ESTRO 2022 - Abstract Book

S1540

Abstract book

ESTRO 2022

The use of virtual bolus leads to a decrease between 1-5 percentage points in PTV D98% and D2% statistics (renormalized PTV V50% = 100% prescription) implying a need for extra effort to optimize a virtual bolus plan compared to the bolusless control case. The effect was the stronger the thicker the bolus was and the further away its HU value was from -500. More radiopaque boli were associated with a deficiency of the dose in the lateral breast. The robustness analyses revealed that in terms of the minimum dose, any virtual bolus is significantly better (D2% = 80 – 90 %) than no bolus at all (D2% < 70 %) but the best results were obtained with 10 mm thick boli in range -100 – 200 HU (D2% ≈ 90 %). Conclusion In terms of the dose homogeneity and robustness, using virtual boli with thicknesses around 10 mm and radiometric densities in the approximate range from - 100HU to 100HU appears to produce VMAT breast plans with the highest clinical quality when AXB is used for evaluation.

[1] Lizondo et al. (2019) Phys. Med. 63:56-62 [2] Rossi et al. (2019) Med. Dos. 44:266-73 [3] Han et al (2011) Med. Phys. 38:2651-64

PO-1738 Investigation into the dependence of a head and neck RapidPlan™ model on number of training plans

H. Carver 1

1 The Clatterbridge Cancer Centre NHS Foundation Trust, Radiotherapy Physics, Liverpool, United Kingdom

Purpose or Objective The implementation of RapidPlan™, a knowledge based planning solution by Varian Medical Systems, for head and neck (H&N) radiotherapy treatment plan optimisation has been shown to have the potential to improve treatment plan quality while improving planning efficiency. The impact of the number of plans used to train a H&N RapidPlan™ model on plan quality is a parameter which has not been widely investigated. This has been assessed during an investigation along with potential strategies for implementation. Materials and Methods Four H&N RapidPlan™ models were trained using varying numbers of plans(150, 120, 80 and 40) with primary dose level between 60Gy and 70Gy. The plan quality achieved by the models was assessed using 29 anonymised, previously treated test patients. Quantitative assessment was carried out using clinical planning metrics and a quality metric developed during the investigation based on clinical planning aims. Significance testing was carried out on the median differences for each considered metric between matched observations using the Wilcoxon signed-rank test. Results There was no statistically significant difference between the overall quality of plans produced by each model and the majority of individual planning metrics. Comparing each model to the corresponding clinical plans demonstrated a statistically significant improvement in plan quality for each model (p<0.05). The model trained with the least number of plans (40) resulted in median increases in Brainstem D 0.1cc and left parotid D mean relative to clinical plans when compared to the other models (>2.2Gy and >0.7Gy respectively), though these results were not statistically significant. The use of RapidPlan™ generated objectives as a starting point for manual optimisation demonstrated an overall improvement in plan quality (p<0.001) relative to clinical plans. Compared to clinical plans, this method exhibited a statistically significant reduction in median D 0.1cc to the canal(p<0.001) of 3.4Gy and brainstem(p<0.001) of 8.5Gy while improving target coverage(p<0.05). Conclusion There was insufficient evidence to suggest that the number of plans used to train a RapidPlan™ model impacts overall plan quality. For many OAR planning metrics, a small median increase was generally observed across the testing set when using the model trained with the least plans. Despite this, these results demonstrate that a large atlas of plans is not necessarily required to produce a H&N RapidPlan™ model. The implementation of a RapidPlan™ model to replace the Eclipse™ objective template as a starting point for planners has the potential to improve H&N plan quality. This study has demonstrated this approach maintains or improves OAR sparing relative to clinical plans while improving target coverage. In addition to plan quality, planning efficiency is also an important consideration and the investigation into this is ongoing.

PO-1739 Volumetric, geometric and density effects on modified gradient index for lung SABR plan evaluation

A. Thorne 1 , W. Polak 1 , A. Palmer 1

1 Portsmouth Hospitals University NHS Trust, Radiotherapy Physics, Portsmouth, United Kingdom

Purpose or Objective UK SABR Consortium guidelines [1] recommend evaluating SABR plan quality using modified gradient index (MGI, or R50%). Its constraints are derived from plans analysed during the UK’s national SABR Commissioning through Evaluation (CtE) programme, and those observed by Yaparpalvi et al [2]. The constraints are based on PTV volume, but are defined in coarse increments. This results in significantly different target R50% for PTV volumes of 19.9cc and 20.1cc.

Materials and Methods