Evidence map›Paper›PMID 38539540›Full record

ReviewCancers2024

Adaptive Radiotherapy: Next-Generation Radiotherapy.

Olga Maria Dona Lemus, Minsong Cao, Bin Cai, Michael Cummings, Dandan Zheng

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 pooled it
58.3field-weighted citation impact, top 1% of its field
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

80 citing papers in PubMed, 1 synthesis or guideline pooled it, 96 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Review
  6. Article
  7. Review
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  9. Article
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  12. Adaptive radiotherapy incident-informed team training: a development and feasibility study.Technical innovations & patient support in radiation oncology · 2026
    Article
  13. Review
  14. Article
  15. Review
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  18. Article
  19. Review
  20. Article

20 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 1 country.

Olga Maria Dona LemusDepartment of Radiation Oncology, University of Rochester, Rochester, NY 14642, USA.
Minsong CaoDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, CA 90095, USA.
Bin CaiDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Michael CummingsDepartment of Radiation Oncology, University of Rochester, Rochester, NY 14642, USA.
Dandan ZhengDepartment of Radiation Oncology, University of Rochester, Rochester, NY 14642, USA.ORCID 0000-0003-2259-1633
University of Rochester · USThe University of Texas Southwestern Medical Center · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiotherapy, a crucial technique in cancer therapy, has traditionally relied on the premise of largely unchanging patient anatomy during the treatment course and encompassing uncertainties by target margins. This review introduces adaptive radiotherapy (ART), a notable innovation that addresses anatomy changes and optimizes the therapeutic ratio. ART utilizes advanced imaging techniques such as CT, MRI, and PET to modify the treatment plan based on observed anatomical changes and even biological changes during the course of treatment. The narrative review provides a comprehensive guide on ART for healthcare professionals and trainees in radiation oncology and anyone else interested in the topic. The incorporation of artificial intelligence in ART has played a crucial role in improving effectiveness, particularly in contour segmentation, treatment planning, and quality assurance. This has expedited the process to render online ART feasible, lowered the burden for radiation oncology practitioners, and enhanced the precision of dynamically personalized treatment. Current technical and clinical progress on ART is discussed in this review, highlighting the ongoing development of imaging technologies and AI and emphasizing their contribution to enhancing the applicability and effectiveness of ART.

Indexed as

adaptive radiotherapyadaptive replanningCBCTIGRTMRgRTpersonalized medicinePETtreatment adaptation

Identifiers

PMID38539540
PMCPMC10968833
OpenAlexW4393005901

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.