Technical note: A knowledge graph approach to registering tumour specific data of patient-candidates for proton therapy in the Netherlands

The registration of multi-source radiation oncology data is a time-consuming and labour-intensive procedure. The standardisation of data collection offers the possibility for the acquisition of quality data for research and clinical purposes. With this study, we present an overview of the different tumour group data lists in the Dutch national proton therapy registry. Furthermore, as a representative example of the workings of these different tumour-specific knowledge graphs, we present the FAIR (Findable, Accessible, Interoperable, Reusable) data principles-compliant knowledge graph approach describing the head and neck tumour variables using radiotherapy domain ontologies and semantic web technologies. Our goal is to provide the radiotherapy community with a flexible and interoperable data model for data exchange between centres. We highlight data variables that are needed for models used in the model-based approach (MBA), which ensures a fair selection of patients that will benefit most from proton therapy.

Automated summary

This study provides an overview of the tumour group data lists in the Dutch national proton therapy registry, and presents a knowledge graph approach using ontologies and semantic web technologies to describe head and neck tumour variables. The goal is to offer a flexible and interoperable data model for data exchange in the radiotherapy community, highlighting variables needed for the model-based approach.