DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF
Introduction<p>External beam radiotherapy (RT) is one of the most common treatments against cancer, with photon-based RT and particle therapy being commonly employed modalities. Very high energy electrons (VHEE) have emerged as promising candidates for novel treatments, particularly in exploit...
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2024
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| _version_ | 1852025083254538240 |
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| author | Lorenzo Arsini (15083796) |
| author2 | Barbara Caccia (3485909) Andrea Ciardiello (20293485) Angelica De Gregorio (20293488) Gaia Franciosini (20293491) Stefano Giagu (8315949) Susanna Guatelli (8359746) Annalisa Muscato (20293494) Francesca Nicolanti (20293497) Jason Paino (20084220) Angelo Schiavi (9571904) Carlo Mancini-Terracciano (20293500) |
| author2_role | author author author author author author author author author author author |
| author_facet | Lorenzo Arsini (15083796) Barbara Caccia (3485909) Andrea Ciardiello (20293485) Angelica De Gregorio (20293488) Gaia Franciosini (20293491) Stefano Giagu (8315949) Susanna Guatelli (8359746) Annalisa Muscato (20293494) Francesca Nicolanti (20293497) Jason Paino (20084220) Angelo Schiavi (9571904) Carlo Mancini-Terracciano (20293500) |
| author_role | author |
| dc.creator.none.fl_str_mv | Lorenzo Arsini (15083796) Barbara Caccia (3485909) Andrea Ciardiello (20293485) Angelica De Gregorio (20293488) Gaia Franciosini (20293491) Stefano Giagu (8315949) Susanna Guatelli (8359746) Annalisa Muscato (20293494) Francesca Nicolanti (20293497) Jason Paino (20084220) Angelo Schiavi (9571904) Carlo Mancini-Terracciano (20293500) |
| dc.date.none.fl_str_mv | 2024-11-20T04:02:49Z |
| dc.identifier.none.fl_str_mv | 10.3389/fphy.2024.1443306.s001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/DataSheet1_Fast_and_precise_dose_estimation_for_very_high_energy_electron_radiotherapy_with_graph_neural_networks_PDF/27859992 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biophysics Astrophysics Applied Physics Computational Physics Condensed Matter Physics Particle Physics Plasma Physics Solar System, Solar Physics, Planets and Exoplanets Classical and Physical Optics Photonics, Optoelectronics and Optical Communications Cloud Physics Tropospheric and Stratospheric Physics High Energy Astrophysics; Cosmic Rays Mesospheric, Ionospheric and Magnetospheric Physics Space and Solar Physics Mathematical Physics not elsewhere classified Physical Chemistry of Materials Physical Chemistry not elsewhere classified Classical Physics not elsewhere classified Condensed Matter Physics not elsewhere classified Quantum Physics not elsewhere classified VHEE radiotherapy dose engine deep learning flash very high energy electrons Monte Carlo |
| dc.title.none.fl_str_mv | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | Introduction<p>External beam radiotherapy (RT) is one of the most common treatments against cancer, with photon-based RT and particle therapy being commonly employed modalities. Very high energy electrons (VHEE) have emerged as promising candidates for novel treatments, particularly in exploiting the FLASH effect, offering potential advantages over traditional modalities.</p>Methods<p>This paper introduces a Deep Learning model based on graph convolutional networks to determine dose distributions of therapeutic VHEE beams in patient tissues. The model emulates Monte Carlo (MC) simulated doses within a cylindrical volume around the beam, enabling high spatial resolution dose calculation along the beamline while managing memory constraints.</p>Results<p>Trained on diverse beam orientations and energies, the model exhibits strong generalization to unseen configurations, achieving high accuracy metrics, including a δ-index 3% passing rate of 99.8% and average relative error <1% in integrated dose profiles compared to MC simulations.</p>Discussion<p>Notably, the model offers three to six orders of magnitude increased speed over full MC simulations and fast MC codes, generating dose distributions in milliseconds on a single GPU. This speed could enable direct integration into treatment planning optimization algorithms and leverage the model’s differentiability for exact gradient computation.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_21a0ca84a2fc629fceaaa0c736f1ffce |
| identifier_str_mv | 10.3389/fphy.2024.1443306.s001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/27859992 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDFLorenzo Arsini (15083796)Barbara Caccia (3485909)Andrea Ciardiello (20293485)Angelica De Gregorio (20293488)Gaia Franciosini (20293491)Stefano Giagu (8315949)Susanna Guatelli (8359746)Annalisa Muscato (20293494)Francesca Nicolanti (20293497)Jason Paino (20084220)Angelo Schiavi (9571904)Carlo Mancini-Terracciano (20293500)BiophysicsAstrophysicsApplied PhysicsComputational PhysicsCondensed Matter PhysicsParticle PhysicsPlasma PhysicsSolar System, Solar Physics, Planets and ExoplanetsClassical and Physical OpticsPhotonics, Optoelectronics and Optical CommunicationsCloud PhysicsTropospheric and Stratospheric PhysicsHigh Energy Astrophysics; Cosmic RaysMesospheric, Ionospheric and Magnetospheric PhysicsSpace and Solar PhysicsMathematical Physics not elsewhere classifiedPhysical Chemistry of MaterialsPhysical Chemistry not elsewhere classifiedClassical Physics not elsewhere classifiedCondensed Matter Physics not elsewhere classifiedQuantum Physics not elsewhere classifiedVHEEradiotherapydose enginedeep learningflashvery high energy electronsMonte CarloIntroduction<p>External beam radiotherapy (RT) is one of the most common treatments against cancer, with photon-based RT and particle therapy being commonly employed modalities. Very high energy electrons (VHEE) have emerged as promising candidates for novel treatments, particularly in exploiting the FLASH effect, offering potential advantages over traditional modalities.</p>Methods<p>This paper introduces a Deep Learning model based on graph convolutional networks to determine dose distributions of therapeutic VHEE beams in patient tissues. The model emulates Monte Carlo (MC) simulated doses within a cylindrical volume around the beam, enabling high spatial resolution dose calculation along the beamline while managing memory constraints.</p>Results<p>Trained on diverse beam orientations and energies, the model exhibits strong generalization to unseen configurations, achieving high accuracy metrics, including a δ-index 3% passing rate of 99.8% and average relative error <1% in integrated dose profiles compared to MC simulations.</p>Discussion<p>Notably, the model offers three to six orders of magnitude increased speed over full MC simulations and fast MC codes, generating dose distributions in milliseconds on a single GPU. This speed could enable direct integration into treatment planning optimization algorithms and leverage the model’s differentiability for exact gradient computation.</p>2024-11-20T04:02:49ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/fphy.2024.1443306.s001https://figshare.com/articles/dataset/DataSheet1_Fast_and_precise_dose_estimation_for_very_high_energy_electron_radiotherapy_with_graph_neural_networks_PDF/27859992CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/278599922024-11-20T04:02:49Z |
| spellingShingle | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF Lorenzo Arsini (15083796) Biophysics Astrophysics Applied Physics Computational Physics Condensed Matter Physics Particle Physics Plasma Physics Solar System, Solar Physics, Planets and Exoplanets Classical and Physical Optics Photonics, Optoelectronics and Optical Communications Cloud Physics Tropospheric and Stratospheric Physics High Energy Astrophysics; Cosmic Rays Mesospheric, Ionospheric and Magnetospheric Physics Space and Solar Physics Mathematical Physics not elsewhere classified Physical Chemistry of Materials Physical Chemistry not elsewhere classified Classical Physics not elsewhere classified Condensed Matter Physics not elsewhere classified Quantum Physics not elsewhere classified VHEE radiotherapy dose engine deep learning flash very high energy electrons Monte Carlo |
| status_str | publishedVersion |
| title | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| title_full | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| title_fullStr | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| title_full_unstemmed | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| title_short | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| title_sort | DataSheet1_Fast and precise dose estimation for very high energy electron radiotherapy with graph neural networks.PDF |
| topic | Biophysics Astrophysics Applied Physics Computational Physics Condensed Matter Physics Particle Physics Plasma Physics Solar System, Solar Physics, Planets and Exoplanets Classical and Physical Optics Photonics, Optoelectronics and Optical Communications Cloud Physics Tropospheric and Stratospheric Physics High Energy Astrophysics; Cosmic Rays Mesospheric, Ionospheric and Magnetospheric Physics Space and Solar Physics Mathematical Physics not elsewhere classified Physical Chemistry of Materials Physical Chemistry not elsewhere classified Classical Physics not elsewhere classified Condensed Matter Physics not elsewhere classified Quantum Physics not elsewhere classified VHEE radiotherapy dose engine deep learning flash very high energy electrons Monte Carlo |