Evidence map›Paper›PMID 31444952›Full record

ArticleJournal of applied clinical medical physics2019

Evaluation of a simplified optimizer for MR-guided adaptive RT in case of pancreatic cancer.

Davide Cusumano, Luca Boldrini, Sebastiano Menna, Stefania Teodoli, Elisa Placidi, Giuditta Chiloiro, Lorenzo Placidi, Francesca Greco, Gerardina Stimato, Francesco Cellini and 3 more

Abstract readEvaluation Study
In one paragraph

Article in Journal of applied clinical medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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  3. Review
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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

13 authors.

Davide CusumanoDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Luca BoldriniDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Sebastiano MennaDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Stefania TeodoliDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Elisa PlacidiDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Giuditta ChiloiroDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Lorenzo PlacidiDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Francesca GrecoDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Gerardina StimatoDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Francesco CelliniDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Vincenzo ValentiniDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Luigi AzarioDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.
Marco De SpiritoDipartimento di diagnostica per immagini, radioterapia oncologica ed ematologia, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Roma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMagnetic resonance-guided adaptive radiotherapy (MRgART) is considered a promising resource for pancreatic cancer, as it allows to online modify the dose distribution according to daily anatomy. This study aims to compare the dosimetric performance of a simplified optimizer implemented on a MR-Linac treatment planning system (TPS) with those obtained using an advanced optimizer implemented on a conventional Linac.

methodsTwenty patients affected by locally advanced pancreatic cancer (LAPC) were considered. Gross tumor volume (GTV) and surrounding organ at risks (OARs) were contoured on the average 4DCT scan. Planning target volume was generated from GTV by adding an isotropic 3 mm margin and excluding overlap areas with OARs. Treatment plans were generated by using the simple optimizer for the MR-Linac in intensity-modulated radiation therapy (IMRT) and the advanced optimizer for conventional Linac in IMRT and volumetric modulated arc therapy (VMAT) technique. Prescription dose was 40 Gy in five fractions. The dosimetric comparison was performed on target coverage, dosimetric indicators, and low dose diffusion.

resultsThe simplified optimizer of MR-Linac generated clinically acceptable plans in 80% and optimal plans in 55% of cases. The number of clinically acceptable plans obtained using the advanced optimizer of the conventional Linac with IMRT was the same of MR-Linac, but the percentage of optimal plans was higher (65%). Using the VMAT technique, it is possible to obtain clinically acceptable plan in 95% and optimal plans in 90% of cases. The advanced optimizer combined with VMAT technique ensures higher target dose homogeneity and minor diffusion of low doses, but its actual optimization time is not suitable for MRgART.

conclusionSimplified optimization solutions implemented in the MR-Linac TPS allows to elaborate in most of cases treatment plans dosimetrically comparable with those obtained by using an advanced optimizer. A superior treatment plan quality is possible using the VMAT technique that could represent a breakthrough for the MRgART if the modern advancements will lead to shorter optimization times.

Indexed as

AlgorithmsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingOrgans at RiskPancreatic NeoplasmsParticle AcceleratorsRadiotherapy DosageRadiotherapy, Image-GuidedRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedIMRTMR-guided Radiotherapyonline adaptive radiotherapypancreatic cancerplan optimization

Identifiers

PMID31444952
PMCPMC6753732

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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.