FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2172972249> ?p ?o ?g. }

• W2172972249 endingPage "6963" @default.
• W2172972249 startingPage "6955" @default.
• W2172972249 abstract "Purpose: Radiation treatments have become increasingly more complex with the development of volumetric modulated arc therapy (VMAT) and the use of stereotactic body radiation therapy (SBRT). SBRT involves the delivery of substantially larger doses over fewer fractions than conventional therapy. SBRT–VMAT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. Electronic portal imaging devices (EPIDs) are available on most commercial linear accelerators (Linacs) and their documented use for dosimetry makes them valuable tools for patient dose verification. In this work, the authors customize and validate a physics-based model which utilizes on-treatment EPID images to reconstruct the 3D dose delivered to the patient during SBRT–VMAT delivery. Methods: The SBRT Linac head, including jaws, multileaf collimators, and flattening filter, were modeled using Monte Carlo methods and verified with measured data. The simulation provides energy spectrum data that are used by their “forward” model to then accurately predict fluence generated by a SBRT beam at a plane above the patient. This fluence is then transported through the patient and then the dose to the phosphor layer in the EPID is calculated. Their “inverse” model back-projects the EPID measured focal fluence to a plane upstream of the patient and recombines it with the extra-focal fluence predicted by the forward model. This estimate of total delivered fluence is then forward projected onto the patient's density matrix and a collapsed cone convolution algorithm calculates the dose delivered to the patient. The model was tested by reconstructing the dose for two prostate, three lung, and two spine SBRT–VMAT treatment fractions delivered to an anthropomorphic phantom. It was further validated against actual patient data for a lung and spine SBRT–VMAT plan. The results were verified with the treatment planning system (TPS) (eclipse aaa) dose calculation. Results: The SBRT–VMAT reconstruction model performed very well when compared to the TPS. A stringent 2%/2 mm χ-comparison calculation gave pass rates better than 91% for the prostate plans, 88% for the lung plans, and 86% for the spine plans for voxels containing 80% or more of the prescribed dose. Patient data were 86% for the lung and 95% for the spine. A 3%/3 mm χ-comparison was also performed and gave pass rates better than 93% for all plan types. Conclusions: The authors have customized and validated a robust, physics-based model that calculates the delivered dose to a patient for SBRT–VMAT delivery using on-treatment EPID images. The accuracy of the results indicates that this approach is suitable for clinical implementation. Future work will incorporate this model into both offline and real-time clinical adaptive radiotherapy." @default.
• W2172972249 created "2016-06-24" @default.
• W2172972249 creator A5011844340 @default.
• W2172972249 creator A5023977131 @default.
• W2172972249 creator A5063905370 @default.
• W2172972249 creator A5070861368 @default.
• W2172972249 creator A5006192309 @default.
• W2172972249 date "2015-11-12" @default.
• W2172972249 modified "2023-09-25" @default.
• W2172972249 title "An <i>in vivo</i> dose verification method for SBRT-VMAT delivery using the EPID" @default.
• W2172972249 cites W1983641888 @default.
• W2172972249 cites W1985089847 @default.
• W2172972249 cites W1987774434 @default.
• W2172972249 cites W1989475812 @default.
• W2172972249 cites W1995028951 @default.
• W2172972249 cites W1997462079 @default.
• W2172972249 cites W1998752874 @default.
• W2172972249 cites W2004365201 @default.
• W2172972249 cites W2005068907 @default.
• W2172972249 cites W2008782751 @default.
• W2172972249 cites W2014219010 @default.
• W2172972249 cites W2040809797 @default.
• W2172972249 cites W2057208460 @default.
• W2172972249 cites W2059363420 @default.
• W2172972249 cites W2063198351 @default.
• W2172972249 cites W2064410184 @default.
• W2172972249 cites W2070980315 @default.
• W2172972249 cites W2071882193 @default.
• W2172972249 cites W2074505565 @default.
• W2172972249 cites W2074511004 @default.
• W2172972249 cites W2074765702 @default.
• W2172972249 cites W2079887738 @default.
• W2172972249 cites W2080567764 @default.
• W2172972249 cites W2083145572 @default.
• W2172972249 cites W2084851290 @default.
• W2172972249 cites W2086210512 @default.
• W2172972249 cites W2091361931 @default.
• W2172972249 cites W2094005774 @default.
• W2172972249 cites W2099104461 @default.
• W2172972249 cites W2107416946 @default.
• W2172972249 cites W2120950852 @default.
• W2172972249 cites W2125063756 @default.
• W2172972249 cites W2171773399 @default.
• W2172972249 cites W3141440004 @default.
• W2172972249 doi "https://doi.org/10.1118/1.4935201" @default.
• W2172972249 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26632051" @default.
• W2172972249 hasPublicationYear "2015" @default.
• W2172972249 type Work @default.
• W2172972249 sameAs 2172972249 @default.
• W2172972249 citedByCount "26" @default.
• W2172972249 countsByYear W21729722492016 @default.
• W2172972249 countsByYear W21729722492017 @default.
• W2172972249 countsByYear W21729722492018 @default.
• W2172972249 countsByYear W21729722492019 @default.
• W2172972249 countsByYear W21729722492020 @default.
• W2172972249 countsByYear W21729722492021 @default.
• W2172972249 countsByYear W21729722492022 @default.
• W2172972249 countsByYear W21729722492023 @default.
• W2172972249 crossrefType "journal-article" @default.
• W2172972249 hasAuthorship W2172972249A5006192309 @default.
• W2172972249 hasAuthorship W2172972249A5011844340 @default.
• W2172972249 hasAuthorship W2172972249A5023977131 @default.
• W2172972249 hasAuthorship W2172972249A5063905370 @default.
• W2172972249 hasAuthorship W2172972249A5070861368 @default.
• W2172972249 hasConcept C104293457 @default.
• W2172972249 hasConcept C105795698 @default.
• W2172972249 hasConcept C120665830 @default.
• W2172972249 hasConcept C121332964 @default.
• W2172972249 hasConcept C126838900 @default.
• W2172972249 hasConcept C161471255 @default.
• W2172972249 hasConcept C168834538 @default.
• W2172972249 hasConcept C180048950 @default.
• W2172972249 hasConcept C19499675 @default.
• W2172972249 hasConcept C19527891 @default.
• W2172972249 hasConcept C201645570 @default.
• W2172972249 hasConcept C22078206 @default.
• W2172972249 hasConcept C2780387249 @default.
• W2172972249 hasConcept C2989005 @default.
• W2172972249 hasConcept C31601959 @default.
• W2172972249 hasConcept C33923547 @default.
• W2172972249 hasConcept C34445779 @default.
• W2172972249 hasConcept C509974204 @default.
• W2172972249 hasConcept C520434653 @default.
• W2172972249 hasConcept C71924100 @default.
• W2172972249 hasConcept C75088862 @default.
• W2172972249 hasConcept C9267231 @default.
• W2172972249 hasConceptScore W2172972249C104293457 @default.
• W2172972249 hasConceptScore W2172972249C105795698 @default.
• W2172972249 hasConceptScore W2172972249C120665830 @default.
• W2172972249 hasConceptScore W2172972249C121332964 @default.
• W2172972249 hasConceptScore W2172972249C126838900 @default.
• W2172972249 hasConceptScore W2172972249C161471255 @default.
• W2172972249 hasConceptScore W2172972249C168834538 @default.
• W2172972249 hasConceptScore W2172972249C180048950 @default.
• W2172972249 hasConceptScore W2172972249C19499675 @default.
• W2172972249 hasConceptScore W2172972249C19527891 @default.
• W2172972249 hasConceptScore W2172972249C201645570 @default.
• W2172972249 hasConceptScore W2172972249C22078206 @default.

• next