A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose

Optimization model based on generalized equivalent uniform dose (gEUD) linear sub-score or quadratic sub-score, which only penalizes doses higher or lower than the prescribed dose gEUD<sub>0</sub>, has the shortcomings of semi-deviation, vanishing gradient and non-increasing in the feasi...

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Autor principal:	Caiping Guo
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Intensity-modulated radiation therapy gEUD hybrid criteria regularization Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/651192a4e9bf4fc18f64103a4320623b
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id	oai:doaj.org-article:651192a4e9bf4fc18f64103a4320623b
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spelling	oai:doaj.org-article:651192a4e9bf4fc18f64103a4320623b2021-11-09T00:03:11ZA New Radiotherapy Optimization Model Based on Equivalent Uniform Dose2169-353610.1109/ACCESS.2021.3123166https://doaj.org/article/651192a4e9bf4fc18f64103a4320623b2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9585435/https://doaj.org/toc/2169-3536Optimization model based on generalized equivalent uniform dose (gEUD) linear sub-score or quadratic sub-score, which only penalizes doses higher or lower than the prescribed dose gEUD<sub>0</sub>, has the shortcomings of semi-deviation, vanishing gradient and non-increasing in the feasible solution space. When gradient-based optimization algorithms are used to solve the radiotherapy inverse optimization problem, these algorithms may get trapped in a local minimum. To address these drawbacks, this study proposes a new gEUD-based optimization model based on regularization theory. In the new optimization model, a dosage whether lower or higher than the prescribed dose is assigned different penalties. To test its efficiency, it was tested on a phantom TG119, and two types of clinic cases(one prostate cancer case and one head and neck cancer case). The improved optimization model was compared with unimproved gEUD-based optimization model. Additionally, the improved gEUD-based optimization model was compared with another improved gEUD-based linear optimization model proposed by us. The gradient-based optimization algorithm(L-BFGS) was applied to solve these large-scale optimization problems. Optimization based on our improved optimization model is capable of improving the organs at risk (OARS) sparing while maintaining the same planning target volume (PTV) coverage. In practice, although the DV-based optimization should be able to gain a similar plan, parameters adjustment of the optimization model is time-consuming. The new gEUD-based hybrid physical–biological optimization model has the potential to expand the solution space and improve the quality of radiotherapy plan.Caiping GuoIEEEarticleIntensity-modulated radiation therapygEUDhybrid criteriaregularizationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 146233-146243 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Intensity-modulated radiation therapy gEUD hybrid criteria regularization Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Intensity-modulated radiation therapy gEUD hybrid criteria regularization Electrical engineering. Electronics. Nuclear engineering TK1-9971 Caiping Guo A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
description	Optimization model based on generalized equivalent uniform dose (gEUD) linear sub-score or quadratic sub-score, which only penalizes doses higher or lower than the prescribed dose gEUD<sub>0</sub>, has the shortcomings of semi-deviation, vanishing gradient and non-increasing in the feasible solution space. When gradient-based optimization algorithms are used to solve the radiotherapy inverse optimization problem, these algorithms may get trapped in a local minimum. To address these drawbacks, this study proposes a new gEUD-based optimization model based on regularization theory. In the new optimization model, a dosage whether lower or higher than the prescribed dose is assigned different penalties. To test its efficiency, it was tested on a phantom TG119, and two types of clinic cases(one prostate cancer case and one head and neck cancer case). The improved optimization model was compared with unimproved gEUD-based optimization model. Additionally, the improved gEUD-based optimization model was compared with another improved gEUD-based linear optimization model proposed by us. The gradient-based optimization algorithm(L-BFGS) was applied to solve these large-scale optimization problems. Optimization based on our improved optimization model is capable of improving the organs at risk (OARS) sparing while maintaining the same planning target volume (PTV) coverage. In practice, although the DV-based optimization should be able to gain a similar plan, parameters adjustment of the optimization model is time-consuming. The new gEUD-based hybrid physical–biological optimization model has the potential to expand the solution space and improve the quality of radiotherapy plan.
format	article
author	Caiping Guo
author_facet	Caiping Guo
author_sort	Caiping Guo
title	A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
title_short	A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
title_full	A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
title_fullStr	A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
title_full_unstemmed	A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose
title_sort	new radiotherapy optimization model based on equivalent uniform dose
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/651192a4e9bf4fc18f64103a4320623b
work_keys_str_mv	AT caipingguo anewradiotherapyoptimizationmodelbasedonequivalentuniformdose AT caipingguo newradiotherapyoptimizationmodelbasedonequivalentuniformdose
_version_	1718441389456359424

A New Radiotherapy Optimization Model Based on Equivalent Uniform Dose

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