Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning
Knowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We u...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/14/12/2849 |
| _version_ | 1797489191499595776 |
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| author | Roni Hytönen Reynald Vanderstraeten Max Dahele Wilko F. A. R. Verbakel |
| author_facet | Roni Hytönen Reynald Vanderstraeten Max Dahele Wilko F. A. R. Verbakel |
| author_sort | Roni Hytönen |
| collection | DOAJ |
| description | Knowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We used a previously validated RapidPlanPT model and scripting to create nine KBPs, one with default and eight with altered beam angles, for 10 recent oropharynx cancer patients. The altered-angle plans were compared against the default-angle ones in terms of grade 2 dysphagia and xerostomia normal tissue complication probability (NTCP), mean doses of several organs at risk, and dose homogeneity index (HI). As KBP could be suboptimal, a proof of principle automatic iterative optimizer (AIO) was added with the aim of reducing the plan NTCP. There were no statistically significant differences in NTCP or HI between default- and altered-angle KBPs, and the altered-angle plans showed a <1% reduction in NTCP. AIO was able to reduce the sum of grade 2 NTCPs in 66/90 cases with mean a reduction of 3.5 ± 1.8%. While the altered-angle plans saw greater benefit from AIO, both default- and altered-angle plans could be improved, indicating that the KBP model alone was not completely optimal to achieve the lowest NTCP. Overall, the data showed that the model was robust to the various beam arrangements within the range described in this analysis. |
| first_indexed | 2024-03-10T00:13:56Z |
| format | Article |
| id | doaj.art-503e80ff261d44679001e0e98bc725da |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T00:13:56Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-503e80ff261d44679001e0e98bc725da2023-11-23T15:55:14ZengMDPI AGCancers2072-66942022-06-011412284910.3390/cancers14122849Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton PlanningRoni Hytönen0Reynald Vanderstraeten1Max Dahele2Wilko F. A. R. Verbakel3Varian Medical Systems Finland, 00270 Helsinki, FinlandVarian Medical Systems Belgium, 1831 Diegem, BelgiumDepartment of Radiation Oncology, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The NetherlandsDepartment of Radiation Oncology, Amsterdam UMC Location Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The NetherlandsKnowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We used a previously validated RapidPlanPT model and scripting to create nine KBPs, one with default and eight with altered beam angles, for 10 recent oropharynx cancer patients. The altered-angle plans were compared against the default-angle ones in terms of grade 2 dysphagia and xerostomia normal tissue complication probability (NTCP), mean doses of several organs at risk, and dose homogeneity index (HI). As KBP could be suboptimal, a proof of principle automatic iterative optimizer (AIO) was added with the aim of reducing the plan NTCP. There were no statistically significant differences in NTCP or HI between default- and altered-angle KBPs, and the altered-angle plans showed a <1% reduction in NTCP. AIO was able to reduce the sum of grade 2 NTCPs in 66/90 cases with mean a reduction of 3.5 ± 1.8%. While the altered-angle plans saw greater benefit from AIO, both default- and altered-angle plans could be improved, indicating that the KBP model alone was not completely optimal to achieve the lowest NTCP. Overall, the data showed that the model was robust to the various beam arrangements within the range described in this analysis.https://www.mdpi.com/2072-6694/14/12/2849knowledge-based planningintensity-modulated proton therapynormal tissue complication probabilityautomated optimization |
| spellingShingle | Roni Hytönen Reynald Vanderstraeten Max Dahele Wilko F. A. R. Verbakel Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning Cancers knowledge-based planning intensity-modulated proton therapy normal tissue complication probability automated optimization |
| title | Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning |
| title_full | Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning |
| title_fullStr | Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning |
| title_full_unstemmed | Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning |
| title_short | Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning |
| title_sort | influence of beam angle on normal tissue complication probability of knowledge based head and neck cancer proton planning |
| topic | knowledge-based planning intensity-modulated proton therapy normal tissue complication probability automated optimization |
| url | https://www.mdpi.com/2072-6694/14/12/2849 |
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