Online

ESTRO 2020

Session Item

Saturday
November 28
10:30 - 11:30
Online
Proffered papers 7: Evaluating and predicting toxicity in RT
1208
Proffered Papers
RTT
11:20 - 11:30
Dosimetric and NTCP comparison of photon treatment techniques in lung cancer
Djoya Hattu, The Netherlands
OC-0113

Abstract

Dosimetric and NTCP comparison of photon treatment techniques in lung cancer
Authors: Dirk De Ruysscher.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Daisy Emans.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Djoya Hattu.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Sebastiaan Nijsten.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Stephanie Peeters.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Wouter van Elmpt.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands), Judith van Loon.(Maastricht Radiation Oncology MAASTRO clinic, Radiotherapy, Maastricht, The Netherlands)
Show Affiliations
Purpose or Objective

Plan quality is generally evaluated and compared based on dosimetric values. Normal tissue complication probability (NTCP) models that predict the probability of side effects can assist in evaluating which dosimetric improvements are of clinical relevance. In The Netherlands NTCP models are used to select patients for proton therapy: the model-based approach (Langendijk et al. 2013). The aim of this planning study is to quantify the difference between commonly used photon treatment techniques based on dosimetric values and NTCP values calculated according to the models used for proton therapy selection.

Material and Methods

26 NSCLC patients were planned with 3 commonly used photon treatment techniques: a 5 field sliding window IMRT technique, a VMAT technique (2 half arc beams) and a hybrid technique (2 opposing APPA fields complemented with 1 or 2 VMAT beams). Treatment plans were made with Eclipse (v15.5 Varian Medical Systems, Palo Alto) by experienced RTTs and met the dosimetric requirements of the clinical guidelines for target coverage and OARs (De Ruysscher et al. 2017). The prescribed dose to the PTV was 60 Gy in 30 fractions. Treatment plans were evaluated for PTV coverage and OARs based on dosimetric and NTCP values. NTCPs were calculated according to 3 validated NTCP models used for proton therapy selection: mortality (Defraene et al. 2019), grade 2 pneumonitis (Appelt et al. 2014) and grade 2 dysphagia (Wijsman et al. 2015). Analogous to selecting patients for proton therapy, the cut-off in ∆NTCP to determine the optimal photon technique was ≥2% for grade ≥3 toxicity and ≥10% for grade 2 toxicity.

Results

All 78 plans met the V95%≥95% requirement for the primary tumor and involved node coverage. Median dose, volume and NTCP values for the hybrid, VMAT and IMRT technique are depicted in Table 1 for the MHD, MLD, V5 of the lungs and the MED. The lowest MHD was achieved with the VMAT technique. Both MLD and MED were not affected by a particular technique, whereas the V5 of the lungs was lowest using a hybrid technique. Based on NTCPs, the risk of 2-year mortality was lowest with VMAT. For grade 2 pneumonitis and dysphagia, the median differences in NTCP were ≤1%. Looking at individual patient differences, the ∆NTCP for mortality was ≥2% in 13/26 and 11/26 patients, mostly favoring VMAT (11/13) or IMRT (8/11) over the hybrid technique. The ∆NTCP for grade 2 pneumonitis did not exceed the 10% threshold. For grade 2 dysphagia only 1 patient met the 10% cut-off in favor of the hybrid technique.

Conclusion

DVH parameters and associated NTCP values according to the model-based approach allow objective selection of optimal photon techniques for lung cancer patients. Based on DVH parameters, there is a trade-off between the V5 of the lungs (hybrid) and the MHD (VMAT). According to model-based selection, VMAT is favored for most patients, predominantly due to ≥2% decreased probability of mortality. These results depend on the selected models, and these models should therefore be validated and updated on a regular basis.