Evidence map›Paper›PMID 38977432›Full record

ArticleStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]2024

Effect of different optimization parameters in single isocenter multiple brain metastases radiosurgery.

Angelika Altergot, Carsten Ohlmann, Frank Nüsken, Jan Palm, Markus Hecht, Yvonne Dzierma

Abstract read
In one paragraph

Article in Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al], 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Angelika AltergotDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany. angelika.altergot@uks.eu.
Carsten OhlmannDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany.
Frank NüskenDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany.
Jan PalmDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany.
Markus HechtDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany.
Yvonne DziermaDepartment of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Kirrberger Straße, Homburg/Saar, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAutomated treatment planning for multiple brain metastases differs from traditional planning approaches. It is therefore helpful to understand which parameters for optimization are available and how they affect the plan quality. This study aims to provide a reference for designing multi-metastases treatment plans and to define quality endpoints for benchmarking the technique from a scientific perspective.

methodsIn all, 20 patients with a total of 183 lesions were retrospectively planned according to four optimization scenarios. Plan quality was evaluated using common plan quality parameters such as conformity index, gradient index and dose to normal tissue. Therefore, different scenarios with combinations of optimization parameters were evaluated, while taking into account dependence on the number of treated lesions as well as influence of different beams.

resultsDifferent scenarios resulted in minor differences in plan quality. With increasing number of lesions, the number of monitor units increased, so did the dose to healthy tissue and the number of interlesional dose bridging in adjacent metastases. Highly modulated cases resulted in 4-10% higher V

conclusionAlthough no clinically relevant differences in parameters where found, we identified some variation in the dose distributions of the different scenarios. Less complex scenarios generated visually more dose overlap; therefore, a more complex scenario may be preferred although differences in the quality metrics appear minor.

Indexed as

Brain NeoplasmsRadiosurgeryRadiotherapy DosageRadiotherapy Planning, Computer-AssistedHumansRetrospective StudiesBrain neoplasmsElements Multiple Brain MetsFlat vs FFF beamsGradient indexPlan complexity

Identifiers

PMID38977432
PMCPMC11343813

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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.