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• W2067846665 abstract "Aims: The accuracy of computer treatment planning systems is important in achieving clinically acceptable dose distributions. The pencil beam (PB) algorithm on Helax-TMS is currently used for all clinical treatment planning at the two centres involved in this study. However, it has been shown that the Helax-TMS collapsed cone (CC) algorithm is more accurate in regions of heterogeneity, such as the thorax, and head and neck. The aim of this study was to show the actual dose delivered to the patient when treating with a Helax-TMS PB plan, by using the corresponding Helax-TMS CC plan as the reference standard. Materials and methods: Thirty PB treatment plans (for lung and oesophageal treatments) were recalculated using the CC algorithm, and plans were then compared. Results: The number of monitor units required to deliver the prescription dose differed between algorithms, by up to 3.4%. In most cases, the CC algorithm calculated more monitor units than the PB, indicating under-dosage at the prescription point during treatment. The dose distributions also seemed less homogeneous when calculated using the CC algorithm. The minimum dose to the planning target volume (PTV) was lower than the PB plan suggested in every case, by up to 23.2%. ICRU homogeneity requirements (i.e. a minimum 95% of the prescription dose in the PTV) were not met in any of the cases. Even with some attempts at optimisation, conformance to these requirements was difficult. Conclusion: The CC algorithm has several factors limiting its suitability for routine clinical use. However, it is an important milestone in radiotherapy treatment planning, and should be used to show expected changes in computer planned dose distributions with new accurate dose algorithms. It is worthwhile considering dose homogeneity requirements well before the advent of anticipated Monte Carlo-based models." @default.
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• W2067846665 date "2004-04-01" @default.
• W2067846665 modified "2023-09-27" @default.
• W2067846665 title "The Clinical Implications of the Collapsed Cone Planning Algorithm" @default.
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• W2067846665 doi "https://doi.org/10.1016/j.clon.2003.11.014" @default.
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