Autor según el artículo: Brooks FMD; Glenn MC; Hernandez V; Saez J; Mehrens H; Pollard-Larkin JM; Howell RM; Peterson CB; Nelson CL; Clark CH; Kry SF
Departamento: Ciències Mèdiques Bàsiques
Autor/es de la URV: Hernandez Masgrau, Victor
Palabras clave: Vmat Radiotherapy, intensity-modulated Radiotherapy planning, computer-assisted Radiotherapy dosage Quality assurance Particle accelerators Organs at risk Neoplasms Mlc Imrt Humans Dose calculation accuracy Complexity metrics Beam modeling Algorithms
Resumen: To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy. Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric. Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites. Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.
Áreas temáticas: Radiology, nuclear medicine and imaging Radiology, nuclear medicine & medical imaging Radiation Medicine (miscellaneous) Medicina ii Medicina i Interdisciplinar Instrumentation Ensino Engenharias iv Engenharias ii Astronomia / física
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: victor.hernandez@urv.cat
Identificador del autor: 0000-0003-3770-8486
Fecha de alta del registro: 2024-09-07
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://aapm.onlinelibrary.wiley.com/doi/10.1002/acm2.14318
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Journal Of Applied Clinical Medical Physics. 25 (5): e14318-
Referencia de l'ítem segons les normes APA: Brooks FMD; Glenn MC; Hernandez V; Saez J; Mehrens H; Pollard-Larkin JM; Howell RM; Peterson CB; Nelson CL; Clark CH; Kry SF (2024). A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy.. Journal Of Applied Clinical Medical Physics, 25(5), e14318-. DOI: 10.1002/acm2.14318
DOI del artículo: 10.1002/acm2.14318
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2024
Tipo de publicación: Journal Publications
Repositori URV