Translational barriers to digital twins in radiation oncology
Federico Mastroleo1,2,3, Mariana Borras-Osorio1, Shiv P Patel1
1Department of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
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Digital twin research in radiation oncology has expanded rapidly across multiple domains, yet the field lacks definitional consensus and validated translational frameworks. A systematic search (PubMed, Scopus and Web of Science - September 2025) identified 903 records and six original studies met inclusion criteria. Appraisal of the available original studies revealed three recurring translational barriers: misuse of the term "digital twin" for virtual humans or patient-specific predictive models; overreliance on internal or in-silico validation; and limited benchmarking against clinically established alternatives. Progress toward clinical translation requires disciplined nomenclature, real-patient external validation, head-to-head benchmarking, explicit attention to data-pipeline and regulatory pathways.
