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Record W2222153634 · doi:10.1088/0031-9155/58/8/e01

Special section: Selected papers from the Third European Workshop on Monte Carlo Treatment Planning (MCTP2012)

2013· editorial· en· W2222153634 on OpenAlexaboutno aff
Emiliano Spezi, Antonio Leal

Bibliographic record

VenuePhysics in Medicine and Biology · 2013
Typeeditorial
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMonte Carlo methodWorkgroupLibrary scienceEvent (particle physics)Section (typography)Computer scienceOperations researchPhysicsEngineeringMathematicsStatistics

Abstract

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The Third European Workshop on Monte Carlo Treatment Planning (MCTP2012) was held from 15–18 May, 2012 in Seville, Spain. The event was organized by the Universidad de Sevilla with the support of the European Workgroup on Monte Carlo Treatment Planning (EWG-MCTP). MCTP2012 followed two successful meetings, one held in Ghent (Belgium) in 2006 (Reynaert 2007) and one in Cardiff (UK) in 2009 (Spezi 2010). The recurrence of these workshops together with successful events held in parallel by McGill University in Montreal (Seuntjens et al 2012), show consolidated interest from the scientific community in Monte Carlo (MC) treatment planning. The workshop was attended by a total of 90 participants, mainly coming from a medical physics background. A total of 48 oral presentations and 15 posters were delivered in specific scientific sessions including dosimetry, code development, imaging, modelling of photon and electron radiation transport, external beam radiation therapy, nuclear medicine, brachitherapy and hadrontherapy. A copy of the programme is available on the workshop's website ( www.mctp2012.com ). In this special section of Physics in Medicine and Biology we report six papers that were selected following the journal's rigorous peer review procedure. These papers actually provide a good cross section of the areas of application of MC in treatment planning that were discussed at MCTP2012. Czarnecki and Zink (2013) and Wagner et al (2013) present the results of their work in small field dosimetry. Czarnecki and Zink (2013) studied field size and detector dependent correction factors for diodes and ion chambers within a clinical 6MV photon beam generated by a Siemens linear accelerator. Their modelling work based on the BEAMnrc/EGSnrc codes and experimental measurements revealed that unshielded diodes were the best choice for small field dosimetry because of their independence from the electron beam spot size and correction factor close to unity. Wagner et al (2013) investigated the recombination effect on liquid ionization chambers for stereotactic radiotherapy, a field of increasing importance in external beam radiotherapy. They modelled both radiation source (Cyberknife unit) and detector with the BEAMnrc/EGSnrc codes and quantified the dependence of the response of this type of detectors on factors such as the volume effect and the electrode. They also recommended that these dependences be accounted for in measurements involving small fields. In the field of external beam radiotherapy, Chakarova et al (2013) showed how total body irradiation (TBI) could be improved by simulating patient treatments with MC. In particular, BEAMnrc/EGSnrc based simulations highlighted the importance of optimizing individual compensators for TBI treatments. In the same area of application, Mairani et al (2013) reported on a new tool for treatment planning in proton therapy based on the FLUKA MC code. The software, used to model both proton therapy beam and patient anatomy, supports single-field and multiple-field optimization and can be used to optimize physical and relative biological effectiveness (RBE)-weighted dose distribution, using both constant and variable RBE models. In the field of nuclear medicine Marcatili et al (2013) presented RAYDOSE, a Geant4-based code specifically developed for applications in molecular radiotherapy (MRT). RAYDOSE has been designed to work in MRT trials using sequential positron emission tomography (PET) or single-photon emission tomography (SPECT) imaging to model patient specific time-dependent metabolic uptake and to calculate the total 3D dose distribution. The code was validated through experimental measurements in homogeneous and heterogeneous phantoms. Finally, in the field of code development Miras et al (2013) reported on CloudMC, a Windows Azure-based application for the parallelization of MC calculations in a dynamic cluster environment. Although the performance of CloudMC has been tested with the PENELOPE MC code, the authors report that software has been designed in a way that it should be independent of the type of MC code, provided that simulation meets a number of operational criteria. We wish to thank Elekta/CMS Inc., the University of Seville, the Junta of Andalusia and the European Regional Development Fund for their financial support. We would like also to acknowledge the members of EWG-MCTP for their help in peer-reviewing all the abstracts, and all the invited speakers who kindly agreed to deliver keynote presentations in their area of expertise. A final word of thanks to our colleagues who worked on the reviewing process of the papers selected for this special section and to the IOP Publishing staff who made it possible. MCTP2012 was accredited by the European Federation of Organisations for Medical Physics as a CPD event for medical physicists. Emiliano Spezi and Antonio Leal Guest Editors References Chakarova R, Müntzing K, Krantz M, E Hedin E and Hertzman S 2013 Monte Carlo optimization of total body irradiation in a phantom and patient geometry Phys. Med. Biol. 58 2461–69 Czarnecki D and Zink K 2013 Monte Carlo calculated correction factors for diodes and ion chambers in small photon fields Phys. Med. Biol. 58 2431–44 Mairani A, Böhlen T T, Schiavi A, Tessonnier T, Molinelli S, Brons S, Battistoni G, Parodi K and Patera V 2013 A Monte Carlo-based treatment planning tool for proton therapy Phys. Med. Biol. 58 2471–90 Marcatili S, Pettinato C, Daniels S, Lewis G, Edwards P, Fanti S and Spezi E 2013 Development and validation of RAYDOSE: a Geant4 based application for molecular radiotherapy Phys. Med. Biol. 58 2491–508 Miras H, Jiménez R, Miras C and Gomà C 2013 CloudMC: A cloud computing application for Monte Carlo simulation Phys. Med. Biol. 58 N125–33 Reynaert N 2007 First European Workshop on Monte Carlo Treatment Planning J. Phys.: Conf. Ser. 74 011001 Seuntjens J, Beaulieu L, El Naqa I and Després P 2012 Special section: Selected papers from the Fourth International Workshop on Recent Advances in Monte Carlo Techniques for Radiation Therapy Phys. Med. Biol. 57 (11) E01 Spezi E 2010 Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) Phys. Med. Biol. 55 (16) E01 Wagner A, Crop F, Lacornerie T, Vandevelde F and Reynaert N 2013 Use of a liquid ionization chamber for stereotactic radiotherapy dosimetry Phys. Med. Biol. 58 2445–59

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.003
Science and technology studies0.0020.002
Scholarly communication0.0080.004
Open science0.0030.002
Research integrity0.0110.014
Insufficient payload (model declined to judge)0.0290.023

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.111
GPT teacher head0.380
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2013
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