Evidence map›Paper›PMID 42204770›Full record

ArticleJournal of applied clinical medical physics2026

Retrospective analysis of adaptation frequencies and factors in offline in offline adaptive proton therapy.

Farideh Pak, Hailei Zhang, Yao Hao, Matthew Schmidt, Weiren Liu, Joshua Schiff, Eric Laugeman, Michael Watts, Stephanie Perkins, Tianyu Zhao

Erratum issuedAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Farideh PakDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Hailei ZhangDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Yao HaoDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-5277-7271
Matthew SchmidtDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.ORCID https://orcid.org/0000-0003-3357-6703
Weiren LiuDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Joshua SchiffDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Eric LaugemanDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Michael WattsDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Stephanie PerkinsDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.
Tianyu ZhaoDepartment of Radiation Oncology, School of Medicine, Washington University in St. Louis, Saint Louis, Missouri, USA.

Funding

Siteman Cancer Center
6 · The paper itself

Abstract

PURPOSE/

objectiveOffline adaptation is a standard practice in radiation therapy to adjust treatment plans for various reasons. Although offline adaptation in proton therapy has been addressed in prior studies, further research is still needed to clarify the underlying reasons. Because of the unique dosimetric properties of protons, it is essential to know why and when offline adaptation is needed. In this retrospective study, in-room CT-on-Rails (CToR) scans were used to characterize the reasons and frequency of offline adaptive proton therapy for head and neck (HN), breast or chest wall (breast/CW), and prostate cases. MATERIALS/

methodsA cohort of 166 cases receiving proton therapy from 2020 to 2023 were reviewed retrospectively, including 76 HN cases, 50 breast/CW, and 40 prostate cases. The imaging frequency and incidence of replanning were recorded, and the rationales for replanning were investigated through anatomic review, dose volume histogram (DVH) comparison, and dose evaluations.

resultsOverall, replanning occurred in 11% of all the cases, with 13% of HN and 16% of breast/CW cases needing replanning. No prostate cases required replanning. HN cases were planned in 20 to 33 fractions, and no timing pattern of replanning emerged. Breast/CW were planned in 16 to 25 fractions, with replanning peaking at fractions 3-6 and 14 and again at 17. Anatomy changes most frequently triggered offline adaptation for HN cases, while more offline adaptation in breast/CW cases were due to displacement of tissue expander magnets.

conclusionThis study uncovered different trends in the rationale for offline adaptation in proton therapy. HN cancer patients were more likely to need adaptation due to anatomy changes whereas breast/CW patients more often needed adaptation due to tissue expander magnet migration. Prostate cases showed stable treatment plans and dose distribution through the treatment course.

Indexed as

Breast NeoplasmsHead and Neck NeoplasmsProstatic NeoplasmsProton TherapyRadiotherapy Planning, Computer-AssistedFemaleHumansMaleOrgans at RiskPrognosisRadiotherapy DosageRadiotherapy, Intensity-ModulatedRetrospective Studiesadaptivebreast and chest wallhead and neckprostateproton therapy

Identifiers

PMID42204770
PMCPMC13239404

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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.