Evidence map›Paper›PMID 29698534›Full record

ArticlePloS one2018

Impact of different biologically-adapted radiotherapy strategies on tumor control evaluated with a tumor response model.

Araceli Gago-Arias, Beatriz Sánchez-Nieto, Ignacio Espinoza, Christian P Karger, Juan Pardo-Montero

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

5 authors.

Araceli Gago-AriasInstituto de Física, Pontificia Universidad Católica de Chile, Santiago, Chile.ORCID 0000-0002-1999-2340
Beatriz Sánchez-NietoInstituto de Física, Pontificia Universidad Católica de Chile, Santiago, Chile.
Ignacio EspinozaInstituto de Física, Pontificia Universidad Católica de Chile, Santiago, Chile.
Christian P KargerNational Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany.
Juan Pardo-MonteroGrupo de Imaxe Molecular, Instituto de Investigación Sanitaria (IDIS), Santiago de Compostela, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivated by the capabilities of modern radiotherapy techniques and by the recent developments of functional imaging techniques, dose painting by numbers (DPBN) was proposed to treat tumors with heterogeneous biological characteristics. This work studies different DPBN optimization techniques for virtual head and neck tumors assessing tumor response in terms of cell survival and tumor control probability with a previously published tumor response model (TRM). Uniform doses of 2 Gy are redistributed according to the microscopic oxygen distribution and the density distribution of tumor cells in four virtual tumors with different biological characteristics. In addition, two different optimization objective functions are investigated, which: i) minimize tumor cell survival (OFsurv) or; ii) maximize the homogeneity of the density of surviving tumor cells (OFstd). Several adaptive schemes, ranging from single to daily dose optimization, are studied and the treatment response is compared to that of the uniform dose. The results show that the benefit of DPBN treatments depends on the tumor reoxygenation capability, which strongly differed among the set of virtual tumors investigated. The difference between daily (fraction by fraction) and three weekly optimizations (at the beginning of weeks 1, 3 and 4) was found to be small, and higher benefit was observed for the treatments optimized using OFsurv. This in silico study corroborates the hypothesis that DPBN may be beneficial for treatments of tumors which show reoxygenation during treatment, and that a few optimizations may be sufficient to achieve this therapeutic benefit.

Indexed as

Cell SurvivalComputer SimulationDose-Response Relationship, RadiationHead and Neck NeoplasmsHumansHypoxiaImage Processing, Computer-AssistedLinear ModelsOxygenProbabilityRadiotherapyRadiotherapy DosageRadiotherapy Planning, Computer-AssistedTime FactorsOxygen

Identifiers

PMID29698534
PMCPMC5919644

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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.