Oncology (CHAVI-RO) is a multi-tier WEB-based medical image databank. It supports archiving de-identified radiological and clinical datasets in a relational database. A semantic relational database model is designed to accommodate imaging and treatment data of cancer patients. It aims to provide key datasets to investigate and model the use of radiological imaging data in response to radiation. This domain of research area addresses the modeling and analysis of complete treatment data of oncology patient. A DICOM viewer is integrated for reviewing the uploaded de-identified DICOM dataset. In a prototype system we carried out a pilot study with cancer data of four diseased sites, namely breast, head and neck, brain, and lung cancers. The representative dataset is used to estimate the data size of the patient. A role-based access control module is integrated with the image databank to restrict the user access limit. We also perform different types of load tests to analyze and quantify the performance of the CHAVI databank.
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Acknowledgements
We would like to extend our gratitude to all the patient, who has given the consent for using their dataset in this study. This project is funded under National Digital Library of India (NDLI) sponsored by Ministry of Human Resource Development (MHRD), Govt. of India.
Funding
This study has been funded by the Ministry of Education, formerly the Ministry of Human Resource Development, India (IIT/SRIC/CS/NDM/2018-19/096).
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CHAVI-databank complies with the principles of data being findable, accessible, interoperable [13].
Findable: Each data stored in the database corresponds to a unique identifier. We also maintain referential data integrity in the dependent data. Which ensures the data findability.
Accessible: Data viewer is a specific user in the databank. Users can browse data and view them. Then the data can be accessed with proper authentication or authorization.
Interoperable: The structure of the DICOM is kept intact even after de-identification. This data can be incorporated with any other applications. Theclinical data of the patients are kept in a relational database. So DICOM and clinical data both can interoperate with any other similar applications. The Reusable part is not specified as of yet we are in the process of discussion with the stakeholders to define the data reuse terms and conditions.
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Kundu, S., Chakraborty, S., Mukhopadhyay, J. et al. Design and Development of a Medical Image Databank for Assisting Studies in Radiomics. J Digit Imaging 35, 408–423 (2022). https://doi.org/10.1007/s10278-021-00576-6
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DOI: https://doi.org/10.1007/s10278-021-00576-6