Evidence map›Paper›PMID 32124546›Full record

ReviewMolecular oncology2020

Technology-driven research for radiotherapy innovation.

Claudio Fiorino, Matthias Guckemberger, Marco Schwarz, Uulke A van der Heide, Ben Heijmen

Abstract readReview
In one paragraph

Review in Molecular oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
–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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Between hope and uncertainty: the elusive evidence on hyperbaric oxygen therapy and radiotherapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. The Value of Radiation Therapists in Online Adaptive Radiotherapy.Journal of medical radiation sciences · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Training for tomorrow: Establishing a worldwide curriculum in online adaptive radiation therapy.Technical innovations & patient support in radiation oncology · 2025
    Article
  18. Review
  19. Review
  20. Article
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

5 authors.

Claudio FiorinoMedical Physics, San Raffaele Scientific Institute, Milano, Italy.ORCID 0000-0002-0013-8494
Matthias GuckembergerDepartment of Radiation Oncology, University Hospital Zurich, University of Zurich, Switzerland.
Marco SchwarzProtontherapy Department, Trento Hospital and TIFPA-INFN, Trento, Italy.
Uulke A van der HeideDepartment of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Ben HeijmenDepartment of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technology has a pivotal role in the continuous development of radiotherapy. The long road toward modern 'high-tech' radiation oncology has been studded with discoveries and technological innovations that resulted from the interaction of various disciplines. In the last decades, a dramatic technology-driven revolution has hugely improved the capability of accurately and safely delivering complex-shaped dose distributions. This has contributed to many clinical improvements, such as the successful management of lung cancer and oligometastatic disease through stereotactic body radiotherapy. Technology-driven research is an active and lively field with promising potential in several domains, including image guidance, adaptive radiotherapy, integration of artificial intelligence, heavy-particle therapy, and 'flash' ultra-high dose-rate radiotherapy. The evolution toward personalized Oncology will deeply influence technology-driven research, aiming to integrate predictive models and omics analyses into fast and efficient solutions to deliver the best treatment for each single patient. Personalized radiation oncology will need affordable technological solutions for middle-/low-income countries, as these are expected to experience the highest increase of cancer incidence and mortality. Moreover, technology solutions for automation of commissioning, quality assurance, safety tests, image segmentation, and plan optimization will be required. Although a large fraction of cancer patients receive radiotherapy, this is certainly not reflected in the worldwide budget for radiotherapy research. Differently from the pharmaceutical companies-driven research, resources for research in radiotherapy are highly limited to equipment vendors, who can, in turn, initiate a limited number of collaborations with academic research centers. Thus, enhancement of investments in technology-driven radiotherapy research via public funds, national governments, and the European Union would have a crucial societal impact. It would allow for radiotherapy to further strengthen its role as a highly effective and cost-efficient cancer treatment modality, and it could facilitate a rapid and equalitarian large-scale transfer of technology to clinic, with direct impact on patient care.

Indexed as

Biomedical ResearchInventionsRadiotherapyArtificial IntelligenceBig DataHumansPrecision Medicineadaptive radiotherapyinnovationpersonalized medicineRadiation Oncologyradiotherapyresearchtechnology

Identifiers

PMID32124546
PMCPMC7332218

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.