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1.
J Appl Clin Med Phys ; 23(1): e13479, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34846098

RESUMO

The Varian Ethos system allows for online adaptive treatments through the utilization of artificial intelligence (AI) and deformable image registration which automates large parts of the anatomical contouring and plan optimization process. In this study, treatments of intact prostate and prostate bed, with and without nodes, were simulated for 182 online adaptive fractions, and then a further 184 clinical fractions were delivered on the Ethos system. Frequency and magnitude of contour edits were recorded, as well as a range of plan quality metrics. From the fractions analyzed, 11% of AI generated contours, known as influencer contours, required no change, and 81% required minor edits in any given fraction. The frequency of target and noninfluencer organs at risk (OAR) contour editing varied substantially between different targets and noninfluencer OARs, although across all targets 72% of cases required no edits. The adaptive plan was the preference in 95% of fractions. The adaptive plan met more goals than the scheduled plan in 78% of fractions, while in 15% of fractions the number of goals met was the same. The online adaptive recontouring and replanning process was carried out in 19 min on average. Significant improvements in dosimetry are possible with the Ethos online adaptive system in prostate radiotherapy.


Assuntos
Neoplasias da Próstata , Radioterapia de Intensidade Modulada , Inteligência Artificial , Humanos , Masculino , Órgãos em Risco , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/radioterapia , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador
2.
J Appl Clin Med Phys ; 21(11): 88-97, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33016622

RESUMO

PURPOSE: To present the development of an in-house coded solution for treatment planning of tangential breast radiotherapy that creates single click plans by emulating the iterative optimization process of human dosimetrists. METHOD: One hundred clinical breast cancer patients were retrospectively planned with an automated planning (AP) code incorporating the hybrid intensity-modulated radiotherapy (IMRT) approach. The code automates all planning processes including plan generation, beam generation, gantry and collimator angle determination, open segments and dynamic IMRT fluence and calculations. Thirty-nine dose volume histogram (DVH) metrics taken from three international recommendations were compared between the automated and clinical plans (CP), along with median interquartile analysis of the DVH distributions. Total planning time and delivery QA were also compared between the plan sets. RESULTS: Of the 39 planning metrics analyzed 23 showed no significant difference between clinical and automated planning techniques. Of the 16 metrics with statistically significant variations, 2 were improved in the clinical plans in comparison to 14 improved in the AP plans. Automated plans produced a greater number of ideal plans against international guidelines as per EviQ (AP:77%, CP:68%), RTOG 1005 (AP:80%, CP:71%), and London Cancer references (AP:80%, CP:75%). Delivery QA results for both techniques were equivalent. Automated planning techniques resulted in an average reduction in planning time from 23 to 5 minutes. CONCLUSION: We have introduced an automated planning code with iterative optimization that produces equivalent quality plans to manual clinical planning. The resultant change in workflow results in a reduction in treatment planning times.


Assuntos
Neoplasias da Mama , Radioterapia de Intensidade Modulada , Mama , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/radioterapia , Feminino , Humanos , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Estudos Retrospectivos
3.
J Appl Clin Med Phys ; 21(12): 27-42, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33068070

RESUMO

Varian (Palo Alto, California, United States) recently released an online adaptation treatment platform, Ethos, which has introduced a new Dose Preview and Automated Plan Generation module despite sharing identical beam data with the existing Halcyon linac. The module incorporates a preconfigured beam model and the Acuros XB algorithm (Ethos AXB model) to generate final dose calculations from an initial fluence optimization. In this study, we comprehensively validated the accuracy of the Ethos AXB model by comparing it against the Halcyon AXB model, the Halcyon Anisotropic Analytical Algorithm (AAA) model, and measurements acquired on an Ethos linac. Results indicated that the Ethos AXB model demonstrated a comparable if not superior dosimetric accuracy to the Halcyon AXB model in basic and complex calculations, and at the same time its dosimetric accuracy in modulated and heterogeneous plans was better than that of the Halcyon AAA model. Despite the fact that the same algorithm was utilized, the Ethos AXB model and the Halcyon AXB model still exhibited variations across a range of tests, although these variations were predominantly insignificant in the clinical environment. The accuracy of the Ethos AXB model has been successfully verified in this study and is considered appropriate for the current clinical scope. On the basis of this study, clinical physicists can perform a data validation instead of a full data commissioning when implementing the Ethos system, thereby adopting a more efficient approach for Ethos installation.


Assuntos
Radiometria , Planejamento da Radioterapia Assistida por Computador , Algoritmos , Humanos , Imagens de Fantasmas , Dosagem Radioterapêutica
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