Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions

Purpose To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. Methods A workflow was developed in which separate dose matrices were calculated for...

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Published inMedical physics (Lancaster) Vol. 45; no. 12; pp. 5597 - 5607
Main Authors MacDonald, R. Lee, Thomas, Christopher G., Ward, Lucy, Syme, Alasdair
Format Journal Article
LanguageEnglish
Published United States 01.12.2018
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Online AccessGet full text
ISSN0094-2405
2473-4209
2473-4209
DOI10.1002/mp.13224

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Abstract Purpose To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. Methods A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra‐arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans. Results Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03). Conclusion A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.
AbstractList To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra-arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans. Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03). A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.
Purpose To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. Methods A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra‐arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans. Results Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03). Conclusion A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.
To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses.PURPOSETo design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses.A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra-arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans.METHODSA workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra-arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans.Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03).RESULTSTreatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03).A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.CONCLUSIONA novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.
Author Thomas, Christopher G.
Ward, Lucy
MacDonald, R. Lee
Syme, Alasdair
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Keywords binary collimation
dynamic collimator motion
simulated annealing
multiple metastases
stereotactic radiosurgery
Language English
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Snippet Purpose To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of...
To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple...
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SubjectTerms binary collimation
dynamic collimator motion
multiple metastases
simulated annealing
stereotactic radiosurgery
Title Intra‐arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions
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