Evidence map›Paper›PMID 35087746›Full record

ArticleFrontiers in oncology2021

Adaptive MR-Guided Stereotactic Radiotherapy is Beneficial for Ablative Treatment of Lung Tumors in High-Risk Locations.

Sebastian Regnery, Carolin Buchele, Fabian Weykamp, Moritz Pohl, Philipp Hoegen, Tanja Eichkorn, Thomas Held, Jonas Ristau, Carolin Rippke, Laila König and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 37 citations in OpenAlex.

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  8. MR-guided online adaptive stereotactic body radiotherapy (MRgSBRT) of primary lung tumors and lung oligometastases.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025
    Article
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  10. MR-linac: role of artificial intelligence and automation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025
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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

16 authors at 5 institutions in 1 country.

Sebastian RegneryDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Carolin BucheleDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Fabian WeykampDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Moritz PohlInstitute of Medical Biometry, University of Heidelberg, Heidelberg, Germany.
Philipp HoegenDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Tanja EichkornDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Thomas HeldDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Jonas RistauDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Carolin RippkeDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Laila KönigDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Michael ThomasNational Center for Tumor diseases, Heidelberg, Germany.
Hauke WinterNational Center for Tumor diseases, Heidelberg, Germany.
Sebastian AdebergDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Jürgen DebusDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Sebastian KlüterDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Juliane Hörner-RieberDepartment of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
University Hospital Heidelberg · DEHeidelberg University · DENational Center for Tumor Diseases · DEGerman Cancer Research Center · DEZimmer Biomet (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo explore the benefit of adaptive magnetic resonance-guided stereotactic body radiotherapy (MRgSBRT) for treatment of lung tumors in different locations with a focus on ultracentral lung tumors (ULT). PATIENTS &

methodsA prospective cohort of 21 patients with 23 primary and secondary lung tumors was analyzed. Tumors were located peripherally (N = 10), centrally (N = 2) and ultracentrally (N = 11, planning target volume (PTV) overlap with proximal bronchi, esophagus and/or pulmonary artery). All patients received MRgSBRT with gated dose delivery and risk-adapted fractionation. Before each fraction, the baseline plan was recalculated on the anatomy of the day (predicted plan). Plan adaptation was performed in 154/165 fractions (93.3%). Comparison of dose characteristics between predicted and adapted plans employed descriptive statistics and Bayesian linear multilevel models. The posterior distributions resulting from the Bayesian models are presented by the mean together with the corresponding 95% compatibility interval (CI).

resultsPlan adaptation decreased the proportion of fractions with violated planning objectives from 94% (predicted plans) to 17% (adapted plans). In most cases, inadequate PTV coverage was remedied (predicted: 86%, adapted: 13%), corresponding to a moderate increase of PTV coverage (mean +6.3%, 95% CI: [5.3-7.4%]) and biologically effective PTV doses (BED

conclusionAdaptive MRgSBRT is highly recommendable for ablative treatment of lung tumors whose PTV initially contacts a sensitive OAR, such as ULT. Here, plan adaptation protects the OAR while maintaining best-possible PTV coverage.

Indexed as

image-guidancemagnetic resonance imagingMR-guided radiotherapypulmonary cancerradiotherapystereotactic body radiotherapy

Identifiers

PMID35087746
PMCPMC8789303
OpenAlexW4205736478

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.