Evidence map›Paper›PMID 42436731›Full record

ArticlePhysics and imaging in radiation oncology2026

Translational barriers to digital twins in radiation oncology.

Federico Mastroleo, Mariana Borras-Osorio, Shiv P Patel, David M Routman, Doug J Moseley, Satomi Shiraishi, Andrew Y K Foong, Mark R Waddle

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Physics and imaging in radiation oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Federico MastroleoDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Mariana Borras-OsorioDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Shiv P PatelDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
David M RoutmanDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Doug J MoseleyDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Satomi ShiraishiDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Andrew Y K FoongDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.
Mark R WaddleDepartment of Radiation Oncology, Mayo Clinic, Rochester, MN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Clinical translationDigital twinsPredictive modelingRadiation oncologyValidation

Identifiers

PMID42436731
PMCPMC13355216

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.