An Open Source Toolkit for Medical Imaging De-Identification

Objective: Medical imaging acquired for clinical purposes can have several legitimate secondary uses in research projects and teaching libraries. No commonly accepted solution for anonymising these images exists because the amount of personal data that should be preserved varies case by case. Our objective is to provide a flexible mechanism for anonymising DICOM data that meets the requirements for deployment in multicentre trials. Methods: We reviewed our current de-identification practices and defined the relevant use cases to extract the requirements for the de-identification process. We then used these requirements in the design and implementation of the toolkit. Finally, we tested the toolkit taking as a reference those requirements, including a multicentre deployment. Results: The toolkit sucesfully anonymised DICOM data from various sources. Furthermore, it was shown that it could forward anonymous data to remote destinations, remove burned-in annotations, and add tracking information to the header. The toolkit also implements the DICOM standard confidentiality mechanism. Conclusion: A DICOM de-identification toolkit that facilitates the enforcement of privacy policies was developed. It is highly extensible and provides the necessary flexibility to account for different de-identification requirements, but at the same time, it has a low adoption barrier to new users

Implementation of an anonymisation tool for clinical trials using a clinical trial processor integrated with an existing trial patient data information system

To present an adapted Clinical Trial Processor (CTP) test set-up for receiving, anonymising and saving Digital Imaging and Communications in Medicine (DICOM) data using external input from the original database of an existing clinical study information system to guide the anonymisation process. Two methods are presented for an adapted CTP test set-up. In the first method, images are pushed from the Picture Archiving and Communication System (PACS) using the DICOM protocol through a local network. In the second method, images are transferred through the internet using the HTTPS protocol. In total 25,000 images from 50 patients were moved from the PACS, anonymised and stored within roughly 2 h using the first method. In the second method, an average of 10 images per minute were transferred and processed over a residential connection. In both methods, no duplicated images were stored when previous images were retransferred. The anonymised images are stored in appropriate directories. The CTP can transfer and process DICOM images correctly in a very easy set-up providing a fast, secure and stable environment. The adapted CTP allows easy integration into an environment in which patient data are already included in an existing information system. Store DICOM images correctly in a very easy set-up in a fast, secure and stable environment Allows adaptation of the software to perform a certain task based on specific needs Allows easy integration into an existing environment Reduce the possibility of inappropriate anonymisation

Storing and Querying DICOM Data with HYTORMO

International audienc