Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy
Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization al...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Aumüller, Philipp [verfasserIn] Rothfuss, Andreas [verfasserIn] Polednik, Martin [verfasserIn] Abo-Madyan, Yasser [verfasserIn] Ehmann, Michael [verfasserIn] Giordano, Frank A. [verfasserIn] Clausen, Sven [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Zeitschrift für medizinische Physik - Amsterdam [u.a.] : Elsevier, 1990, 32, Seite 173-187 |
|---|---|
| Übergeordnetes Werk: |
volume:32 ; pages:173-187 |
| DOI / URN: |
10.1016/j.zemedi.2021.06.003 |
|---|
| Katalog-ID: |
ELV007968035 |
|---|
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| 024 | 7 | |a 10.1016/j.zemedi.2021.06.003 |2 doi | |
| 035 | |a (DE-627)ELV007968035 | ||
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| 100 | 1 | |a Aumüller, Philipp |e verfasserin |0 (orcid)0000-0002-2282-7645 |4 aut | |
| 245 | 1 | 0 | |a Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
| 264 | 1 | |c 2021 | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
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| 520 | |a Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. | ||
| 650 | 4 | |a Brachytherapy | |
| 650 | 4 | |a LDR | |
| 650 | 4 | |a Seeds | |
| 650 | 4 | |a Robotic | |
| 650 | 4 | |a Path planning | |
| 650 | 4 | |a Inverse optimization | |
| 700 | 1 | |a Rothfuss, Andreas |e verfasserin |0 (orcid)0000-0002-7323-6861 |4 aut | |
| 700 | 1 | |a Polednik, Martin |e verfasserin |4 aut | |
| 700 | 1 | |a Abo-Madyan, Yasser |e verfasserin |0 (orcid)0000-0003-2205-503X |4 aut | |
| 700 | 1 | |a Ehmann, Michael |e verfasserin |4 aut | |
| 700 | 1 | |a Giordano, Frank A. |e verfasserin |0 (orcid)0000-0001-5243-4781 |4 aut | |
| 700 | 1 | |a Clausen, Sven |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Zeitschrift für medizinische Physik |d Amsterdam [u.a.] : Elsevier, 1990 |g 32, Seite 173-187 |h Online-Ressource |w (DE-627)510617662 |w (DE-600)2231492-1 |w (DE-576)272350818 |x 1876-4436 |7 nnns |
| 773 | 1 | 8 | |g volume:32 |g pages:173-187 |
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10.1016/j.zemedi.2021.06.003 doi (DE-627)ELV007968035 (ELSEVIER)S0939-3889(21)00061-1 DE-627 ger DE-627 rda eng 610 DE-600 44.31 bkl Aumüller, Philipp verfasserin (orcid)0000-0002-2282-7645 aut Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. Brachytherapy LDR Seeds Robotic Path planning Inverse optimization Rothfuss, Andreas verfasserin (orcid)0000-0002-7323-6861 aut Polednik, Martin verfasserin aut Abo-Madyan, Yasser verfasserin (orcid)0000-0003-2205-503X aut Ehmann, Michael verfasserin aut Giordano, Frank A. verfasserin (orcid)0000-0001-5243-4781 aut Clausen, Sven verfasserin aut Enthalten in Zeitschrift für medizinische Physik Amsterdam [u.a.] : Elsevier, 1990 32, Seite 173-187 Online-Ressource (DE-627)510617662 (DE-600)2231492-1 (DE-576)272350818 1876-4436 nnns volume:32 pages:173-187 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.31 Medizinische Physik AR 32 173-187 |
| spelling |
10.1016/j.zemedi.2021.06.003 doi (DE-627)ELV007968035 (ELSEVIER)S0939-3889(21)00061-1 DE-627 ger DE-627 rda eng 610 DE-600 44.31 bkl Aumüller, Philipp verfasserin (orcid)0000-0002-2282-7645 aut Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. Brachytherapy LDR Seeds Robotic Path planning Inverse optimization Rothfuss, Andreas verfasserin (orcid)0000-0002-7323-6861 aut Polednik, Martin verfasserin aut Abo-Madyan, Yasser verfasserin (orcid)0000-0003-2205-503X aut Ehmann, Michael verfasserin aut Giordano, Frank A. verfasserin (orcid)0000-0001-5243-4781 aut Clausen, Sven verfasserin aut Enthalten in Zeitschrift für medizinische Physik Amsterdam [u.a.] : Elsevier, 1990 32, Seite 173-187 Online-Ressource (DE-627)510617662 (DE-600)2231492-1 (DE-576)272350818 1876-4436 nnns volume:32 pages:173-187 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.31 Medizinische Physik AR 32 173-187 |
| allfields_unstemmed |
10.1016/j.zemedi.2021.06.003 doi (DE-627)ELV007968035 (ELSEVIER)S0939-3889(21)00061-1 DE-627 ger DE-627 rda eng 610 DE-600 44.31 bkl Aumüller, Philipp verfasserin (orcid)0000-0002-2282-7645 aut Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. Brachytherapy LDR Seeds Robotic Path planning Inverse optimization Rothfuss, Andreas verfasserin (orcid)0000-0002-7323-6861 aut Polednik, Martin verfasserin aut Abo-Madyan, Yasser verfasserin (orcid)0000-0003-2205-503X aut Ehmann, Michael verfasserin aut Giordano, Frank A. verfasserin (orcid)0000-0001-5243-4781 aut Clausen, Sven verfasserin aut Enthalten in Zeitschrift für medizinische Physik Amsterdam [u.a.] : Elsevier, 1990 32, Seite 173-187 Online-Ressource (DE-627)510617662 (DE-600)2231492-1 (DE-576)272350818 1876-4436 nnns volume:32 pages:173-187 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.31 Medizinische Physik AR 32 173-187 |
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10.1016/j.zemedi.2021.06.003 doi (DE-627)ELV007968035 (ELSEVIER)S0939-3889(21)00061-1 DE-627 ger DE-627 rda eng 610 DE-600 44.31 bkl Aumüller, Philipp verfasserin (orcid)0000-0002-2282-7645 aut Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. Brachytherapy LDR Seeds Robotic Path planning Inverse optimization Rothfuss, Andreas verfasserin (orcid)0000-0002-7323-6861 aut Polednik, Martin verfasserin aut Abo-Madyan, Yasser verfasserin (orcid)0000-0003-2205-503X aut Ehmann, Michael verfasserin aut Giordano, Frank A. verfasserin (orcid)0000-0001-5243-4781 aut Clausen, Sven verfasserin aut Enthalten in Zeitschrift für medizinische Physik Amsterdam [u.a.] : Elsevier, 1990 32, Seite 173-187 Online-Ressource (DE-627)510617662 (DE-600)2231492-1 (DE-576)272350818 1876-4436 nnns volume:32 pages:173-187 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.31 Medizinische Physik AR 32 173-187 |
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10.1016/j.zemedi.2021.06.003 doi (DE-627)ELV007968035 (ELSEVIER)S0939-3889(21)00061-1 DE-627 ger DE-627 rda eng 610 DE-600 44.31 bkl Aumüller, Philipp verfasserin (orcid)0000-0002-2282-7645 aut Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. Brachytherapy LDR Seeds Robotic Path planning Inverse optimization Rothfuss, Andreas verfasserin (orcid)0000-0002-7323-6861 aut Polednik, Martin verfasserin aut Abo-Madyan, Yasser verfasserin (orcid)0000-0003-2205-503X aut Ehmann, Michael verfasserin aut Giordano, Frank A. verfasserin (orcid)0000-0001-5243-4781 aut Clausen, Sven verfasserin aut Enthalten in Zeitschrift für medizinische Physik Amsterdam [u.a.] : Elsevier, 1990 32, Seite 173-187 Online-Ressource (DE-627)510617662 (DE-600)2231492-1 (DE-576)272350818 1876-4436 nnns volume:32 pages:173-187 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.31 Medizinische Physik AR 32 173-187 |
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Aumüller, Philipp @@aut@@ Rothfuss, Andreas @@aut@@ Polednik, Martin @@aut@@ Abo-Madyan, Yasser @@aut@@ Ehmann, Michael @@aut@@ Giordano, Frank A. @@aut@@ Clausen, Sven @@aut@@ |
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The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. 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Aumüller, Philipp |
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Aumüller, Philipp ddc 610 bkl 44.31 misc Brachytherapy misc LDR misc Seeds misc Robotic misc Path planning misc Inverse optimization Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
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610 DE-600 44.31 bkl Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy Brachytherapy LDR Seeds Robotic Path planning Inverse optimization |
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ddc 610 bkl 44.31 misc Brachytherapy misc LDR misc Seeds misc Robotic misc Path planning misc Inverse optimization |
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Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
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Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
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Aumüller, Philipp Rothfuss, Andreas Polednik, Martin Abo-Madyan, Yasser Ehmann, Michael Giordano, Frank A. Clausen, Sven |
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10.1016/j.zemedi.2021.06.003 |
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multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
| title_auth |
Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
| abstract |
Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. |
| abstractGer |
Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. |
| abstract_unstemmed |
Purpose: Robotic systems to assist needle placements for low-dose rate brachytherapy enable conformal dose planning only restricted to path planning around risk structures. We report a treatment planning system (TPS) combining multiple direction needle-path planning with inverse dose optimization algorithms.Methods: We investigated in a path planning algorithm to efficiently locate needle injection points reaching the target volume without puncturing risk structures. A candidate needle domain with all combinations of trajectories is used for the optimization process. We report a modular algorithm for inverse radiation plan optimization. The initial plan with V100>99% is generated by the “greedy optimizer”. The “remove-seed algorithm” reduces the number of seeds in the high dose regions. The “depth-optimizer” varies the insertion depth of the needles. The “coverage-optimizer” locates under-dosed areas in the target volume and supports them with an additional amount of seeds. The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. The TPS allows taking full advantage of robotic navigation tools to enable a new precise and safe method of minimally invasive low-dose-rate brachytherapy. |
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Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy |
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Rothfuss, Andreas Polednik, Martin Abo-Madyan, Yasser Ehmann, Michael Giordano, Frank A. Clausen, Sven |
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The dose calculation algorithm is benchmarked on an image set of a phantom with a liver metastasis (prescription dose D p r = 100 Gy ) and is re-planned in a commercial CE-marked TPS to compare the calculated dose grids using a global gamma analysis. The inverse optimizer is benchmarked by calculating 10 plans on the same phantom to investigate the stability and statistical variability of the dose parameters.Results: The path planning algorithm efficiently removes 72.5% of all considered injection points. The candidate needle domain consists of combinations of 1971 tip points and 827 injection points. The global gamma analysis with gamma 1 % = 2.9 Gy , 1 mm showed a pass rate of 98.5 % . The dose parameters were V 100 = 99.1 ± 0.3 % , V 150 = 76.4 ± 2.5 % , V 200 = 44.5 ± 5.5 % and D 90 = 125.9 ± 3.6 Gy and 10.7 ± 1.3 needles with 34.0 ± 0.8 seeds were used. The median of the TPS total running time was 4.4minutes.Conclusions: The TPS generates treatment plans with acceptable dose coverage in a reasonable amount of time. The gamma analysis shows good accordance to the commercial TPS. 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