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. 2018 Apr;9(2):377-390.
doi: 10.1055/s-0038-1651497. Epub 2018 May 30.

Integrating Multimodal Radiation Therapy Data into i2b2

Affiliations

Integrating Multimodal Radiation Therapy Data into i2b2

Eric Zapletal et al. Appl Clin Inform. 2018 Apr.

Abstract

Background: Clinical data warehouses are now widely used to foster clinical and translational research and the Informatics for Integrating Biology and the Bedside (i2b2) platform has become a de facto standard for storing clinical data in many projects. However, to design predictive models and assist in personalized treatment planning in cancer or radiation oncology, all available patient data need to be integrated into i2b2, including radiation therapy data that are currently not addressed in many existing i2b2 sites.

Objective: To use radiation therapy data in projects related to rectal cancer patients, we assessed the feasibility of integrating radiation oncology data into the i2b2 platform.

Methods: The Georges Pompidou European Hospital, a hospital from the Assistance Publique - Hôpitaux de Paris group, has developed an i2b2-based clinical data warehouse of various structured and unstructured clinical data for research since 2008. To store and reuse various radiation therapy data-dose details, activities scheduling, and dose-volume histogram (DVH) curves-in this repository, we first extracted raw data by using some reverse engineering techniques and a vendor's application programming interface. Then, we implemented a hybrid storage approach by combining the standard i2b2 "Entity-Attribute-Value" storage mechanism with a "JavaScript Object Notation (JSON) document-based" storage mechanism without modifying the i2b2 core tables. Validation was performed using (1) the Business Objects framework for replicating vendor's application screens showing dose details and activities scheduling data and (2) the R software for displaying the DVH curves.

Results: We developed a pipeline to integrate the radiation therapy data into the Georges Pompidou European Hospital i2b2 instance and evaluated it on a cohort of 262 patients. We were able to use the radiation therapy data on a preliminary use case by fetching the DVH curve data from the clinical data warehouse and displaying them in a R chart.

Conclusion: By adding radiation therapy data into the clinical data warehouse, we were able to analyze radiation therapy response in cancer patients and we have leveraged the i2b2 platform to store radiation therapy data, including detailed information such as the DVH to create new ontology-based modules that provides research investigators with a wider spectrum of clinical data.

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Conflict of interest statement

None.

Figures

Fig. 1
Fig. 1
The integration pipeline of the radiation therapy data into the Hôpital Européen Georges Pompidou (HEGP) Informatics for Integrating Biology and the Bedside (i2b2) clinical data warehouse.
Fig. 2
Fig. 2
The Business Objects Universe created to validate the integration of radiation therapy data into the Hôpital Européen Georges Pompidou (HEGP) Informatics for Integrating Biology and the Bedside (i2b2) clinical data warehouse (CDW).
Fig. 3
Fig. 3
Partial view of the “Dose details” screen of the vendor's radiation therapy application.
Fig. 4
Fig. 4
Business Objects dashboard created to validate the “Dose details” data integration into Informatics for Integrating Biology and the Bedside (i2b2). This dashboard is replicating the vendor's application screen.
Fig. 5
Fig. 5
Modelization of the dose-volume histogram (DVH) data integrated into the Hôpital Européen Georges Pompidou (HEGP) Informatics for Integrating Biology and the Bedside (i2b2) clinical data warehouse (CDW).
Fig. 6
Fig. 6
Output of the R script displaying radiation therapy data extracted from the Hôpital Européen Georges Pompidou (HEGP) Informatics for Integrating Biology and the Bedside (i2b2) clinical data warehouse (CDW).
Fig. 7
Fig. 7
The Radiation Oncology Structures as displayed in the Informatics for Integrating Biology and the Bedside (i2b2) Web client.

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