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Toward Data-Driven Radiation Oncology Using Standardized Terminology as a Starting Point: Cross-sectional Study
Nikola Cihoric1, Eugenia Vlaskou Badra2, Anna Stenger-Weisser1,3
1Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
JMIR Formative Research
|January 19, 2022
Summary
Current terminology resources are insufficient for modern radiation oncology, hindering data-driven practice. A new, standardized terminology resource is needed for improved semantic interoperability in radiation therapy.
Area of Science:
- Medical Informatics
- Oncology
- Health Informatics
Background:
- Seamless information exchange is crucial for data-driven radiation therapy.
- Semantic interoperability is essential for advancing personalized and precision medicine in oncology.
- Current limitations hinder the full potential of AI and advanced algorithms in radiation oncology.
Purpose of the Study:
- To evaluate existing terminology resources (TRs) for radiation oncology.
- To assess the current state of radiation therapy-specific terminology.
- To identify prerequisites for establishing a comprehensive oncology semantic ecosystem.
Main Methods:
- Searched the Unified Medical Language System (UMLS) for radiation oncology and therapy terms.
- Extracted and analyzed 6509 unique concepts from 35 source vocabularies (SVs).
- Quantitatively assessed SVs based on origin, author, license, lexical density, and semantic types.
Main Results:
- No dedicated TRs for radiation oncology were identified.
- A small number of SVs (14%) contained the majority (94.59%) of concepts.
- Many SVs lacked clear usage rights (54%) or had not been updated recently (43%).
Conclusions:
- Existing terminologies are inadequate for modern radiation oncology practice and research.
- A new, standardized, and universally accepted TR for radiation therapy is required.
- Developing such a TR is essential for achieving sufficient semantic interoperability.
