Evidence map›Paper›PMID 42365440›Full record

ArticleMedical physics2026

Monte Carlo assessment of a treatment planning system for intraoperative radiotherapy in the presence of tissue heterogeneities.

Aurora Corso, F Javier Jimenez-Albericio, Michele Avanzo, Pablo Ortega-Pardina, Roberto Cirio, Daniel Vera-Tena, Elena Gonzalez-Gonzalez, Alejandro Garcia-Romero

Abstract read
In one paragraph

Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

8 authors.

Aurora CorsoUniversity of Turin, Turin, Italy.
F Javier Jimenez-AlbericioHospital Clinico Universitario "Lozano Blesa" de Zaragoza, Zaragoza, Spain.
Michele AvanzoCentro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy.
Pablo Ortega-PardinaHospital Clinico Universitario "Lozano Blesa" de Zaragoza, Zaragoza, Spain.
Roberto CirioUniversity of Turin, Turin, Italy.
Daniel Vera-TenaHospital Clinico Universitario "Lozano Blesa" de Zaragoza, Zaragoza, Spain.
Elena Gonzalez-GonzalezHospital Clinico Universitario "Lozano Blesa" de Zaragoza, Zaragoza, Spain.
Alejandro Garcia-RomeroHospital Clinico Universitario "Lozano Blesa" de Zaragoza, Zaragoza, Spain.

Funding

Universidad de Zaragoza Academic Library
6 · The paper itself

Abstract

backgroundRadiance is a Monte Carlo-based treatment planning software integrated into the Intrabeam system for 50-kVp X-rays intraoperative radiotherapy (IORT). PURPOSE: This study evaluates Radiance accuracy in calculating absorbed dose in IORT of the breast including the effect of tissue heterogeneities.

methodsDose distributions from IORT were calculated in 88 virtual phantoms of different tissue-equivalent materials. Dose was calculated independently using the penEasy code for the PENELOPE Monte Carlo engine and compared to Radiance. Depth dose curves (DDCs) were compared through gamma analysis using 5%/0.5 mm and 3%/0.5 mm criteria.

resultsWhen comparing Radiance vs penEasy all passing rates were above 95%. Notable differences from dose to water emerged for some tissues: cortical bone absorbed about four times more than water, while adipose tissue received about 45% less. These variations were affected by atomic number more than density.

conclusionRadiance results show strong agreement with penEasy simulations. Furthermore, it was observed that IORT absorbed doses can fluctuate by ± 50% due to heterogeneities surrounding the applicator. This highlights that the prescribed dose and the absorbed dose in the applicator surface do not necessarily coincide in non-water tissues, emphasizing the critical need to account for specific tissue characteristics during treatment planning.

Indexed as

Monte Carlo MethodRadiotherapy Planning, Computer-AssistedBreast NeoplasmsHumansIntraoperative PeriodPhantoms, ImagingRadiotherapy DosageheterogeneitiesIORTMonte Carlo

Identifiers

PMID42365440
PMCPMC13310351

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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.